A Review of Three-Dimensional Imaging Technologies for Pavement Distress Detection and Measurements
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paper_title: Automated Imaging Technologies for Pavement Distress Surveys

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This circular documents state-of-the-art techniques and technologies in the acquisition of pavement surface images, and basic requirements needed to automatically identify and classify pavement surface distresses. The basics of film or magnetic tape–based image acquisition are presented. The circular also discusses digital acquisition and reports on the new laser-based imaging system with its high-quality image and low-power usage, as well as the potential for using 3-D laser imaging technology for pavement surveys.
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paper_title: Detection of Pavement Distresses Using 3D Laser Scanning Technology

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The 3D laser scanning is one of the exceptionally versatile and efficient technologies for accurately capturing large sets of 3D coordinates. 3D laser scanner uses a technique that employs reflected laser pulses to create accurate digital models of existing objects. For 3D survey, detection of pavement distresses, such as potholes, large-area utility cuts or patches, is possible application where laser scanner technology excels. The traditional surveying and evaluation of distresses on pavement are extremely rough and restrictive as it implies lane or even entire road closures. In the study, the accurate 3D point-cloud points with their elevations were captured during scanning and extracted focusing on specific distress features by means of a grid-based processing approach. The experimental results indicate that the severity and coverage of distresses can be accurately and automatically quantified to calculate the needed amounts of filled materials. This application is the first attempt and can assist pavement engineers in monitoring pavement performance and estimating repair funding.
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paper_title: Elements of automated survey of pavements and a 3D methodology

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Sound transportation infrastructure is critical for economic development and sustainability. Pavement condition is a primary concern among agencies of the roadway infrastructure. Automation has become possible in recent years on collecting data and producing results for certain aspects of pavement performance, while challenges remain in several other categories, such as automated cracking survey. This paper reviews the technological advances on automated survey of pavements, and discusses the most recent breakthroughs by the team led by the author in using 3D laser imaging for capturing 1 mm surface images of pavements.
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paper_title: Pavement cracking measurements using 3D laser-scan images

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Pavement condition surveying is vital for pavement maintenance programs that ensure ride quality and traffic safety. This paper first introduces an automated pavement inspection system which uses a three-dimensional (3D) camera and a structured laser light to acquire dense transverse profiles of a pavement lane surface when it carries a moving vehicle. After the calibration, the 3D system can yield a depth resolution of 0.5 mm and a transverse resolution of 1.56 mm pixel−1 at 1.4 m camera height from the ground. The scanning rate of the camera can be set to its maximum at 5000 lines s−1, allowing the density of scanned profiles to vary with the vehicle's speed. The paper then illustrates the algorithms that utilize 3D information to detect pavement distress, such as transverse, longitudinal and alligator cracking, and presents the field tests on the system's repeatability when scanning a sample pavement in multiple runs at the same vehicle speed, at different vehicle speeds and under different weather conditions. The results show that this dedicated 3D system can capture accurate pavement images that detail surface distress, and obtain consistent crack measurements in repeated tests and under different driving and lighting conditions.
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paper_title: Accurate and Robust Image Alignment for Road Profile Reconstruction

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In this paper, we propose a novel approach of the two-image alignment problem based on a functional representation of images. This allows us to derive a one-to-several correspondence, multi-scale algorithm. At the same time, it also formalizes the problem as a robust estimation problem between possible matches. We then derive an accurate, robust and faster version for the alignment of edge images. The proposed algorithm is developed and tested in the context of off-line longitudinal road profile reconstruction from stereo images.
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paper_title: Stereo-vision applications to reconstruct the 3D texture of pavement surface

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Characterisation of pavement surface texture has significant effects on ride comfort and road safety. Pavement texture is typically reported as a single attribute, such as mean profile depth, root mean square roughness or hydraulic radius, which limits the usefulness of information extracted from texture measurements. Therefore, advanced methods that characterise pavement texture in three dimensions are needed. This paper reviews recent advances in the development of two imaging-based texture evaluation methods. The main objective of these methods is to recover the 3D heights of the pavement surface. Also, the validation of the proposed image-based texture indicators is examined. Results show that image-based techniques can be successfully applied to recover the 3D heights of pavement surface textures and provide substantial information on the friction and noise characteristics of the surface.
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paper_title: 3D surface profile equipment for the characterization of the pavement texture – TexScan

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Loads from vehicles alter the functional and structural characteristics of road pavements that directly affect the loss of resistance of the pavement and the users’ comfort and safety. Those alterations require constant observation and analysis of an extensive area of road surface with high precision. For such it was developed a new scanning prototype machine capable of acquiring the 3D road surface data and characterize the road texture through two algorithms that allows calculate the Estimated Texture Depth (ETD) and Texture Profile Level (L) indicators. The experimental results obtained from nine road samples validate the developed algorithms for the texture analysis and showed good agreement between the scanning prototype equipment and the traditional Sand Patch Method.
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paper_title: Pavement Crack Detection Using High-Resolution 3D Line Laser Imaging Technology

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With the advancement of 3D sensor and information technology, a high-resolution, high-speed 3D line laser imaging system has become available for pavement surface condition data collection. This paper presents preliminary results of a research project sponsored by the U. S. Department of Transportation (DOT) Research and Innovation Technology Administration (RITA) and the Commercial Remote Sensing and Spatial Information (CRSS however, the data resolution limits the detection of hairline cracks to approximately 1mm. The findings are crucial for transportation agencies to use when determining their automated pavement survey policies. Recommendations for future research are discussed in the paper.
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paper_title: Laser Scanning on Road Pavements: A New Approach for Characterizing Surface Texture

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The surface layer of road pavement has a particular importance in relation to the satisfaction of the primary demands of locomotion, such as security and eco-compatibility. Among those pavement surface characteristics, the “texture” appears to be one of the most interesting with regard to the attainment of skid resistance. Specifications and regulations, providing a wide range of functional indicators, act as guidelines to satisfy the performance requirements. This paper describes an experiment on the use of laser scanner techniques on various types of asphalt for texture characterization. The use of high precision laser scanners, such as the triangulation types, is proposed to expand the analysis of road pavement from the commonly and currently used two-dimensional method to a three-dimensional one, with the aim of extending the range of the most important parameters for these kinds of applications. Laser scanners can be used in an innovative way to obtain information on areal surface layer through a single measurement, with data homogeneity and representativeness. The described experience highlights how the laser scanner is used for both laboratory experiments and tests in situ, with a particular attention paid to factors that could potentially affect the survey.
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paper_title: Pothole Properties Measurement through Visual 2D Recognition and 3D Reconstruction

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Current pavement condition assessment methods are predominantly manual and time consuming. Existing pothole recognition and assessment methods rely on 3D surface reconstruction that requires high equipment and computational costs or relies on acceleration data which provides preliminary results. This paper presents an inexpensive solution that automatically detects and assesses the severity of potholes using vision-based data for both 2D recognition and for 3D reconstruction. The combination of these two techniques is used to improve recognition results by using visual and spatial characteristics of potholes and measure properties (width, number, and depth) that are used to assess severity of potholes. The number of potholes is deduced with 2D recognition whereas the width and depth of the potholes is obtained with 3D reconstruction. The proposed method is validated on several actual potholes. The results show that the proposed inexpensive and visual method holds promise to improve automated pothole detection and severity assessment.
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paper_title: Measurement and Characterization of Asphalt Pavement Surface Macrotexture Using Three Dimensional Laser Scanning Technology

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Pavement macrotexture plays a critical role in highway users' safety. It is also closely related to tire-pavement interaction noise. In recent years, continuous effort has been made toward three-dimensional (3D) macrotexture measurement in the field to accommodate pavement management. This study presents a newly developed macrotexture measuring system with 3D laser scanning technology. The underlying system demonstrates a series of desirable properties including: (1) 3D surface feature, (2) high speed data collection, (3) large sampling capacity, (4) high resolution and accuracy, and (5) ease of operation. Based on data collected on a real-world asphalt pavement by the system, it is demonstrated that the existing pavement macrotexture evaluation indexes are extended from two-dimensional (2D) to 3D. By comparison, it is shown that the 3D indexes are able to characterize pavement macrotexture in a more comprehensive and realistic manner. The correlation among the 3D indexes is also evaluated, which provides pavement researchers and engineers more flexibility in selecting relevant indexes in macrotexture property evaluation.
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paper_title: Aggregate Surface Areas Quantified through Laser Measurements for South African Asphalt Mixtures

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For several decades, efforts have been made by engineers and researchers in road and airfield pavements and railroads to develop methods/procedures for accurate quantification of aggregate shape and packing properties. The difficult part of the process has been the fact that aggregate particles have irregular and nonideal shapes. New research capabilities, including laser-based technology, can effectively address the difficulties associated with aggregate shape measurements to optimize asphalt mix design. This paper introduces the use of a three-dimensional (3D) laser scanning method to directly measure the surface area of aggregates used in road pavements in South Africa. As an application of the laser-based measurements, the asphalt film thicknesses of five typical South African mixtures were calculated and compared with the film thicknesses calculated from traditional methods. Based on the laser scanning method, new surface area factors were developed for coarse aggregates used in the asphalt mixtures. Overall, the study demonstrated applicability of 3D laser scanning method to characterize coarse aggregates.
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paper_title: PRIMITIVE-BASED CLASSIFICATION OF PAVEMENT CRACKING IMAGES

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Collection and analysis of pavement distress data are receiving attention for their potential to improve the quality of information on pavement condition. We present an approach for the automated classificaton of asphalt pavement distresses recorded on video or photographic film. Based on a model that describes the statistical properties of pavement images, we develop algorithms for image enhancement, segmentation, and distress classification. Image enhancement is based on subtraction of an “average” background: segmentation assigns one of four possible values to pixels based on their likelihood of belonging to the object. The classification approach proceeds in two steps: in the first step, the presence of primitives (building blocks of the various distresses) is identified, and in the second step, classification of images to a distress type (using the results from the first step) takes place. The system addresses the following distress types: longitudinal, transverse, block, alligator cracking, and plai...
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paper_title: An Unmanned Aerial Vehicle-Based Imaging System for 3D Measurement of Unpaved Road Surface Distresses

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Abstract:i¾?Road condition data are important in transportation management systems. Over the last decades, significant progress has been made and new approaches have been proposed for efficient collection of pavement condition data. However, the assessment of unpaved road conditions has been rarely addressed in transportation research. Unpaved roads constitute approximately 40% of the U.S. road network, and are the lifeline in rural areas. Thus, it is important for timely identification and rectification of deformation on such roads. This article introduces an innovative Unmanned Aerial Vehicle UAV-based digital imaging system focusing on efficient collection of surface condition data over rural roads. In contrast to other approaches, aerial assessment is proposed by exploring aerial imagery acquired from an unpiloted platform to derive a three-dimensional 3D surface model over a road distress area for distress measurement. The system consists of a low-cost model helicopter equipped with a digital camera, a Global Positioning System GPS receiver and an Inertial Navigation System INS, and a geomagnetic sensor. A set of image processing algorithms has been developed for precise orientation of the acquired images, and generation of 3D road surface models and orthoimages, which allows for accurate measurement of the size and the dimension of the road surface distresses. The developed system has been tested over several test sites with roads of various surface distresses. The experiments show that the system is capable for providing 3D information of surface distresses for road condition assessment. Experiment results demonstrate that the system is very promising and provides high accuracy and reliable results. Evaluation of the system using 2D and 3D models with known dimensions shows that subcentimeter measurement accuracy is readily achieved. The comparison of the derived 3D information with the onsite manual measurements of the road distresses reveals differences of 0.50 cm, demonstrating the potential of the presented system for future practice.
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paper_title: Comparison of pavement surface texture determination by sand patch test and 3D laser scanning

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A modern highway must be capable of proving traffic safety, comfort to passengers as well as efficient and economical transportation. In view of the increase in the number of traffic accidents due to the developments in automotive industry, the traffic safety has gathered too much consideration in recent years. Skid resistance, on which road safety depends, is closely related to the pavement surface texture. The deterioration due to the traffic loads, especially polishing effect, involves a change in surface texture. In recent years, efforts are needed to develop more advanced technologies for evaluating pavement surface texture. In this study, the 3D laser scanner was utilized to quantify the mean profile depth (MPD) of a pavement at a static location. The surface texture of asphalt concrete pavements was scanned at 31 different locations and the results have been compared with the results of sand patch test. It was found that there is a good correlation between MPD as measured by 3D laser scanning and the m ::: ean texture depth (MTD) as measured by volumetric method (sand patch test).
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paper_title: Texas Department of Transportation 3D Transverse Profiling System for High-Speed Rut Measurement

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Pavement rutting is a critical measure of road condition. Severe rutting indicates road structure deformation and exposes drivers to hazards, especially when it holds rainwater. The Pavement Management Information System requires ruts to be measured regularly for pavement condition score calculation. In the past few decades, a number of automated rut-measurement devices have been developed and used for highway speed data collection. However, all these devices exhibit limitations on measuring ground truth in practice. This paper introduces a high-speed true three-dimensional (3D) pavement surface measurement tool that can produce accurate rut data at highway speeds. Network-level data collections were conducted and the results analyzed to evaluate and verify the system.
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paper_title: CHARACTERIZATION OF ROAD MICROTEXTURE BY MEANS OF IMAGE ANALYSIS

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Abstract Road surface microtexture (sub-millimeter scale) is essential for pavement skid-resistance. However, its measurement is only possible in the laboratory on cores taken from trafficked roads, and is time consuming. For efficient road monitoring, it is necessary to develop faster methods usable on-site. Collaboration has been developed for 2 years between LCPC and the laboratory Signal, Image and Communication (SIC) to develop a measurement and characterization method for road microtexture based on image analysis. This paper deals with too complementary works: • The measurement of road microtexture. Research is focused on the image measurement and extraction of roughness information from images. The prototype using a high-resolution camera is described. The procedure separating relief from aspect-information using a photometric model for the surface is given. Image-based relief variation is compared to relief variation obtained through a laser sensor. • The characterization of road microtexture. This characterization, obtained through a geometrical and frequential analysis of images, leads to descriptors related to the shape and the density of surface asperities. Experimental programmes were carried out to validate the feasibility of measuring on-site images and to correlate surface descriptors to friction. Results are presented and discussed. Perspective for future works is given.
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paper_title: Road surface inspection using laser scanners adapted for the high precision 3D measurements of large flat surfaces

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In this paper an optical configuration based on autosynchronized laser scanning is proposed for the 3D measurement of road surfaces. The advantages of this technique over classical triangulation methods are exposed. The road inspection system developed at the National Optics Institute (NOI) using this type of laser telemetry is also presented. This system uses two autosynchronized laser scanners in order to obtain transverse 3D and intensity profiles of road surfaces. Also described are simple algorithms which detect and measure rutting and cracking conditions. Results include rut measurements on both real and simulated 3D road profiles and a crack map of an actual pavement section.
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paper_title: A New Rutting Measurement Method Using Emerging 3D Line-Laser-Imaging System

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Rut depth is one of the important pavement performance measures. Rut depth has traditionally been measured using a manual rutting measurement, which is time-consuming, labor-intensive, and dangerous. More recently, point-based bar systems (e.g., 3, 5 points) have been used by some agencies. However, studies have shown these systems might not be able to accurately measure rut depth because of limited number of sample points. There is a need to improve the accuracy and reliability of rutting measurement. With the advances of sensing technology, emerging 3D line-laser-imaging system is now capable of acquiring high-resolution transverse profile of more than 4,000 points. This provides a great opportunity for developing a reliably and accurately rut measurement method. However, there is no framework to handle this overwhelming amount of 3D range-based pavement data. A framework is proposed in this paper to acquire, process, analyze, and visualize the high-resolution 3D pavement data collected using emerging 3D line-laser-imaging system. The proposed framework includes 1) data acquisition using the sensing system, 2) data processing, 3) data segmentation, 4) data statistical analysis, 5) data visualization, and 6) decision support. A case study carried on Interstate Highway 95 (I-95) near Savannah, Georgia, at highway speed is used to demonstrate of the applicability of the proposed framework.
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paper_title: Critical Assessment of Measuring Concrete Joint Faulting Using 3D Continuous Pavement Profile Data

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AbstractFaulting has traditionally been collected by using manual methods, which are labor intensive, time-consuming, and hazardous to workers and drivers. Therefore, alternative methods for effectively and safely collecting faulting data are needed. With emerging laser technology originally designed for crack detection, high-resolution, full lane-width coverage, three-dimensional (3D) continuous pavement profile data can now be acquired. This paper critically assesses the feasibility of using this 3D continuous pavement profile data for measuring faulting with a special focus on accuracy and repeatability. Controlled field tests were conducted to evaluate the accuracy for faulting in different ranges. Field tests were conducted at highway speeds on I-16 in Georgia to evaluate the repeatability and feasibility of the proposed method. Results show the proposed method can estimate faulting with an average error of less than 1 mm compared with those measured using the Georgia fault meter, and it can achieve ...
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paper_title: Automated pavement distress inspection based on 2D and 3D information

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During the last few decades, many efforts have been made to produce automatic inspection systems to meet the specific requirements in assessing distress on the road surfaces using video cameras and image processing algorithms. However, due to the noisy images from pavement surfaces, limited success was accomplished. One major issue with pure video based systems is their inability to discriminate dark areas not caused by pavement distress such as tire marks, oil spills, shadows, and recent fillings. To overcome the limitation of the conventional imaging based methods, a probabilistic relaxation technique based on 3-dimensional (3D) information is proposed in this paper. The primary goal of this technique is to integrate conventional image processing techniques with stereovision technology to obtain an accurate topological structure of the road defects. Simulation results show the proposed system is effective and robust on a variety of pavement surfaces.
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paper_title: Using 3D laser profiling sensors for the automated measurement of road surface conditions

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In order to maximize road maintenance funds and optimize the condition of road networks, pavement management systems need detailed and reliable data on the status of the road network. To date, reliable crack and raveling data has proven difficult and expensive to obtain. To solve this problem, over the last 10 years Pavemetrics inc. in collaboration with INO (National Optics Institute of Canada) and the MTQ (Ministere des Transports du Quebec) have been developing and testing a new 3D technology called the LCMS (Laser Crack Measurement System).
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paper_title: 3D reconstruction of road surfaces using an integrated multi-sensory

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In this paper, we present our experience in building a mobile imaging system that incorporates multi-modality sensors for road surface mapping and inspection applications. Our proposed system leverages 3D laser-range sensors, video cameras, global positioning systems (GPS) and inertial measurement units (IMU) towards the generation of photo-realistic, geometrically accurate, geo-referenced 3D models of road surfaces. Based on our summary of the state-of-the-art systems for a road distress survey, we identify several challenges in the real-time deployment, integration and visualization of the multi-sensor data. Then, we present our data acquisition and processing algorithms as a novel two-stage automation procedure that can meet the accuracy requirements with real-time performance. We provide algorithms for 3D surface reconstruction to process the raw data and deliver detail preserving 3D models that possess accurate depth information for characterization and visualization of cracks as a significant improvement over contemporary commercial video-based vision systems.
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paper_title: A real-time 3D scanning system for pavement rutting and pothole detections

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Rutting and pothole are the common pavement distress problems that need to be timely inspected and ::: repaired to ensure ride quality and safe traffic. This paper introduces a real-time, automated inspection system ::: devoted for detecting these distress features using high-speed transverse scanning. The detection principle is based ::: on the dynamic generation and characterization of 3D pavement profiles obtained from structured light ::: measurements. The system implementation mainly involves three tasks: multi-view coplanar calibration, sub-pixel ::: laser stripe location, and pavement distress recognition. The multi-view coplanar scheme was employed in the ::: calibration procedure to increase the feature points and to make the points distributed across the field of view of the ::: camera, which greatly improves the calibration precision. The laser stripe locating method was implemented in four ::: steps: median filtering, coarse edge detection, fine edge adjusting, stripe curve mending and interpolation by cubic ::: splines. The pavement distress recognition algorithms include line segment approximation of the profile, searching ::: for the feature points, and parameters calculations. The parameter data of a curve segment between two feature ::: points, such as width, depth and length, were used to differentiate rutting, pothole, and pothole under different ::: constraints. The preliminary experiment results show that the system is capable of locating these pavement ::: distresses, and meets the needs for real-time and accurate pavement inspection.
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paper_title: Laser Scan System to Establish 3-D Surface Texture and Predict Friction of Pavement

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Friction of pavement is the most popular tropic which is concerned by drivers and engineers, surface texture are also widely regarded as key factor to influence it. The brief object of this study is to establish the relationship between 3 D texture and friction. In the study, the mixtures include Dense Grade Asphalt Concrete (DGAC), Stone Mastic Asphalt (SMA), and Porous Asphalt (PA). High Definition Scan Texture Machine (HDSTM) with 2D Laser CCD was adopted to measure the 2 D texture of Asphalt concrete specimens, and British Portable Tester (BPN) was also used to evaluate friction of various mixture specimen surfaces. The study was attempted to further create initial 3 D model with data of HDSTM and Computer Simulation Program. Correlation coefficients between the ratio of Surface area in unit area (SA/A) and friction was up to 0.8. SA/A could be regards as the best feasible factor to estimate the mixture surface in the ability of skid resistance, and. Based on above results, 3D texture parameter is remarkable for evaluation of friction and is was worthy of further study.
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paper_title: Pavement Distress Analysis Using Image Processing Techniques

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This paper demonstrates the feasibility of applying image processing techniques to the analysis of pavement distress due to cracking. Pavement image samples were obtained using a custom-designed data acquisition system called the Automatic Crack Monitor (ACM). The image samples containing pavement cracks are analyzed, and quantitative measures, called crack parameters, are extracted using techniques described in this paper. The crack parameters are necessary measures used in calculations of the Pavement Serviceability Index (PSI), which is used by highway maintenance engineers to decide whether a certain pavement section needs to be repaired. Experimental results are shown and the potential hardware implementation of the developed techniques is also discussed.
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paper_title: Three-View Stereo Analysis

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This correspondence describes a new stereo analysis method using three views, in which correspondence is established among three images taken from triangularly configured viewpoints. Each match-point candidate obtained by the initial matching between the first and second images is easily examined independently of the other candidates using the third image. The correspondence determination is simple, fast, and reliable. Additionally, this analysis method allows occlusion to be dealt with explicitly. The effectiveness of the three-view stereo-analysis method is demonstrated by simulation and real object experiments. Ambiguous matches are sufficiently avoided for polyhedra. Position errors are less than 2.5 mm (about 0.4 percent) with camera-object spacing of 630 mm.
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paper_title: Potential of Low-Cost, Close-Range Photogrammetry Toward Unified Automatic Pavement Distress Surveying

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Automatic pavement distress detection and data collection is important for pavement management systems. It is estimated that pavement defects cause damage costing $10 billion/year in the US alone. Despite the importance of image-based distress detection systems, they are still semi-automatic to a great extent. They rely internally on one or more threshold values during processing or may need a pre-processing stage, and the quality is affected by shadows and low or extra illumination among other factors. After years of research, processing still typically relies heavily on global or in-context pixels content analysis. Such systems lack the robust sensor modeling, hence, robust detection and modeling which cannot be achieved directly through 2D image space analysis. The exploitation of arrays of laser profilers for 3D data acquisition is an expensive approach and has limitations for enhancing or replacing image-based output. Alternatively, 3D surfaces can be generated using stereo vision techniques. This research has investigated close range photogrammetry as a robust approach to overcome the above disadvantages. The experimental work is carried out using a non-metric DSLR camera with its built-in flash and natural daylight as sources of illumination. Initial investigations show significant potential for 3D distress detection and modeling with higher spatial precision and a higher level of automation, while retaining 2D color and shading information for data fusion. The output of automatic photogrammetric processing can be further exploited directly in existing automated and semi-automated systems for updating the content, analysis and visualization of pavement management system (PMS) and geographic information systems (GIS).
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paper_title: Stereo-vision applications to reconstruct the 3D texture of pavement surface

paper_content:

Characterisation of pavement surface texture has significant effects on ride comfort and road safety. Pavement texture is typically reported as a single attribute, such as mean profile depth, root mean square roughness or hydraulic radius, which limits the usefulness of information extracted from texture measurements. Therefore, advanced methods that characterise pavement texture in three dimensions are needed. This paper reviews recent advances in the development of two imaging-based texture evaluation methods. The main objective of these methods is to recover the 3D heights of the pavement surface. Also, the validation of the proposed image-based texture indicators is examined. Results show that image-based techniques can be successfully applied to recover the 3D heights of pavement surface textures and provide substantial information on the friction and noise characteristics of the surface.
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paper_title: 3D surface profile equipment for the characterization of the pavement texture – TexScan

paper_content:

Loads from vehicles alter the functional and structural characteristics of road pavements that directly affect the loss of resistance of the pavement and the users’ comfort and safety. Those alterations require constant observation and analysis of an extensive area of road surface with high precision. For such it was developed a new scanning prototype machine capable of acquiring the 3D road surface data and characterize the road texture through two algorithms that allows calculate the Estimated Texture Depth (ETD) and Texture Profile Level (L) indicators. The experimental results obtained from nine road samples validate the developed algorithms for the texture analysis and showed good agreement between the scanning prototype equipment and the traditional Sand Patch Method.
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paper_title: Variable baseline/resolution stereo

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We present a novel multi-baseline, multi-resolution stereo method, which varies the baseline and resolution proportionally to depth to obtain a reconstruction in which the depth error is constant. This is in contrast to traditional stereo, in which the error grows quadratically with depth, which means that the accuracy in the near range far exceeds that of the far range. This accuracy in the near range is unnecessarily high and comes at significant computational cost. It is, however, non-trivial to reduce this without also reducing the accuracy in the far range. Many datasets, such as video captured from a moving camera, allow the baseline to be selected with significant flexibility. By selecting an appropriate baseline and resolution (realized using an image pyramid), our algorithm computes a depthmap which has these properties: 1) the depth accuracy is constant over the reconstructed volume, 2) the computational effort is spread evenly over the volume, 3) the angle of triangulation is held constant w.r.t. depth. Our approach achieves a given target accuracy with minimal computational effort, and is orders of magnitude faster than traditional stereo.
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paper_title: Discovering and exploiting 3D symmetries in structure from motion

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Many architectural scenes contain symmetric or repeated structures, which can generate erroneous image correspondences during structure from motion (Sfm) computation. Prior work has shown that the detection and removal of these incorrect matches is crucial for accurate and robust recovery of scene structure. In this paper, we point out that these incorrect matches, in fact, provide strong cues to the existence of symmetries and structural regularities in the unknown 3D structure. We make two key contributions. First, we propose a method to recover various symmetry relations in the structure using geometric and appearance cues. A set of structural constraints derived from the symmetries are imposed within a new constrained bundle adjustment formulation, where symmetry priors are also incorporated. Second, we show that the recovered symmetries enable us to choose a natural coordinate system for the 3D structure where gauge freedom in rotation is held fixed. Furthermore, based on the symmetries, 3D structure completion is also performed. Our approach significantly reduces drift through ”structural” loop closures and improves the accuracy of reconstructions in urban scenes.
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paper_title: A multiple-baseline stereo

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A stereo matching method that uses multiple stereo pairs with various baselines generated by a lateral displacement of a camera to obtain precise distance estimates without suffering from ambiguity is presented. Matching is performed simply by computing the sum of squared-difference (SSD) values. The SSD functions for individual stereo pairs are represented with respect to the inverse distance and are then added to produce the sum of SSDs. This resulting function is called the SSSD-in-inverse-distance. It is shown that the SSSD-in-inverse-distance function exhibits a unique and clear minimum at the correct matching position, even when the underlying intensity patterns of the scene include ambiguities or repetitive patterns. The authors first define a stereo algorithm based on the SSSD-in-inverse-distance and present a mathematical analysis to show how the algorithm can remove ambiguity and increase precision. Experimental results with real stereo images are presented to demonstrate the effectiveness of the algorithm. >
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paper_title: A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms

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Stereo matching is one of the most active research areas in computer vision. While a large number of algorithms for stereo correspondence have been developed, relatively little work has been done on characterizing their performance. In this paper, we present a taxonomy of dense, two-frame stereo methods designed to assess the different components and design decisions made in individual stereo algorithms. Using this taxonomy, we compare existing stereo methods and present experiments evaluating the performance of many different variants. In order to establish a common software platform and a collection of data sets for easy evaluation, we have designed a stand-alone, flexible C++ implementation that enables the evaluation of individual components and that can be easily extended to include new algorithms. We have also produced several new multiframe stereo data sets with ground truth, and are making both the code and data sets available on the Web.
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paper_title: Automated Pavement Distress Survey: A Review and A New Direction

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Pavement condition survey normally includes surface distresses, such as cracking, rutting, and other surface defects. Broadly, pavement roughness is also included as a condition survey item in some literature. This paper reviews past research efforts in this area conducted at several institutions, including the automated survey system of pavement surface cracking at the University of Arkansas. The paper also proposes a new direction of technology development through the use of stereovision technology for the comprehensive survey of pavement condition in its broad definition. The goal is to develop a working system that is able to establish three-dimensional (3D) surface model of pavements for the entire pavement lane-width at 1 to 2-millimeter resolution so that comprehensive condition information can be extracted from the 3D model.
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paper_title: Single lens 3D-camera with extended depth-of-field

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Placing a micro lens array in front of an image sensor transforms a normal camera into a single lens 3D camera, ::: which also allows the user to change the focus and the point of view after a picture has been taken. While ::: the concept of such plenoptic cameras is known since 1908, only recently the increased computing power of ::: low-cost hardware and the advances in micro lens array production, have made the application of plenoptic ::: cameras feasible. This text presents a detailed analysis of plenoptic cameras as well as introducing a new type ::: of plenoptic camera with an extended depth of field and a maximal effective resolution of up to a quarter of the ::: sensor resolution.
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paper_title: Light Field Photography with a Hand-held Plenoptic Camera

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This paper presents a camera that samples the 4D light field on its sensor in a single photographic exposure. This is achieved by inserting a microlens array between the sensor and main lens, creating a plenoptic camera. Each microlens measures not just the total amount of light deposited at that location, but how much light arrives along each ray. By re-sorting the measured rays of light to where they would have terminated in slightly different, synthetic cameras, we can compute sharp photographs focused at different depths. We show that a linear increase in the resolution of images under each microlens results in a linear increase in the sharpness of the refocused photographs. This property allows us to extend the depth of field of the camera without reducing the aperture, enabling shorter exposures and lower image noise. Especially in the macrophotography regime, we demonstrate that we can also compute synthetic photographs from a range of different viewpoints. These capabilities argue for a different strategy in designing photographic imaging systems. To the photographer, the plenoptic camera operates exactly like an ordinary hand-held camera. We have used our prototype to take hundreds of light field photographs, and we present examples of portraits, high-speed action and macro close-ups.
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paper_title: Autofocusing algorithm selection in computer microscopy

paper_content:

Autofocusing is a fundamental technology for automated biological and biomedical analyses and is indispensable for routine use of microscopes on a large scale. This paper presents a comprehensive comparison study of 18 focus algorithms in which a total of 139,000 microscope images are analyzed. Six samples were used with three observation methods (bright field, phase contrast, an d differential interference contrast (DIC)) under two magnifications (100/spl times/ and 400/spl times/). A ranking methodology is proposed, based on which the 18 focus algorithms are ranked. Image pre-processing is also conducted to extensively reveal the performance and robustness of the focus algorithms. The presented guidelines allow for the selection of the optimal focus algorithm for different microscopy applications.
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paper_title: Depth from Focusing and Defocusing

paper_content:

The problem of obtaining depth information from focusing and defocusing is studied. In depth from focusing, instead of the Fibonacci search, which is often trapped in local maxima, the combination of Fibonacci search and curve fitting is proposed. This combination leads to an unprecedentedly accurate result. A model of the blurring effect that takes geometric blurring as well as imaging blurring into consideration in the calibration of the blurring model is proposed. In spectrogram-based depth from defocusing, a maximal resemblance estimation method is proposed to decrease or eliminate the window effect. >
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paper_title: Monocular 3D Scene Reconstruction at Absolute Scales by Combination of Geometric and Real-aperture Methods

paper_content:

We propose a method for combining geometric and real-aperture methods for monocular 3D reconstruction of static scenes at absolute scales. Our algorithm relies on a sequence of images of the object acquired by a monocular camera of fixed focal setting from different viewpoints. Object features are tracked over a range of distances from the camera with a small depth of field, leading to a varying degree of defocus for each feature. Information on absolute depth is obtained based on a Depth-from-Defocus approach. The parameters of the point spread functions estimated by Depth-from-Defocus are used as a regularisation term for Structure-from-Motion. The reprojection error obtained from Bundle Adjustment and the absolute depth error obtained from Depth-from-Defocus are simultaneously minimised for all tracked object features. The proposed method yields absolutely scaled 3D coordinates of the scene points without any prior knowledge about the structure of the scene. Evaluating the algorithm on real-world data we demonstrate that it yields typical relative errors between 2 and 3 percent. Possible applications of our approach are self-localisation and mapping for mobile robotic systems and pose estimation in industrial machine vision.
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paper_title: Triangulation-Based Approaches to Three-Dimensional Scene Reconstruction

paper_content:

Triangulation-based approaches to three-dimensional scene reconstruction are primarily based on the concept of bundle adjustment, which allows the determination of the three-dimensional point coordinates in the world and the camera parameters based on the minimisation of the reprojection error in the image plane. A framework based on projective geometry has been developed in the field of computer vision, where the nonlinear optimisation problem of bundle adjustment can to some extent be replaced by linear algebra techniques. Both approaches are related to each other in this chapter. Furthermore, an introduction to the field of camera calibration is given, and an overview of the variety of existing methods for establishing point correspondences is provided, including classical and also new feature-based, correlation-based, dense, and spatiotemporal approaches.
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paper_title: Numerical Shape from Shading and Occluding Boundaries

paper_content:

An iterative method for computing shape from shading using occluding boundary information is proposed. Some applications of this method are shown. ::: ::: We employ the stereographic plane to express the orientations of surface patches, rather than the more commonly used gradient space. Use of the stereographic plane makes it possible to incorporate occluding boundary information, but forces us to employ a smoothness constraint different from the one previously proposed. The new constraint follows directly from a particular definition of surface smoothness. ::: ::: We solve the set of equations arising from the smoothness constraints and the image-irradiance equation iteratively, using occluding boundary information to supply boundary conditions. Good initial values are found at certain points to help reduce the number of iterations required to reach a reasonable solution. Numerical experiments show that the method is effective and robust. Finally, we analyze scanning electron microscope (SEM) pictures using this method. Other applications are also proposed.
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paper_title: Surface Reflection: Physical and Geometrical Perspectives

paper_content:

Reflectance models based on physical optics and geometrical optics are studied. Specifically, the authors consider the Beckmann-Spizzichino (physical optics) model and the Torrance-Sparrow (geometrical optics) model. These two models were chosen because they have been reported to fit experimental data well. Each model is described in detail, and the conditions that determine the validity of the model are clearly stated. By studying reflectance curves predicted by the two models, the authors propose a reflectance framework comprising three components: the diffuse lobe, the specular lobe, and the specular spike. The effects of surface roughness on the three primary components are analyzed in detail. >
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paper_title: Triangulation-Based Approaches to Three-Dimensional Scene Reconstruction

paper_content:

Triangulation-based approaches to three-dimensional scene reconstruction are primarily based on the concept of bundle adjustment, which allows the determination of the three-dimensional point coordinates in the world and the camera parameters based on the minimisation of the reprojection error in the image plane. A framework based on projective geometry has been developed in the field of computer vision, where the nonlinear optimisation problem of bundle adjustment can to some extent be replaced by linear algebra techniques. Both approaches are related to each other in this chapter. Furthermore, an introduction to the field of camera calibration is given, and an overview of the variety of existing methods for establishing point correspondences is provided, including classical and also new feature-based, correlation-based, dense, and spatiotemporal approaches.
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paper_title: Photometric method for determining surface orientation from multiple images

paper_content:

A novel technique called photometric stereo is introduced. The idea of photometric stereo is to vary the direction of incident illumi­ nation between successive images, while holding the viewing direction constant. It is shown that this provides sufficient information to deter­ mine surface orientation at each image point. Since the imaging geom­ etry is not changed, the correspondence between image points is known a priori. The technique is photometric because it uses the radiance values recorded at a single image location, in successive views, rather than the relative positions of displaced features. Photometric stereo is used in computer-based image understanding. It can be applied in two ways. First, it is a general technique for deter­ mining surface orientation at each image point. Second, it is a technique for determining object points that have a particular surface orientation. These applications are illustrated using synthesized examples.
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paper_title: The 4-source photometric stereo technique for three-dimensional surfaces in the presence of highlights and shadows

paper_content:

We present an algorithm for separating the local gradient information and Lambertian color by using 4-source color photometric stereo in the presence of highlights and shadows. We assume that the surface reflectance can be approximated by the sum of a Lambertian and a specular component. The conventional photometric method is generalized for color images. Shadows and highlights in the input images are detected using either spectral or directional cues and excluded from the recovery process, thus giving more reliable estimates of local surface parameters.
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paper_title: Continuous Road Damage Detection Using Regular Service Vehicles

paper_content:

This paper outlines an affordable system that continuously monitors the road network for surface damage like potholes and cracks. The system consists of a structured light sensor and a camera mounted on vehicles that travel the roads on a regular basis. It makes use of sensors and equipment already present on the vehicle, like GPS on transit buses. The data is collected from many vehicles, aggregated and analyzed at a central location and the assessment results are displayed interactively to facilitate road maintenance operations. The key sensor, the data it collects and the algorithm to detect cracks and potholes are described in detail.
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paper_title: Optical Coherence Tomography: An Emerging Technology for Biomedical Imaging and Optical Biopsy

paper_content:

Optical coherence tomography (OCT) is an emerging technology for performing high-resolution cross-sectional imaging. OCT is analogous to ultrasound imaging, except that it uses light instead of sound. OCT can provide cross-sectional images of tissue structure on the micron scale in situ and in real time. Using OCT in combination with catheters and endoscopes enables high-resolution intraluminal imaging of organ systems. OCT can function as a type of optical biopsy and is a powerful imaging technology for medical diagnostics because unlike conventional histopathology which requires removal of a tissue specimen and processing for microscopic examination, OCT can provide images of tissue in situ and in real time. OCT can be used where standard excisional biopsy is hazardous or impossible, to reduce sampling errors associated with excisional biopsy, and to guide interventional procedures. In this paper, we review OCT technology and describe its potential biomedical and clinical applications.
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paper_title: High-Accuracy Stereo Depth Maps Using Structured Light

paper_content:

Progress in stereo algorithm performance is quickly outpacing the ability of existing stereo data sets to discriminate among the best-performing algorithms, motivating the need for more challenging scenes with accurate ground truth information. This paper describes a method for acquiring high-complexity stereo image pairs with pixel-accurate correspondence information using structured light. Unlike traditional range-sensing approaches, our method does not require the calibration of the light sources and yields registered disparity maps between all pairs of cameras and illumination projectors. We present new stereo data sets acquired with our method and demonstrate their suitability for stereo algorithm evaluation. Our results are available at http://www.middlebury.edu/stereo/.
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paper_title: Pattern Codification Strategies in Structured Light Systems

paper_content:

Coded structured light is considered one of the most reliable techniques for recovering the surface of objects. This technique is based on projecting a light pattern and viewing the illuminated scene from one or more points of view. Since the pattern is coded, correspondences between image points and points of the projected pattern can be easily found. The decoded points can be triangulated and 3D information is obtained. We present an overview of the existing techniques, as well as a new and definitive classification of patterns for structured light sensors. We have implemented a set of representative techniques in this field and present some comparative results. The advantages and constraints of the different patterns are also discussed.
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paper_title: An all-solid-state optical range camera for 3D real-time imaging with sub-centimeter depth resolution (SwissRanger)

paper_content:

A new miniaturized camera system that is capable of 3-dimensional imaging in real-time is presented. The compact imaging device is able to entirely capture its environment in all three spatial dimensions. It reliably and simultaneously delivers intensity data as well as range information on the objects and persons in the scene. The depth measurement is based on the time-of-flight (TOF) principle. A custom solid-state image sensor allows the parallel measurement of the ::: phase, offset and amplitude of a radio frequency (RF) modulated light field that is emitted by the system and reflected back by the camera surroundings without requiring any mechanical scanning parts. In this paper, the theoretical background of the implemented TOF principle is presented, together with the technological requirements and detailed ::: practical implementation issues of such a distance measuring system. Furthermore, the schematic overview of the complete 3D-camera system is provided. The experimental test results are presented and discussed. The present camera system can achieve sub-centimeter depth resolution for a wide range of operating conditions. A miniaturized version of such a 3D-solid-state camera, the SwissRanger 2 , is presented as an example, illustrating the possibility of ::: manufacturing compact, robust and cost effective ranging camera products for 3D imaging in real-time.
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paper_title: Unsupervised Approach for Autonomous Pavement-Defect Detection and Quantification Using an Inexpensive Depth Sensor

paper_content:

AbstractCurrent pavement condition–assessment procedures are extensively time consuming and laborious; in addition, these approaches pose safety threats to the personnel involved in the process. In this study, a RGB-D sensor is used to detect and quantify defects in pavements. This sensor system consists of a RGB color image, and an infrared projector and a camera that act as a depth sensor. An approach, which does not need any training, is proposed to interpret the data sensed by this inexpensive sensor. This system has the potential to be used for autonomous cost-effective assessment of road-surface conditions. Various road conditions including patching, cracks, and potholes are autonomously detected and, most importantly, quantified, using the proposed approach. Several field experiments have been carried out to evaluate the capabilities, as well as the limitations of the proposed system. The global positioning system information is incorporated with the proposed system to localize the detected defects...
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paper_title: Outdoor RGB-D SLAM Performance in Slow Mine Detection

paper_content:

The introduction of Kinect-style RGB-D cameras has dramatically revolutionized robotics research in a very short span. However, despite their low cost and excellent indoor performance in comparison with other competing technologies, they face some basic limitations which prevent their use in outdoor environments. Perhaps for the first time, we report an outdoor application of Kinect-style cameras in a robotics application. We report the use of benchmark RGB-D SLAM algorithm in a land-mine detection application. We argue that due to the slow nature of mine-detection tasks, basic limitations of RGB-D outdoor performance are overcome or gracefully negotiated. We report results from extensive experimentation in a variety of terrains & lighting conditions for three different types of robots.
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paper_title: Pothole tagging system

paper_content:

4th Robotics and Mechatronics Conference of South Africa (RobMech 2011), CSIR International Conference Centre, Pretoria, 23-25 November 2011
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Title: A Review of Three-Dimensional Imaging Technologies for Pavement Distress Detection and Measurements

Section 1: INTRODUCTION
Description 1: This section introduces the topic, mentions the motivation behind the study, and highlights the significance of using 3D imaging technologies for pavement distress detection and measurements.

Section 2: IMAGING PAVEMENTS IN 3D: STATE OF THE ART
Description 2: This section provides a summary of the current level of technology in 3D imaging of pavements for condition monitoring. It mainly focuses on the practical application of 3D imaging and compares accuracies obtained from different systems.

Section 3: A TAXONOMY OF 3D IMAGING TECHNOLOGIES
Description 3: This section provides a comprehensive review of various 3D imaging methods from the perspective of pavement imaging, including explanations and practical considerations for each technology.

Section 4: DISCUSSION
Description 4: This section compares different 3D imaging technologies considering the geometric shapes of pavement defects and their implications. It evaluates how suitable each technology is for imaging specific types of pavement distress.

Section 5: CONCLUSION
Description 5: This section summarizes the findings of the review, highlighting the predominant use of laser scanning and suggesting other potential techniques. It provides a selection procedure for different imaging methods based on their inherent properties and the dimensional details of the distresses.