Iris Recognition Methods- Survey
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paper_title: UBIRIS: A Noisy Iris Image Database

paper_content:

This paper presents a new iris database that contains images with noise. This is in contrast with the existing databases, that are noise free. UBIRIS is a tool for the development of robust iris recognition algorithms for biometric proposes. ::: ::: We present a detailed description of the many characteristics of UBIRIS and a comparison of several image segmentation approaches used in the current iris segmentation methods where it is evident their small tolerance to noisy images.
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paper_title: Image feature extraction for application of biometric identification of iris - a morphological approach

paper_content:

We present a new approach based on morphological operators for application of biometric identification of individuals by segmentation and analysis of the iris. Algorithms based on morphological operators are developed to segment the iris region from the eye image and also to highlight chosen iris patterns. The extracted features are used to represent and characterize the iris. In order to properly extract the desired patterns, an algorithm is proposed to produce skeletons with unique paths among end-points and nodes. The representation obtained by the morphological processing is stored for identification purposes. To illustrate the efficiency of the morphological approach, some results are presented. The proposed system was derived to present low complexity implementation and low storage requirements.
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paper_title: Iris Extraction Based on Intensity Gradient and Texture Difference

paper_content:

Biometrics has become more and more important in security applications. In comparison with many other bio- metric features, iris recognition has very high recognition accuracy. Successful iris recognition depends largely on correct iris localization, however, the performance of current techniques for iris localization still leaves room for improvement. To improve the iris localization performance, we propose a novel method that optimally utilizes both the intensity gradient and texture difference. Experimental results demonstrate that our new approach gives much better results than previous approaches. In order to make the iris boundary more accurate, we present a new issue called model selection and propose a method to choose between ellipse/circle and circle/circle models. Furthermore, we propose a dome model to compute mask images and remove eyelid occlusions in the unwrapped images rather than in the original eye images with a least commitment strategy.
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paper_title: Personal Identification Based on Iris Texture Analysis

paper_content:

With an increasing emphasis on security, automated personal identification based on biometrics has been receiving extensive attention over the past decade. Iris recognition, as an emerging biometric recognition approach, is becoming a very active topic in both research and practical applications. In general, a typical iris recognition system includes iris imaging, iris liveness detection, and recognition. This paper focuses on the last issue and describes a new scheme for iris recognition from an image sequence. We first assess the quality of each image in the input sequence and select a clear iris image from such a sequence for subsequent recognition. A bank of spatial filters, whose kernels are suitable for iris recognition, is then used to capture local characteristics of the iris so as to produce discriminating texture features. Experimental results show that the proposed method has an encouraging performance. In particular, a comparative study of existing methods for iris recognition is conducted on an iris image database including 2,255 sequences from 213 subjects. Conclusions based on such a comparison using a nonparametric statistical method (the bootstrap) provide useful information for further research.
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paper_title: Video Pupil Tracking for Iris Based Identification

paper_content:

Currently, iris identification systems are not easy to use since they need a strict cooperation of the user during the snapshot acquisition process. Several acquisitions are generally needed to obtain a workable image of the iris for recognition purpose. To make the system more flexible and open to large public applications, we propose to work on the entire sequence acquired by a camera during the enrolment. Hence the recognition step can be applied on a selected number of the “best workable images” of the iris within the sequence. In this context, the aim of the paper is to present a method for pupil tracking based on a dynamic Gaussian Mixture Model (GMM) together with Kalman prediction of the pupil position along the sequence. The method has been experimented on a real video sequence captured by a near Infra-Red (IR) sensitive camera and has shown its effectiveness in nearly real time computing.
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paper_title: UBIRIS: A Noisy Iris Image Database

paper_content:

This paper presents a new iris database that contains images with noise. This is in contrast with the existing databases, that are noise free. UBIRIS is a tool for the development of robust iris recognition algorithms for biometric proposes. ::: ::: We present a detailed description of the many characteristics of UBIRIS and a comparison of several image segmentation approaches used in the current iris segmentation methods where it is evident their small tolerance to noisy images.
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paper_title: Iris recognition for biometric identification using dyadic wavelet transform zero-crossing

paper_content:

A novel biometric identification approach based on the human iris pattern is proposed. The main idea of this technique is to represent the features of the iris by fine-to-coarse approximations at different resolution levels based on the discrete dyadic wavelet transform zero-crossing representation. The resulting one-dimensional (1D) signals are compared with model features using different distances. Before performing the feature extraction, a pre-processing step is to be made by image processing techniques, isolating the iris and enhancing the area of study. The proposed technique is translation, rotation and scale invariant. Results show a classification success above 98%, achieving an equal error rate equal to 0.21% and the possibility of having null false acceptance rates with low false rejection rates.
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paper_title: How iris recognition works

paper_content:

The principle that underlies the recognition of persons by their iris patterns is the failure of a test of statistical independence on texture phase structure as encoded by multiscale quadrature wavelets. The combinatorial complexity of this phase information across different persons spans about 249 degrees of freedom and generates a discrimination entropy of about 3.2 bits/mm/sup 2/ over the iris, enabling real-time decisions about personal identity with extremely high confidence. Algorithms first described by the author in 1993 have now been tested in several independent field trials and are becoming widely licensed. This presentation reviews how the algorithms work and presents the results of 9.1 million comparisons among different eye images acquired in trials in Britain, the USA, Korea, and Japan.
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paper_title: Recent research results in iris biometrics

paper_content:

Many security applications require accurate identification of people, and research has shown that iris biometrics ::: can be a powerful identification tool. However, in order for iris biometrics to be used on larger populations, ::: error rates in the iris biometrics algorithms must be as low as possible. Furthermore, these algorithms need to ::: be tested in a number of different environments and configurations. In order to facilitate such testing, we have ::: collected more than 100,000 iris images for use in iris biometrics research. Using this data, we have developed a ::: number of techniques for improving recognition rates. These techniques include fragile bit masking, signal-level ::: fusion of iris images, and detecting local distortions in iris texture. Additionally, we have shown that large ::: degrees of dilation and long lapses of time between image acquisitions negatively impact performance.
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paper_title: Recognition of Human Iris Patterns for Biometric Identification

paper_content:

Iris recognition is an efficient method for identification of persons. This paper provides a technique for the iris recognition. A biometric system provides automatic identification of individuals. Iris is an unique feature which is applicable for identification. Unlike face recognition or finger prints, iris recognition comes from randomly distributed features. It is most reliable and accurate method of identification. This paper proposes a personal identification using iris recognition system with the help of six major steps i.e. image acquisition,localization, Isolation, normalization, feature extraction and matching and also these six steps consists a numbers of minor steps to complete each step. The boundaries of the iris, as papillary and limbic boundary, are detected by using Canny Edge Detector. We can use masking technique to isolate the iris image form the given eye image, this isolated iris image is transformed from Cartesian to polar co-ordinate. Now finally extract the unique features (feature vector) of the iris after enhancing the iris image and then perform matching process on iris code using Hamming Distance for acceptance and rejectance process. Keywords: Canny edge detection , Hamming distance , Hough transform, Masking, Histogram equalization, Haar wavelet.
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paper_title: Learning Appearance Primitives of Iris Images for Ethnic Classification

paper_content:

Iris pattern is commonly regarded as a kind of phenotypic feature without relation to genes. In our previous work, we argued that iris texture is race related, and its genetic information is illustrated in coarse scale texture features, rather than preserved in the minute local features of state-of-the-art iris recognition algorithms. In this paper, we propose a novel ethnic classification method based on learning appearance primitives of iris images. So we not only confirm that iris texture is race related, but also try to find out which kinds of iris visual primitives make iris images look different between Asian and non-Asian. In our scheme, we learned a small finite vocabulary of micro-structures, which are called iris-textons, to represent visual primitives of iris images. Then we use iris-texton histogram to capture the difference between iris textures. Finally iris images are grouped into two race categories, Asian and non-Asian, by support vector machine (SVM). Based on the proposed method, we get a higher correct classification rate (CCR) of 91.02% than our previous method on a database containing 2400 iris samples.
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paper_title: Iris recognition: an emerging biometric technology

paper_content:

In this paper, iris recognition as one of the important method of biometrics-based identification systems and iris recognition algorithm is described. As technology advances and information and intellectual properties are wanted by many unauthorized personnel. As a result many organizations have being searching ways for more secure authentication methods for the user access. In network security there is a vital emphasis on the automatic personal identification. Due to its inherent advantages biometric based verification especially iris identification is gaining a lot of attention. Iris recognition uses iris patterns for personnel identification. The system steps are capturing iris patterns; determining the location of iris boundaries; converting the iris boundary to the stretched polar coordinate system; extracting iris code based on texture analysis. The system has been implemented and tested using dataset of number of samples of iris data with different contrast quality. The developed algorithm performs satisfactorily on the images, provides 93% accuracy. Experimental results show that the proposed method has an encouraging performance.
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paper_title: A system for automated iris recognition

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This paper describes a prototype system for personnel verification based on automated iris recognition. The motivation for this endeavour stems from the observation that the human iris provides a particularly interesting structure on which to base a technology for noninvasive biometric measurement. In particular, it is known in the biomedical community that irises are as distinct as fingerprints or patterns of retinal blood vessels. Further, since the iris is an overt body its appearance is amenable to remote examination with the aid of a computer vision system. The body of this paper details the design and operation of such a system. Also presented are the results of an empirical study where the system exhibits flawless performance in the evaluation of 520 iris images. >
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paper_title: A machine-vision system for iris recognition

paper_content:

This paper describes a prototype system for personnel verification based on automated iris recognition. The motivation for this endevour stems from the observation that the human iris provides a particularly interesting structure on which to base a technology for noninvasive biometric measurement. In particular, it is known in the biomedical community that irises are as distinct as fingerprints or patterns of retinal blood vessels. Further, since the iris is an overt body, its appearance is amenable to remote examination with the aid of a machine-vision system. The body of this paper details the design and operation of such a system. Also presented are the results of an empirical study in which the system exhibits flawless performance in the evaluation of 520 iris images.
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paper_title: A Human Identification Technique Using Images of the Iris and Wavelet Transform

paper_content:

A new approach for recognizing the iris of the human eye is presented. Zero-crossings of the wavelet transform at various resolution levels are calculated over concentric circles on the iris, and the resulting one-dimensional (1-D) signals are compared with model features using different dissimilarity functions.
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paper_title: A region-based Iris feature extraction method based on 2D-wavelet transform

paper_content:

Despite significant progress made in iris recognition, handling noisy and degraded iris images is still an open problem and deserves further investigation. This paper proposes a feature extraction method to cope with degraded iris images. This method is founded on applying the 2D-wavelet transform on overlapped blocks of the iris texture. The proposed approach enables us to select the most informative wavelet coefficients providing both essential texture information and enough robustness against the degradation factors. Our experimental results on the UBIRIS database demonstrate the effectiveness of the proposed method that achieves 4.10%FRR (@ FAR=.01 %) and 0.66% EER.
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paper_title: Improving Iris Recognition Accuracy via Cascaded Classifiers

paper_content:

As a reliable approach to human identification, iris recognition has received increasing attention in recent years. The most distinguishing feature of an iris image comes from the fine spatial changes of the image structure. So iris pattern representation must characterize the local intensity variations in iris signals. However, the measurements from minutiae are easily affected by noise, such as occlusions by eyelids and eyelashes, iris localization error, nonlinear iris deformations, etc. This greatly limits the accuracy of iris recognition systems. In this paper, an elastic iris blob matching algorithm is proposed to overcome the limitations of local feature based classifiers (LFC). In addition, in order to recognize various iris images efficiently a novel cascading scheme is proposed to combine the LFC and an iris blob matcher. When the LFC is uncertain of its decision, poor quality iris images are usually involved in intra-class comparison. Then the iris blob matcher is resorted to determine the input iris' identity because it is capable of recognizing noisy images. Extensive experimental results demonstrate that the cascaded classifiers significantly improve the system's accuracy with negligible extra computational cost.
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paper_title: Personal Identification Based on Iris Texture Analysis

paper_content:

With an increasing emphasis on security, automated personal identification based on biometrics has been receiving extensive attention over the past decade. Iris recognition, as an emerging biometric recognition approach, is becoming a very active topic in both research and practical applications. In general, a typical iris recognition system includes iris imaging, iris liveness detection, and recognition. This paper focuses on the last issue and describes a new scheme for iris recognition from an image sequence. We first assess the quality of each image in the input sequence and select a clear iris image from such a sequence for subsequent recognition. A bank of spatial filters, whose kernels are suitable for iris recognition, is then used to capture local characteristics of the iris so as to produce discriminating texture features. Experimental results show that the proposed method has an encouraging performance. In particular, a comparative study of existing methods for iris recognition is conducted on an iris image database including 2,255 sequences from 213 subjects. Conclusions based on such a comparison using a nonparametric statistical method (the bootstrap) provide useful information for further research.
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paper_title: Efficient iris recognition by characterizing key local variations

paper_content:

Unlike other biometrics such as fingerprints and face, the distinct aspect of iris comes from randomly distributed features. This leads to its high reliability for personal identification, and at the same time, the difficulty in effectively representing such details in an image. This paper describes an efficient algorithm for iris recognition by characterizing key local variations. The basic idea is that local sharp variation points, denoting the appearing or vanishing of an important image structure, are utilized to represent the characteristics of the iris. The whole procedure of feature extraction includes two steps: 1) a set of one-dimensional intensity signals is constructed to effectively characterize the most important information of the original two-dimensional image; 2) using a particular class of wavelets, a position sequence of local sharp variation points in such signals is recorded as features. We also present a fast matching scheme based on exclusive OR operation to compute the similarity between a pair of position sequences. Experimental results on 2 255 iris images show that the performance of the proposed method is encouraging and comparable to the best iris recognition algorithm found in the current literature.
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paper_title: An efficient iris recognition system

paper_content:

Iris recognition, a relatively new biometric technology, has great advantages, such as variability, stability and security, and is most promising for high security environments. A new iris recognition algorithm is proposed in this paper, which adopts Independent Component Analysis (ICA) to extract iris texture feature and a competitive learning mechanism to recognize iris patterns. Experimental results show that the algorithm is efficient and adaptive to the environment, e.g. it works well even for blurred iris images, variable illumination, and interference of eyelids and eyelashes.
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paper_title: Multi-modal authentication using continuous dynamic programming

paper_content:

Storing and retrieving the behavioral and physiological templates of a person for authentication using a common algorithm is indispensable in on-line applications. This paper deals with authentication of on-line signature data and textual iris information using continuous dynamic programming [CDP]. Kinematic derived feature, acceleration is considered. The shape of acceleration plot is analysed. The experimental study depict that, as the number of training samples considered for CDP algorithm increase, the false rejection rate decrease.
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Title: Iris Recognition Methods - Survey

Section 1: INTRODUCTION
Description 1: This section introduces the concept of biometrics, with a focus on iris recognition techniques, and describes the historical development and potential applications of iris recognition systems.

Section 2: IRIS IMAGE DATASETS
Description 2: This section discusses the importance of image quality in iris recognition systems and provides an overview of publicly available iris image databases used for research and development.

Section 3: Phase-based method
Description 3: This section explains the phase-based iris recognition method, detailing the algorithm and various improvements made to enhance recognition accuracy.

Section 4: Texture-analysis based method
Description 4: This section covers iris recognition methods based on texture analysis, explaining the approaches and techniques used to identify unique iris patterns.

Section 5: Zero-Crossing representation method
Description 5: This section describes the zero-crossing representation method for iris recognition, highlighting its algorithm and the computational advantages and drawbacks.

Section 6: Approach based on intensity variations
Description 6: This section details the methods that utilize local intensity variations in iris patterns for recognition, including feature extraction processes and classification techniques.

Section 7: Approach using Independent Component Analysis
Description 7: This section describes the use of Independent Component Analysis (ICA) for iris recognition, explaining how it extracts and encodes iris texture features.

Section 8: Iris authentication based on Continuous Dynamic Programming
Description 8: This section discusses the iris authentication method based on Continuous Dynamic Programming (CDP), focusing on kinematic characteristics and plot segmentation for verification.

Section 9: PRODUCTS AND SOLUTIONS
Description 9: This section provides an overview of iris authentication products and solutions used in applications such as civilian identification management programs.

Section 10: CONCLUSION
Description 10: This section summarizes the unique aspects of iris recognition, discusses various approaches, and suggests future directions for developing novel techniques in this domain.