Image Segmentation

Segmentation methods in image processing and analysis

Image segmentation is the process of dividing an image into multiple parts. This is typically used to identify objects or other relevant information in digital images. There are many different ways to perform image segmentation, including:

Thresholding methods such as Otsu’s method
Color-based Segmentation such as K-means clustering
Transform methods such as watershed segmentation
Texture methods such as texture filters

An effective approach to performing image segmentation includes using algorithms, tools, and a comprehensive environment for data analysis, visualization, and algorithm development. See Image Processing Toolbox™ for more information.

Examples and How To

Software Reference

See also: Steve on Image Processing, image enhancement, digital image processing, image transform, image analysis, geometric transformations and image registration, image processing and computer vision, feature extraction, optical flow, color profile, image analysis, image thresholding, edge detection, image registration, ransac, pattern recognition, affine transformation, lab color

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