Segmentation-based Object Categorization
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Segmentation-based Object Categorization
The image segmentation problem is concerned with partitioning an image into multiple regions according to some homogeneity criterion. This article is primarily concerned with graph theoretic approaches to image segmentation applying graph partitioning via minimum cut or maximum cut. Segmentation-based object categorization can be viewed as a specific case of spectral clustering applied to image segmentation. Applications of image segmentation * Image compression ** Segment the image into homogeneous components, and use the most suitable compression algorithm for each component to improve compression. * Medical diagnosis ** Automatic segmentation of MRI images for identification of cancerous regions. * Mapping and measurement ** Automatic analysis of remote sensing data from satellites to identify and measure regions of interest. * Transportation ** Partition a transportation network makes it possible to identify regions characterized by homogeneous traffic states. Segm ...
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Image Segmentation
In digital image processing and computer vision, image segmentation is the process of partitioning a digital image into multiple image segments, also known as image regions or image objects (Set (mathematics), sets of pixels). The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze.Linda Shapiro, Linda G. Shapiro and George C. Stockman (2001): "Computer Vision", pp 279–325, New Jersey, Prentice-Hall, Image segmentation is typically used to locate objects and Boundary tracing, boundaries (lines, curves, etc.) in images. More precisely, image segmentation is the process of assigning a label to every pixel in an image such that pixels with the same label share certain characteristics. The result of image segmentation is a set of segments that collectively cover the entire image, or a set of Contour line, contours extracted from the image (see edge detection). Each of the pixels in a region ...
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