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image segmentation matlab code
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In computer vision, image segmentation is the process of partitioning a digital image into multiple segments (sets of pixels, also known as super pixels). The goal of segmentation is to simplify and / or change the representation of an image into something that is more meaningful and easy to analyze. Image segmentation is typically used to locate objects and boundaries (lines, curves, etc.) in images. More precisely, image segmentation is the process of assigning a tag to each pixel in an image such that pixels with the same tag share certain characteristics.

The result of image segmentation is a set of segments that collectively cover the entire image, or a set of contours extracted from the image (see edge detection). Each of the pixels in a region is similar with respect to some feature or computed property, such as colour, intensity, or texture. Adjacent regions are significantly different with respect to the same feature (s). When applied to a stack of images, typical of medical images, the resulting contours after image segmentation can be used to create 3D reconstructions with the aid of interpolation algorithms such as Marching cubes.
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