Описание тега image-segmentation

In image processing, image segmentation is the process of partitioning an image into multiple segments (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. 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 visual characteristics.

The result of image segmentation is a set of segments that collectively cover the entire image. Each of the pixels in a region are similar with respect to some characteristic or computed property, such as color, intensity, or texture. Adjacent regions are significantly different with respect to the same characteristic(s).

Image segmentation is somewhat related to perceptual grouping: the spatial organization of visual stimuli. Some image segmentation algorithms attempt to employ Gestalt Laws of perceptual grouping to produce visually meaningful image segments.

Some popular image segmentation algorithms are Normalized cuts (by Shi and malik) and Mean-shift (by Comaniciu and Meer).