Evaluation of Different Image Segmentation Methods With Respect to Computational Systems

摘要

Image segmentation is a fundamental step in the modern computational vision systems and itsgoal is to produce amore simple and meaningful representation of the image making it easier toanalyze. Image segmentation is a subcategory of image processing of digital images and,basically, it divides a given image into two parts: the object(s) of interest and the background.Image segmentation is typically used to locate objects and boundaries in images and itsapplicability extends to other methods such as classification, feature extraction and patternrecognition. Most methods are based on histogram analysis, edge detection and regiongrowing.Currently, other approaches are presented such as segmentation by graph partition,using genetic algorithms and genetic programming. This paper presents a review of this area,starting with taxonomy of the methods followed by a discussion of the most relevant ones.