EVALUATION OF DIFFERENT IMAGE SEGMENTATION METHODS WITH RESPECT TO COMPUTATIONAL SYSTEMS

Image segmentation is a fundamental step in the modern computational vision systems and its goal is to produce amore simple and meaningful representation of the image making it easier to analyze. Imagesegmentation is a subcategory of image processing ofdigital 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 its applicability extends to other methods such as classification, feature extraction and pattern recognition. Most methods are based on histogram analysis, edge detection and region-growing. 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.