出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：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. 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 its
applicability extends to other methods such as classification, feature extraction and pattern
recognition. 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.
