Review of Image Segmentation Techniques: A Survey
Image segmentation is a relevant research area in Computer Vision and hundreds of segmentation algorithms have been proposed in the last 30 years. Image segmentation is a mechanism used to divide an image into multiple segments. The main goal is to make image more simple and meaningful. Most methods can be classified into three groups: the analytical, the empirical goodness and the empirical discrepancy groups. Each group has its own characteristics. After a brief description of each method in every group, some comparative discussions about different method groups are first carried out. An experimental comparison for some empirical (goodness and discrepancy) methods commonly used is then performed to provide a rank of their evaluation abilities. In addition, some special methods are also discussed. This study is helpful for an appropriate use of existing evaluation methods and for improving their performance as well as for systematically designing new evaluation methods.