Object Segmentation by Comparison of Active Contour Snake and Level Set in Biomedical Applications

Automatic foreground object segmentation is a fascinating, a demanding research area, and an exigent problem in biomedical applications. Existing works cannot segment concave objects and completely dependent on initial curve that is initialized manually by the users, and must be closer to the object. Due to these limitations, most of them were considered as semi-automatic approaches. In this paper, we incorporated active contours (level-set) based on Bhattacharya distance to the Chan and Vese energy functional such that are not only minimized the differences within each region but also maximized the distance between the two regions as well. Compared with active contour snake, the proposed model gave more accurate results that segment the foreground objects automatically.