A COMBINATION OF LOCAL AND DIFFERENTIAL IMAGE INFORMATION BASED ON HYBRID ACTIVE CONTOUR METHOD FOR IMAGE SEGMENTATION

Abstract

Image segmentation is the actual scheme of partitioning an image into several regions and it has a big importance in image processing and computer vision. Until now, there is a variety of segmentation methods, and among them active contour model is a popular one widely studied and used in many applications. The fundamental idea of active contour model is to construct some constraints to the object and realize the segmentation process by curve evolution. Depending on the type of information used active contour method scan roughly be categorized into three categories: edge based, region based and hybrid active contour models. This research we proposed a hybrid active contour method combining the local and differential gray intensity information for inhomogeneous image segmentation.