A region extraction method using multiple active contour models

Abstract

A new method for extracting an object region in a complex scene image is proposed. For improving the accuracy and the robustness of region extraction, to the region of a single object, the proposed method applies multiple active contour models (ACMs) controlled by the statistical characteristics of image data. Around the object boundary, these ACMs compete with each other and each ACM extracts a subregion of uniform image properties. As a result of this competition, the entire region of an object is extracted as a set of several subregions. For the proposed method it is necessary to set many initial contours. To lighten this load, a procedure for making multiple initial contours from a single initial curve is also proposed. In this procedure, a few initial curves are set in an image, each initial curve is divided into segments at the optimal loci, and initial contours are made by dilating these segments.