Image segmentation with the competitive learning based MS model

In this paper, we propose a competitive learning approach to image segmentation by coupling the Mumford-Shah (MS) model and the Distance Sensitive Rival Penalized Competitive Learning (DSRPCL) mechanism, being denoted as the DBMS model. Actually, the DBMS model with the evolution of the level set function can get highly accurate segmentation of the image by automatically detecting the appropriate number of segmented regions and overcoming the problems of vacuum and overlap. It is demonstrated by experimental results on BSDS500 that our DBMS approach can obtain the state-of-the-art segmentation result under the evaluation of ODS index.