REGION-BASED ACTIVE CONTOUR DRIVEN BY GLOBAL INTENSITY FITTING ENERGY  

作　　者：Tian Yun Zhou Mingquan Wu Zhongke Wang Xingce 

机构地区：[1]College of Information Science ＆ Technology, Beijing Normal University, Beijing 100875, China

出　　处：《Journal of Electronics(China)》2010年第4期480-489,共10页电子科学学刊（英文版）

基　　金：Supported by the State Key Program of National Natural Science of China (No. 61003134, 60736008);the National Natural Science Foundation of China (No. 60803082);the Key Program of Natural Science of Beijing (No.4081002)

摘　　要：In this paper, we present a novel region-based active contour model based on global in-tensity fitting energy in a variational level set framework. Meanwhile, an internal energy term is in-troduced, and it forces the level set function to be close to a signed distance function. Image global information utilized efficiently makes the proposed model insensitive to noise, and the introduced penalty term can avoid the costly re-initialization for the evolving level set function, which not only speeds up the contour evolvement, but also improves accuracy of the final contour. Comparisons with other classical region-based models, such as Chan-Vese model and Region-Scalable Fitting (RSF) model, show the advantages of our model in terms of efficiency and accuracy. Moreover, the model is robust to noise.In this paper, we present a novel region-based active contour model based on global in-tensity fitting energy in a variational level set framework. Meanwhile, an internal energy term is in-troduced, and it forces the level set function to be close to a signed distance function. Image global information utilized efficiently makes the proposed model insensitive to noise, and the introduced penalty term can avoid the costly re-initialization for the evolving level set function, which not only speeds up the contour evolvement, but also improves accuracy of the final contour. Comparisons with other classical region-based models, such as Chan-Vese model and Region-Scalable Fitting （RSF） model, show the advantages of our model in terms of efficiency and accuracy. Moreover, the model is robust to noise.

关 键 词：Region-based active contours Internal energy Global energy Level set RE-INITIALIZATION 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]