关键词: 活动轮廓模型, 局部灰度差异, 图像分割, 水平集, 区域可变的能量拟合（RSF）模型

Abstract: The existing local models are easy to fall into local minimum when segmenting the images with intensity inhomogeneity, which leads to the phenomenon that the evolution curve remains in the background or inside the target and can not continue to evolve and causing the segmentation failure, a model is put forward. The proposed model introduces a local intensity difference term in the energy function to drive the evolution curve across the background or inside the target by maximizing the difference between the target and the background in the neighborhood of all points on the evolution curve until it stably remains at the target edge. The experimental results show that the proposed model in this paper can effectively solve the problem caused by the local minimum in local models and improves the accuracy of complex images such as image inhomogeneity and reduces the sensitivity to the initial contour.

Key words: active contour model, local intensity difference, image segmentation, level set method, Region-Scalable Fitting（RSF） model