Abstract：The Region-Scalable Fitting(RSF) model can be used to segment images with intensity inhomogeneity, but it is so sensitive to the location of initial curve and is easy to fall into local minimums that limits its practical application. Therefore，a region-based active contour model combining the fuzzy means clustering (FCM) in a variational level set formulation is proposed in this paper. In the proposed method, it uses the fuzzy means clustering algorithm for image preprocessing, and the results of binarization of the pre-processing serves as the initial contour of the Next level set evolution, which solves the sensitivity to the location of initial curve; The local energy item is defined as a linear combination of the RSF model and our model by taking domain and range kernel functions into account, which can make up for the defects that sampling weights are only related to spatial distance and improve the accuracy of segmentation. Also, it establishes a global fitting force by introducing the fuzzy membership of the Cluster analysis that serves as the global information of image and combine with the improved CV active contour model, which can increase the self-adaptability of the model and can also accelerate the speed of convergence of the proposed model. Experimental results show that the proposed model allows for automatic initialization and is less sensitive to noise, while it has been applied to images with intensity inhomogeneity with desirable results.
赵杰,祁永梅,潘正勇. 融合模糊全局和双核局部信息的活动轮廓模型[J]. , 2014, 35(3): 663-666.
ZHAO Jie，QI Yong-mei，PAN Zheng-yong. Active Contour Model of Combining Fuzzy Global and Dual-core Local Information
