电子学报2018，Vol.46Issue(6)：1312-1318,7.DOI:10.3969/j.issn.0372-2112.2018.06.006
基于自适应区域限制FCM的图像分割方法
Adaptive Region Constrained FCM Algorithm for Image Segmentation
摘要
Abstract
An image segmentation method based on robust regional constraint FCM ( Fuzzy C-Means) is proposed, which combines hidden Markov random filed (HMRF) model with FCM. In order to improve the performance of the pro-posed method,the consistency of superpixels of the input image is adaptively used as a priori in clustering process. The pro-posed method first obtains the superpixels of the image,and for each superpixel,calculates a contribution of each pixel to the superpixel and the contributions are used to compute the superpixel's membership functions. And then the pointwise prior probabilities of pixels are calculated with pixel-level membership function or region-level membership function according to whether the superpixel to which the pixels belong has the dominant label. The use of region-level membership function is to guide the direction of clustering optimization, and thus there are some unused labels which are removed in the iteration process. Finally,the segmentation result is obtained after iteration stop. Experimental results demonstrate the good perform-ance of the proposed method.关键词
图像分割/模糊聚类/超像素/主标签/区域限制Key words
image segmentation/fuzzy clustering/super pixels/dominant label/region constraint分类
信息技术与安全科学引用本文复制引用
李磊,董卓莉,张德贤..基于自适应区域限制FCM的图像分割方法[J].电子学报,2018,46(6):1312-1318,7.基金项目
河南省教育厅自然科学项目(No.15A520057) （No.15A520057）
河南省科技厅自然科学项目(No.132102210494,No.162102210189) （No.132102210494,No.162102210189）
高层次人才基金(No.21476062) （No.21476062）
省属高校基本科研业务费专项资金(No.2016QNJH25) （No.2016QNJH25）
