一种适用于灰度图像分割的快速FCM算法  

A QUICK FCM ALGORITHM FOR GRAY IMAGES SEGMENTATION

作　　者：丁震[1] 胡钟山[1] 杨静宇[1] 唐振民[1] 邬永革[1] 

机构地区：[1]南京理工大学计算机科学系,210094

出　　处：《模式识别与人工智能》1997年第2期133-139,共7页Pattern Recognition and Artificial Intelligence

摘　　要：模糊C均值(FCM)算法用于灰度图像分割是一种非监督模糊聚类后再标定的过程.然而,FCM算法用于图像数据聚类时的最大缺陷是运算的开销太大.这就限制了这种方法在图像分割中的应用.本文根据FCM算法和灰度图像的特点,提出了一种适用于灰度图像分割的快速模糊C-均值(QFCM)算法.该方法降低了运算开销,使得分割耗时明显减少.本文从数学和实验上证明了这种算法的有效性和可行性.It is a procedure of the label following a unsupervised fuzzy clustering that fuzzy c-means (FCM) algorithm is applied for intensity image segmentation. However the fatal defciency of FCM algorithm, for image data clustering, is the operational cost very high, which limit its application in image segmentation. In the paper, a quick fuzzy c-means (QFCM) algorithm, for intensity image segmentation, is proposed on the basis of the characters of FCM algorithm and intensity images, with which the operational cost is decreased and the time-consuming of segmentation is obviously reduced. The effectiveness and the feasibility of the algorithm is proved on mathematics and the experiment.

关 键 词：图像分割 模糊聚类 FCM算法 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]