自适应FCM算法在图像分割中的应用研究  

Research and application of image segmentation by adaptive FCM algorithm

作　　者：田胜利[1] 杜根远[1,2,3] 

机构地区：[1]许昌学院计算机科学与技术学院,河南许昌461000 [2]成都理工大学信息工程学院,成都610059 [3]地球探测与信息技术教育部重点实验室,成都610059

出　　处：《计算机工程与应用》2010年第13期151-153,167,共4页Computer Engineering and Applications

基　　金：国家自然科学基金No.60475040;地球探测与信息技术教育部重点实验室开放基金No.2008DTKF012~~

摘　　要：针对目前还没有较好的方法确定模糊C均值FCM聚类中C值和各个初始聚类中心这一问题,提出一种先用进化聚类快速确定初始聚类中心和聚类个数C,后用模糊C均值FCM聚类的算法,算法时间复杂度和空间复杂度与C均值FCM基本相当。应用该算法在人物图像和遥感图像中进行了分割实验验证,算法在分割的准确性和模糊边界的分隔上取得令人满意的效果。For there is no better way to make certain the initial each center of clusters and the value of C in fuzzy C-means method in the issue of image color clustering segmentation,a new method is introduced.Firstly,pixels of the image are segmented quickly based on the value of RGB by evolving clustering.At the same time the value of C is confirmed.Secondly the center of clustering that has been segmented is optimized by Fuzzy C-Means（FCM）.Finally,the image is segmented by FCM.The time complexity factor and space complexity factor of this method and the FCM are much the same.The FCM method is equivalent to this method which is proved by experiment.The method is applied to segment the remote sensing images and characters image.The results of the expriment indicate that this method is good at segmentation-accuracy and vague boundary region segmentation.

关 键 词：图像分割 进化聚类 基于内容的遥感图像检索 模糊C均值FCM聚类 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置]