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標題:A New Cluster Validity Measure and Its Application to Image Compression
學年93
學期1
出版(發表)日期2004/11/01
作品名稱A New Cluster Validity Measure and Its Application to Image Compression
作品名稱(其他語言)
著者Chou, C.H.; Su, M.C.; Lai, Eugene
單位淡江大學電機工程學系
出版者
著錄名稱、卷期、頁數Pattern Analysis and Applications 7, pp.205-220
摘要Many validity measures have been proposed for evaluating clustering results. Most of these popular validity measures do not work well for clusters with different densities and/or sizes. They usually have a tendency of ignoring clusters with low densities. In this paper, we propose a new validity measure that can deal with this situation. In addition, we also propose a modified K-means algorithm that can assign more cluster centres to areas with low densities of data than the conventional K-means algorithm does. First, several artificial data sets are used to test the performance of the proposed measure. Then the proposed measure and the modified K-means algorithm are applied to reduce the edge degradation in vector quantisation of image compression.
關鍵字Clustering algorithm;Cluster validity;Image compression;Pattern recognition;Vector quantisation
語言英文
ISSN1433-755X;1433-7541
期刊性質國外
收錄於
產學合作
通訊作者
審稿制度
國別英國
公開徵稿
出版型式,電子版,紙本
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