期刊論文
| 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 | en |
| ISSN | 1433-755X 1433-7541 |
| 期刊性質 | 國外 |
| 收錄於 | |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | 否 |
| 國別 | GBR |
| 公開徵稿 | |
| 出版型式 | ,電子版,紙本 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/60855 ) |