Possibilistic C-template clustering and its application in object detection in images

Tsai-Pei Wang*

*此作品的通信作者

研究成果: Conference contribution同行評審

2 引文 斯高帕斯(Scopus)

摘要

We present in this paper a new type of alternating-optimization based possibilistic c-shell clustering algorithm called possibilistic c-template (PCT). A template is represented by a set of line segments. A cluster prototype consists of a copy of the template after translation, scaling, and rotation transforms. This extends the capability of shell clustering beyond a few standard geometrical shapes that have been studied so far. We use a number of 2-dimensional data sets to illustrate the application of our algorithm in detecting generic template-based shapes in images. Techniques taken to relax the requirements of known number of clusters and good initialization are also described. Results for both synthetic and actual image data are presented.

原文English
主出版物標題Advances in Image and Video Technology - First Pacific Rim Symposium, PSIVT 2006, Proceedings
頁面383-392
頁數10
DOIs
出版狀態Published - 1 12月 2006
事件1st Pacific Rim Symposium on Image and Video Technology, PSIVT 2006 - Hsinchu, 台灣
持續時間: 10 12月 200613 12月 2006

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
4319 LNCS
ISSN(列印)0302-9743
ISSN(電子)1611-3349

Conference

Conference1st Pacific Rim Symposium on Image and Video Technology, PSIVT 2006
國家/地區台灣
城市Hsinchu
期間10/12/0613/12/06

指紋

深入研究「Possibilistic C-template clustering and its application in object detection in images」主題。共同形成了獨特的指紋。

引用此