A color differentiated fuzzy c-means (CDFCM) based image segmentation algorithm

Min-Jen Tsai*, Hsuan Shao Chang

*此作品的通信作者

研究成果: Conference contribution同行評審

摘要

Image segmentation is a very important process in digital image/video processing and computer vision applications. It is often used to partition an image into separated parts for further processes. For some applications (i.e., concept-based image retrieval), a successful segmentation algorithm is necessary to identity the objects effectively. In addition, how to tag the objects after the segmentation associated with keywords is also a challenge for researchers. In this study, we proposed a color differentiated fuzzy c-means (CDFCM) framework for effective image segmentation to achieve segmented objects within image which is useful for further annotation. In our experiments, we compared our approach with other FCM techniques on synthetic image with excellent performance. Furthermore, CDFCM outperforms other approaches by using the Berkeley image segmentation data set with layered annotation, which can be applied for additional operations.

原文English
主出版物標題2012 IEEE Visual Communications and Image Processing, VCIP 2012
DOIs
出版狀態Published - 2012
事件2012 IEEE Visual Communications and Image Processing, VCIP 2012 - San Diego, CA, United States
持續時間: 27 11月 201230 11月 2012

出版系列

名字2012 IEEE Visual Communications and Image Processing, VCIP 2012

Conference

Conference2012 IEEE Visual Communications and Image Processing, VCIP 2012
國家/地區United States
城市San Diego, CA
期間27/11/1230/11/12

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