Presentation 2001/3/16
Region Extraction Based on Clustering along An Object Contour
Yuki Matsuzawa, Itsuo Kumazawa, Toru Abe,
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Abstract(in English) For accurate and robust region extraction, region-based active contour models (ACM) have been proposed. However sufficient discussion has not been conducted on efficient and effective measures to introduce image properties into controlling ACM. Therefore, existing methods have problems on their processing time and the preciseness of their extraction. Considering these problems, we propose a method which introduces image properties into extraction processes effectively and efficiently by iterating clustering of region along an object contour and control of ACM. In the proposed method, the processing time is reduced by limiting the processing area to the region along an object contour. In addition, the preciseness of extraction is improved by clustering the limited region into subregions of appropriate sizes.
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Keyword(in English) Region extraction / Active contour model / Clustering / Uniformity of regions / Linear discriminant method
Paper # PRMU2000-234
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Conference Information
Committee PRMU
Conference Date 2001/3/16(1days)
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Paper Information
Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Region Extraction Based on Clustering along An Object Contour
Sub Title (in English)
Keyword(1) Region extraction
Keyword(2) Active contour model
Keyword(3) Clustering
Keyword(4) Uniformity of regions
Keyword(5) Linear discriminant method
1st Author's Name Yuki Matsuzawa
1st Author's Affiliation Graduate School of Information Science and Engineering, Tokyo Institute of Technology()
2nd Author's Name Itsuo Kumazawa
2nd Author's Affiliation Graduate School of Information Science and Engineering, Tokyo Institute of Technology
3rd Author's Name Toru Abe
3rd Author's Affiliation School of Information Science, Japan Advanced Institute of Science and Technology
Date 2001/3/16
Paper # PRMU2000-234
Volume (vol) vol.100
Number (no) 702
Page pp.pp.-
#Pages 8
Date of Issue