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Proceedings Paper

Interactive object segmentation using color similarity based nearest neighbor regions mergence
Author(s): Jun Zhang; Qieshi Zhang
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Paper Abstract

An effective object segmentation is an important task in computer vision. Due to the automatic image segmentation is hard to segment the object from natural scenes, the interactive approach becomes a good solution. In this paper, a color similarity measure based region mergence approach is proposed with the interactive operation. Some local regions, which belong to the background and object, need to be interactively marked respectively. To judge whether two adjacent regions need to be merged or not, a color similarity measure is proposed with the help of mark. Execute merging operation based on the marks in background and the two regions with maximum similarity need to be merged until all candidate regions are examined. Consequently, the object is segmented by ignoring the merged background. The experiments prove that the proposed method can obtain more accurate result from the natural scenes.

Paper Details

Date Published: 14 February 2015
PDF: 5 pages
Proc. SPIE 9445, Seventh International Conference on Machine Vision (ICMV 2014), 94450N (14 February 2015); doi: 10.1117/12.2180729
Show Author Affiliations
Jun Zhang, Waseda Univ. (Japan)
Xi'an Serv Stress Engineering Technology Co., Ltd. (China)
Qieshi Zhang, Waseda Univ. (Japan)


Published in SPIE Proceedings Vol. 9445:
Seventh International Conference on Machine Vision (ICMV 2014)
Antanas Verikas; Branislav Vuksanovic; Petia Radeva; Jianhong Zhou, Editor(s)

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