Interactive object segmentation using color similarity based nearest neighbor regions mergence

Jun Zhang, Qieshi Zhang

研究成果: Conference contribution

抄録

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.

本文言語English
ホスト出版物のタイトルProceedings of SPIE - The International Society for Optical Engineering
出版社SPIE
9445
ISBN(印刷版)9781628415605
DOI
出版ステータスPublished - 2015
イベント7th International Conference on Machine Vision, ICMV 2014 - Milan
継続期間: 2014 11月 192014 11月 21

Other

Other7th International Conference on Machine Vision, ICMV 2014
CityMilan
Period14/11/1914/11/21

ASJC Scopus subject areas

  • 応用数学
  • コンピュータ サイエンスの応用
  • 電子工学および電気工学
  • 電子材料、光学材料、および磁性材料
  • 凝縮系物理学

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