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文章基本信息

  • 标题:Fuzzy split and merge for shadow detection
  • 作者:Remya K. Sasi ; V.K. Govindan
  • 期刊名称:Egyptian Informatics Journal
  • 印刷版ISSN:1110-8665
  • 出版年度:2015
  • 卷号:16
  • 期号:1
  • 页码:29-35
  • DOI:10.1016/j.eij.2014.11.003
  • 出版社:Elsevier
  • 摘要:Presence of shadow in an image often causes problems in computer vision applications such as object recognition and image segmentation. This paper proposes a method to detect the shadow from a single image using fuzzy split and merge approach. Split and merge is a classical algorithm used in image segmentation. Predicate function in the classical approach is replaced by a Fuzzy predicate in the proposed approach. The method follows a top down approach of recursively splitting an image into homogeneous quadtree blocks, followed by a bottom up approach by merging adjacent unique regions. The method has been compared with previous approaches and found to be better in performance in terms of accuracy.
  • 关键词:Shadow detection ; Split and merge ; Fuzzy predicate ; ANFIS
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