Indexed by:会议论文
Date of Publication:2016-06-12
Included Journals:EI、CPCI-S、Scopus
Volume:2016-September
Page Number:1837-1841
Abstract:In this paper, a novel image descriptor, called Color Binary Correlation (CBC), is proposed for image retrieval. This method defines and describes the structure elements utilizing binary patterns based on colors and edge orientation respectively, and thus integrate texture with the other two properties. Besides, its variants CBCri and CBCu2, which are presented for rotated invariance and "unform" patterns respectively, are presented and analyzed for image retrieval. The experimental results in Corel-1K and Corel-10K datasets demonstrate that our descriptors are more robust and discriminative than other methods and CBC shows better performance than CBCri and CBCu2 because of taking more possible patterns into consideration.
Associate Professor
Supervisor of Master's Candidates
Gender:Male
Alma Mater:大连理工大学
Degree:Doctoral Degree
School/Department:创新创业学院
Discipline:Computer Applied Technology
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