3 Kirsch direction templates are first performed pixel by pixel, and thus each pixel is characterized by an 8-dimenional edge-strength vector. Then a binary operation is performed on each edge-strength vector to obtain its integer-valued SLBKP. Finally, three SLBKP histograms are concatenated together as the final feature of each input colour image. Experimental results show that, compared with the existing structured local binary Haar pattern (SLBHP)-based feature, the proposed feature can greatly improve retrieval performance." />
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Image Retrieval Based on Structured Local Binary Kirsch Pattern

Guang-Yu KANG
Shi-Ze GUO
De-Chen WANG
Long-Hua MA
Zhe-Ming LU

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E96-D    No.5    pp.1230-1232
Publication Date: 2013/05/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E96.D.1230
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Image Processing and Video Processing
Keyword: 
image retrieval,  structured local binary Haar pattern,  structured local binary Kirsch pattern,  

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Summary: 
This Letter presents a new feature named structured local binary Kirsch pattern (SLBKP) for image retrieval. Each input color image is decomposed into Y, Cb and Cr components. For each component image, eight 33 Kirsch direction templates are first performed pixel by pixel, and thus each pixel is characterized by an 8-dimenional edge-strength vector. Then a binary operation is performed on each edge-strength vector to obtain its integer-valued SLBKP. Finally, three SLBKP histograms are concatenated together as the final feature of each input colour image. Experimental results show that, compared with the existing structured local binary Haar pattern (SLBHP)-based feature, the proposed feature can greatly improve retrieval performance.

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