Image retrieval based on an improved CS-LBP descriptor

The texture spectrum descriptors, center-symmetric local binary pattern (CS-LBP) and its extension D-LBP are effective for region description. However, they discard the low frequency information of a region. A novel improved operator, named ID-LBP, is proposed based on D-LBP in this paper. The new o...

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Bibliographic Details
Published in2010 2nd IEEE International Conference on Information Management and Engineering pp. 115 - 117
Main Authors Sun Junding, Zhu Shisong, Wu Xiaosheng
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2010
Subjects
center-symmetric local binary pattern
Computer science
Control engineering
direction local binary pattern
Frequency
Histograms
Image databases
Image retrieval
Laboratories
Pattern analysis
Robustness
Sun
texture spectrum
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ISBN9781424452637
1424452635
DOI10.1109/ICIME.2010.5477432

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Summary:The texture spectrum descriptors, center-symmetric local binary pattern (CS-LBP) and its extension D-LBP are effective for region description. However, they discard the low frequency information of a region. A novel improved operator, named ID-LBP, is proposed based on D-LBP in this paper. The new operator classifies the local pattern based on the relativity between the local gray mean and the center-symmetric pixels instead of the gray variation between the center-symmetric pixels and the center pixel as D-LBP. Comparisons are given among CS-LBP, D-LBP and ID-LBP on two commonly used image databases and the experimental results show the performance improvement of the new method.
ISBN:9781424452637
1424452635
DOI:10.1109/ICIME.2010.5477432