Local binary patterns: Difference between revisions

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{{Wikify|date=April 2010}}

Local Binary Patterns (abbreviated LBP) is a type of feature used for [[classification]] in computer vision. It was first described by Ojala, Pietikäinen and Harwood in 1996 <ref>T. Ojala, M. Pietikäinen, and D. Harwood (1996), "A Comparative Study of Texture Measures with Classification Based on Feature Distributions", Pattern Recognition, vol. 29, pp. 51-59</ref> , and has since been found to be a powerful feature for texture classification. It has also been found that when combined with the HOG classifier, it yields the best classifier of humans (i.e. person vs. non-person), among the classifiers usually considered in academic literature<ref>"An HOG-LBP Human Detector with Partial Occlusion Handling", Xiaoyu Wang, Tony X. Han, Shuicheng Yan, ICCV 2009</ref>.

==Basic Idea==