Local binary patterns: Difference between revisions

Content deleted Content added
Concept: Normalized or not, either histograms will be concatenated.
m links
Line 1:
'''Local binary patterns''' (LBP) is a type of feature used for classification in [[computer vision]]. LBP is the particular case of the Texture Spectrum model proposed in 1990.<ref>DC. He and L. Wang (1990), "Texture Unit, Texture Spectrum, And Texture Analysis", Geoscience and Remote Sensing, IEEE Transactions on, vol. 28, pp. 509 - 512.</ref><ref>L. Wang and DC. He (1990), "Texture Classification Using Texture Spectrum", Pattern Recognition, Vol. 23, No. 8, pp. 905 - 910.</ref> LBP was first described in 1994.<ref>T. Ojala, [[Matti Pietikäinen (academic)|M. Pietikäinen]], and D. Harwood (1994), "Performance evaluation of texture measures with classification based on Kullback discrimination of distributions", Proceedings of the 12th IAPR International Conference on Pattern Recognition (ICPR 1994), vol. 1, pp. 582 - 585.</ref><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> It has since been found to be a powerful feature for texture classification; it has further been determined that when LBP is combined with the [[Histogram of oriented gradients]] (HOG) classifier, it improves the detection performance considerably on some datasets.<ref>"An HOG-LBP Human Detector with Partial Occlusion Handling", Xiaoyu Wang, Tony X. Han, Shuicheng Yan, ICCV 2009</ref>
 
==Concept==
Line 23:
== See also ==
* [[Local ternary patterns]]
* [http://www.scholarpedia.org/article/Local_Binary_Patterns Local Binary Pattern (LBP) methodology in Scholarpedia]
 
==References==