Local binary patterns

Local binary patterns (LBP) is a type of visual descriptor used for classification in computer vision.

[3][4] 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) descriptor, it improves the detection performance considerably on some datasets.

[5] A comparison of several improvements of the original LBP in the field of background subtraction was made in 2015 by Silva et al.[6] A full survey of the different versions of LBP can be found in Bouwmans et al.[7] The LBP feature vector, in its simplest form, is created in the following manner: The feature vector can now be processed using the Support vector machine, extreme learning machines, or some other machine learning algorithm to classify images.

A useful extension to the original operator is the so-called uniform pattern,[8] which can be used to reduce the length of the feature vector and implement a simple rotation invariant descriptor.

This idea is motivated by the fact that some binary patterns occur more commonly in texture images than others.