LBP texture feature extraction algorithm. First detection window is divided into 1616 small area (cell), one pixel in each cell, its circular neighborhood of 8 points (You can also ring neighborhood, as shown in Figure 3-4 example of application of the LBP algorithm, three neighborhood shown) clockwise or counterclockwise, the center pixel value than the adjacent points, then adjacent points assigned to 1, otherwise the assignment is 0, so that each point will an 8-bit binary number (usually converted to a decimal number). And then computing the histogram of each cell, each number (assuming that is a decimal number) the frequency (that is, one on each pixel next to the interior point for a binary sequence of statistics), then the histogram normalized. Finally, get the histogram of each cell to connect, to get the whole image of the LBP texture features

TextureLBP.h
TextureLBP.cpp

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