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Texture classification is one of the problems which has been paid muchattention on by computer scientists since late 90s. If texture classificationis done correctly and accurately, it can be used in many cases such as Patternrecognition, object tracking, and shape recognition. So far, there have been somany methods offered to solve this problem. Near all these methods have triedto extract and define features to separate different labels of textures reallywell. This article has offered an approach which has an overall process on theimages of textures based on Local binary pattern and Gray Level Co-occurrencematrix and then by edge detection, and finally, extracting the statisticalfeatures from the images would classify them. Although, this approach is ageneral one and is could be used in different applications, the method has beentested on the stone texture and the results have been compared with some of theprevious approaches to prove the quality of proposed approach.

Texture Classification Approach Based on Combination of Edge & Co-occurrence and Local Binary Pattern