Fuzzy based scaling rotational and transformation for invariant texture classification

Texture classification is important step in image processing and computer vision applications. The proposed method offers efficient way to classify the invariant texture using discrete shearlet transform and fuzzy logic. The texture features of an image are represented using shearlet energy features and shearlet co-occurrence features. These features are obtained from block based energy form of shearlet decomposed image using two levels of discrete shearlet transform with two directions and by varying the block size. Finally, the obtained parameters are used to classify the texture in an image using fuzzy logic classifier. © 2016 SERSC.