Scale and rotation invariant texture classification

Numerous approaches have been reported towards texture classification. The vast majority of these approaches assume, either explicitly or implicitly that the training and test texture samples have identical scale and orientation. Such an assumption is rather restrictive in many practical applications. In this paper, we discuss texture classification approaches whose performances are not affected by changes in scale and orientation. Previous work on scale and rotation invariant texture classification is summarised, followed by suggestions for future research work