Rotation Scale Invariant Texture Classification for a Computational Engine

Texture analysis is a highly significant area in the arena of computer vision and connected pitches. Not the least, classification is also equally important and laudable zone in the area of understanding the texture pattern and is gaining a lot of interest among the researchers in the field of computer vision. It finds a widespread application in area of pattern classification, robotic applications, textile industries etc. In this study, rotation invariant texture has been analyzed and a novel Rotation scale invariant texture classification algorithm has been proposed and tested which is found to be very efficacious and improved results are obtained with the same. The proposed algorithm has been made to undergo testing with standard data sets as UMD dataset, Vision Texture (VisTex), UIUC dataset. The results are discussed clearly with a line of justification being drawn.