In order to overcome the weakness of tradition CS-LBP descriptor in rotation-invariant

in this paper

we propose a new CS-LBP texture spectrum descriptor from the perspective of the human visual. It integrates the rotation of texture pattern with the shift operation of string. Based on the concept of texture pattern equivalent

a more effective method is designed to enhance the anti-rotation ability of the new descriptor. Experimental results show that the new descriptor and method have with more rotation robustness

and improve the clustering accuracy of rotary texture image by 9% to 38%.