Research of an Improved LBP Algorithm in Texture Classification Based on Rotation Invariance and Statistical Phase Distribution
Han Yan · Chinese Journal of Computers · 2011
The traditional LBP algorithm lacks the phase analysis of graphical element,so it could not better distinguish the same classified texture image formed by the rotation of graphical element.The paper proposes an improved texture classification algorithm based on LBP,combining two important properties of graphical elements: rotational invariance and statistical phase distribution.The algorithm utilizes the equivalence classes about rotational invariance to reduce the texture features,and can reduce the error caused by texture rotation.It uses the statistical phase distribution to further subdivide the texture image,and can resolve the under-classifying problem caused by extracting rotational invariance feature of graphical element.The improved method can well reserve some advantages of the traditional LBP.In the experiment,the tool of texture classification is Mean Shift,and the test texture images are from Brodatz.The experiment shows that the statistical phase can well describe the direction distribution of the graphical element in the texture image.Comparing with the algorithm which only uses the rotational invariance feature,the new one can improve the rate of correct classification to 98.1%,which is obviously better than the traditional WTGGD and LBP.