Wavelet Based Statistical Adapted Local Binary Patterns for Recognizing Avatar Faces

In this paper, we propose a novel face recognition technique based on discrete wavelet transform and Local Binary Pattern (LBP) with adapted threshold to recognize avatar faces in different virtual worlds. The original LBP operator mainly thresholds pixels in a specific predetermined window based on the gray value of the central pixel of that window. As a result the LBP operator becomes more sensitive to noise especially in near-uniform or flat area regions of an image. To deal with this problem we propose a new definition to the original LBP operator not based only on the value of the central pixel of a certain window, but based on all pixels values in that window. Experiments conducted on two virtual world avatar face image datasets show that our technique performs better than original LBP, wavelet LBP, adaptive LBP and wavelet adaptive LBP in terms of accuracy.