关键词: 二进小波, 量化特征, 直方图特征, 人脸识别

Abstract: A novel image texture feature descriptor is proposed which is insensitive to Gaussian blur and Gaussian noise.The four scales horizontal high-pass components and vertical high-pass components of image are extracted by dyadic wavelet transform.These components are arranged at each pixel in image，and then uniformly quantized in an eight-dimensional space，represented as an integer using binary coding.At last，a histogram sequence is computed by concatenated histogram from each region which is the descriptor of the image.Due only using the high-frequency coefficients，the descriptor is more robust to Gaussian noise.Experiment on face image recognition shows that the method has attractive features than LBP and LPQ which is the state-of-art local feature descriptors.

Key words: dyadic wavelet, quantization feature, histogram feature, face recognition