关键词: 图像多方向梯度, 块局部相位量化, 纹理特征提取

Abstract:

Gradient is an important feature of image. Local Phase Quantization（LPQ） model for texture classification based on multi-directional gradient is proposed. The texture local phase quantization model based on multi-directional gradient first extracts the gradient features from different directions of image, and then encodes the gradient features in each direction using the local phase quantization method. The gradient features in each direction coded by LPQ are connected into a matching vector. In order to make full use of the gradient information of the image, the local phase quantization method with block mode is also discussed. Experiments on two texture databases and one palmprint database fully show that local phase quantization coding for gradient information in several directions of image is an effective texture feature extraction algorithm.

Key words: multi-directional gradient of image, block local phase quantization, texture feature extraction