Texture feature method based on Gaussian local binary pattern

Abstract

The texture description of machine vision is important for image analysis and pattern recognition. To improve the robustness of feature describing, a texture feature based on Gaussian local binary pattern(LBP) is proposed in this paper. Firstly, the Gaussian filtering is used to construct the multi-scale images as the image pyramid after image enhancement. Secondly, the local binary pattern is improved to enhance the rotation invariance and noise immunity. The pattern is extracted by using the mean value and the principal direction. Finally, for the different scales, the feature vector of three local binary patterns is extracted and reduced by histogram for image classification. The experiment result shows the feature has good distinguishability and efficiency and it is applicable for image classification.

Keywords

• texture feature
• Gaussian filtering
• local binary pattern
• image analysis