Extraction method of texture feature of images of coal and gangue

In view of problems of less extraction feature parameters and low recognition precision existed in image processing methods of coal and gangue, an extraction method of texture feature of images of coal and gangue fused with local binary pattern and gray level co-occurrence matrix was proposed. Firstly, the preprocessed images of coal and gangue were transformed into local binary pattern images, then the local binary pattern images were used to generate gray level co-occurrence matrix, the mean value and normalization of those texture features including angular second moment, correlation, contrast and entropy were processed. Finally, support vector machine was used for samples training and recognition results were obtained. The experimental results show that the method can effectively extract the texture feature of images of coal and gangue, and the recognition rates of coal and gangue are respectively 94% and 96%.