Coal-rock recognition method based on distance metric learning

A coal-rock recognition method based on distance metric learning was proposed. In the method, features of coal-rock images are extracted firstly from training sets of coal-rock images. Then a fit distance metric is gotten, which can make distance between any two features of coal samples or the ones of rock samples smaller and distance between features of coal samples and rock samples bigger, so as to improve classification and recognition effect. Finally, classifier is used to recognize coal-rock. The experimental results show when extracted coal-rock features are LBP, HOG or GLCM features, the method has higher coal-rock recognition rate than coal-rock recognition methods based on Euclidean distance, LDA or ITML.