Abstract: The coal gangue identification method based on optical image has the advantages of simple equipment, easy realization, greenness and environmental protection, and it is an important way to realize intelligent coal gangue separation.There are two research ways. One way requiresextracting artificial features for recognition, which generally includes four steps: coal and gangue image data set collection, image preprocessing, feature extraction and selection, and coal and gangue recognition. The other way uses deep learning neural network to independently extractfeatures.This paper summarizes the different methods in the two research ways, and points out that the existing identification methods have shortcomings such as incomplete coal gangue image data set, incomplete feature understanding, and failure to give consideration to both efficiency and real-time performance. Suggestions for efficient coal gangue identification are put forward.