Classifying similar， counterfeit and deteriorated slices in Chinese herbal slices plays a vital role in clinical application of Chinese medicine. Traditional manual identification methods are subjective and fallible. And the classification of traditional Chinese herbal slices based on computer vision is superior in speed and accuracy， which makes Chinese herbal slice screening intelligent. Firstly， general steps of Chinese medicine recognition algorithm based on computer vision were introduced， and technical development status of preprocessing， feature extraction and recognition model of Chinese medicine images were reviewed separately. Then， 12 classes of similar and easily confused Chinese herbal slices were selected as a case to study. By constructing a dataset with 9 156 pictures of Chinese herbal slices， the recognition performance differences of traditional recognition algorithms and various deep learning models were analyzed and compared. Finally， the difficulties and future development trends of computer vision in Chinese herbal slices were summarized and prospected.