Abstract: In view of the shortcomings of traditional difference behavior feature classification methods,such as ineffective recognition of small difference behavior and low classification accuracy,a classification method of small difference behavior feature based on intelligent vision was put forward.Firstly,with the immune multi-agent method,the features of small difference behavior are extracted to conduct the immune multi-agent operation for the acquired image set and to analyze the small difference behavior of the slight deformation of the characters to obtain the feature extraction set.Then,the method of video frame image array detection is used to pre-process the gray level of the pixels in the feature extraction set.By constructing the video frame image array,the gray level pixel value is obtained by tracking and recognition initialization learning,and the better small difference behavior feature set is obtained.Finally,the multi-criteria small difference behavior feature classification method is used to segment the better feature set,and the best small difference behavior feature classification results are obtained by contrasting each feature subset with the measurement criteria.The experimental results show that the proposed method improves the classification accuracy of small difference behavior features with a high efficiency.

Key words: Classification, Feature extraction, Intelligent vision, Preprocessing, Small difference behavior