A method based on deep belief networks（ DBN） is proposed to identify social security card number.Firstly

collect the social security card image and segment the card number area by the module segmentation.Secondly

split a single character of the card number using the regional growth method. Thirdly

the character image is grayed

binarized and normalized to the size of 32 × 32

which is taking as the input data of DBN.Training the 3 layers restricted Boltzmann machine（ RBM） to obtain more abstract features. The top layer of the model combined the softmax regression classifier to classify the extracted features. Experimental results show that the accuracy rate is up to 98. 3%. Compared with the BP neural network and support vector machine（ SVM）model

the DBN not only learned the high-level characteristics but also reduced the dimension of features and improved the accuracy of classifier classification. Finally

it effectively improved the recognition rate of social security card number.