Aiming at the shortcomings of the current pedestrian re-identification technology, this paper presents a pedestrian re-identification method based on Siamese network. First, Dropout algorithm is used to improve the performance of Convolutional Neural Network (CNN), which can reduce the incidence of the fitting problem. By integration of classification and inspection in the CNN, Siamese network is constructed to improve the efficiency and accuracy of image recognition. Finally, Markov distance for metric learning algorithm is used as the evaluation index of image matching similarity. Experiments are conducted on the Market-1501, and the experimental results show that this method is effective in terms of improving the efficiency and accuracy of pedestrian re-identification algorithm.