The identification and analysis of seismic gaps is one of the important means of medium-term earthquake prediction. However, it is difficult to achieve the desired effect by the traditional artificial method. Computer vision provides a new way to solve the problem. In this paper, an automatic identification method for seismic gaps based on image processing methods is proposed. The input is the text information of the historical earthquake. It is processed by computer vision methods such as distance transformation, threshold segmentation and watershed algorithm. The effective seismic gap is screened by iterative comparison and feature parameters. The output is the distribution image of the seismic gaps and its corresponding characteristic parameters. In addition, the algorithm of this paper is tested through a certain case. The test suggests that the algorithm of this paper can clearly obtain the seismic gaps with internal connectivity and clear external contour. Compared with the expert calibration, the recall rate of this algorithm is 81.25%, and the accuracy is 92.86%. This method provides a powerful tool for seismic researchers to conduct earthquake prediction business and related research.