Abstract: The edge contour features of infrared face images are of great value for applications related to infrared face detection and recognition. Aiming at the problem of false edges in the edge contour extraction of infrared face images, an edge contour extraction of infrared face image based on improved Canny algorithm was proposed. Firstly, by introducing dynamic threshold constraint factor to the guided filtering algorithm to replace the Gaussian filtering in the original algorithm, the disadvantages of uneven filtering processing and the loss of weak edge features in the infrared face image were solved. Then, the non-maximum suppression was improved, and four gradient directions were added on the basis of the original gradient direction, which made the interpolation of non-maximum suppression more precise than the original algorithm. Finally, the OTSU algorithm was improved by constructing a gray-gradient mapping function to determine the optimal threshold value, which solved the limitation of the original algorithm to determine the threshold value by human experience. The experimental results show that, compared with the original Canny algorithm filtering processing, the performance of signal-to-noise ratio of the filtered image from edge contour extraction of infrared face images based on improved Canny algorithm is improved by 34.40%, and the performance of structural similarity is improved by 21.66%. Finally, the quality coefficient value of the experiment of infrared face edge contour extraction is higher than that of other methods in the comparison experiment, which proves that the improved algorithm has superiority for the edge contour extraction of infrared face image.