To solve the problems of low contrast between a local target and its background and segmentation of an infrared handprint image with blurred edge, an edge blurred infrared target extraction algorithm based on geometric growth with structural morphology is proposed. Firstly, the maximum entropy method and threshold extension are used to segment the image roughly. Secondly, the feature points of the regional blocks in the roughly segmented target area are extracted to construct the structural morphology of the hand. Finally, by using the regional block feature point to find the seed point and using the distance relationship between the seed points and the corresponding feature points as the growth decision condition for geometric growth, the target area is obtained from the image. The method is compared with the conventional extraction algorithm experimentally. The results show that the proposed method can extract the complete target more effectively for the blurred infrared images with blurred edge.