Target Recognition of Laser Imaging Fuze Based on Corner Features

Aiming at the problem that the laser imaging fuze needs to process a large amount of data and the algorithm is complex, so it is difficult to eliminate the cloud interference quickly and accurately, a target recognition method based on the combination of improved Harris corner detection algorithm and rectangularity is proposed. Firstly, B-spline function is used to replace the Gaussian window function in the original corner detection algorithm for smoothing filtering; Secondly, the gray value of the central pixel is compared with its 8 neighborhood, and the diagonal points are pre screened. After eliminating the pseudo corners, the corners are determined by using the improved corner response function and non maximum suppression; Finally, count the number of corners and calculate the rectangularity of the corner area, take the number of corners and rectangularity as the feature vector, and select the linear analysis method with the highest accuracy and the fastest reasoning speed for classification and recognition. The experimental results show that the accuracy of the target recognition method can reach 95.02%. The target recognition method proposed in this paper can quickly and accurately distinguish fighter from cloud.