Target Local Matching Recognition Algorithm based on Improved Harris Key Point Detection Operator

Abstract

In the process of attacking fighters, helicopters and other targets, infrared imaging guided air-to-air missiles once they find themselves intercepted, they will release interference to induce the missile to deviate from the trajectory, which brings great difficulties to the missile to successfully destroy the target. When infrared interference occludes aircraft targets, a target local matching recognition algorithm based on the improved Harris key point detection operator is proposed. The algorithm first uses the Gaussian smoothing window to count the gradients in the x direction and y direction of each pixel, forms an autocorrelation feature matrix and calculates its feature values. Because smaller eigenvalues can be used to characterize the prominence of the curve, the minimum eigenvalue is used as the corner response function value, and the point when greater than the given threshold is marked as the key point of the aircraft target. In the process of interference occlusion of aircraft targets, the local matching recognition of targets is achieved by calculating the Euclidean distance of the feature descriptors between key points. Experimental results show that the proposed improved algorithm can achieve local matching recognition of infrared aircraft targets when infrared interference occludes aircraft targets.