Realization of Real-time Detection Algorithms for Key Parts of Unmanned Aerial Vehicle Based on Support Vector Machine

Fixed-point attack on the key parts of small aerial vehicles is an important means of UAV (Unmanned Aerial Vehicle) countermeasure. Because of the fast speed and flexible attitude of fixed-wing aircraft, the detection accuracy of key points of fixed-wing aircraft in infrared images is low and the speed is slow. This paper presents an improved detection and tracking algorithm based on SVM. Firstly, the detection module extracts the fixed-wing aircraft area by image segmentation, then extracts the characteristics of the fixed-wing aircraft, then uses SVM to judge the flight direction of the fixed-wing aircraft, and then locates the key points according to the direction. The experimental results show that the proposed detection algorithm can process 30 frames per second on the platform of DSP (TSM320C6678), and still achieve a high detection rate (>93%) with very high practical value.