Research on vehicle detection based on visible light and infrared fusion

Abstract

Combining the gamma transform with Sobel edge detection method, an image enhancement method is designed. The improved Mask R-CNN infrared target detection algorithm based on image enhancement network is proposed. This algorithm is introduced into the Mask R-CNN network based on the decrease of learning rate. Aiming at the limitation of image captured by single sensor, a new target detection algorithm based on decision-level fusion is proposed. This algorithm combines visible light detection with infrared detection. Experiments show that the infrared target detection accuracy is improved by 4.48% after the improved algorithm. The target detection results at decision level are 5.49%~33.80% higher than those of single sensor imaging.