Combining Region-of-Interest Extraction and Image Enhancement for Nighttime Vehicle Detection

Abstract

In nighttime images, vehicle detection is a challenging task because of low contrast and luminosity. In this article, the authors combine a novel region-of-interest (ROI) extraction approach that fuses vehicle light detection and object proposals together with a nighttime image enhancement approach based on improved multiscale retinex to extract accurate ROIs and enhance images for accurate nighttime vehicle detection. Experimental results demonstrate that the proposed nighttime image enhancement method, score-level multifeature fusion, and the ROI extraction method are all effective for nighttime vehicle detection. But the proposed vehicle detection method demonstrates 93.34 percent detection rate and outperforms other models, detecting blurred and partly occluded vehicles, as well as vehicles in a variety of sizes, numbers, locations, and backgrounds.