De-hazing CCTV Images using Dark Channel Prior for Improved Vehicle Detection

Abstract

The recent advancements in artificial intelligence have led to significant improvements in object detection. Researchers have focused on enhancing the performance of object detection in challenging environments, as this has the potential to enhance the practical applications. Deep learning has been successful in image classification and object detection and has a wide range of applications including vehicle detection. However, vehicle detection models trained on high-quality images often struggle to perform well under adverse weather conditions, such as fog and rain. In this paper, we propose an improved vehicle detection method using a faster R-CNN with a dark channel prior (DCP). The proposed method first preprocesses the image using DCP and then performs vehicle detection on the preprocessed image using faster R-CNN. This method has been shown to improve the effectiveness of vehicle detection. © 2023 ACM.