HDR 기능이 없는 카메라를 이용한 야간 차량 검출

Abstract

Vehicle detection using a camera has been studied actively for a couple of decades in the intelligent vehicle system. Especially, vehicle detection at nighttime has several difficulties because of lack of light. Most of night vehicle detection methods use a high dynamic range (HDR) camera or tune brightness of a camera to capture only light regions. However, the camera we use does not have HDR property and is tuned for lane departure warning system (LDWS). Therefore, the brightness of the camera is fixed to capture lanes on the road even at night and the white balance of the camera is changed to boost white and yellow. In this paper, we propose an effective vehicle detection method using non-HDR camera. The proposed method consists of two main parts; light segmentation and pairing. In the light segmentation part, candidate lights are segmented from an original image using a novel adaptive threshold method. Features for a classifier are extracted from each candidate light. Candidate lights are classified as tail, head, and other lights using a random forest classifier. In the pairing part, only tail lights are handled to detect preceding vehicles. Two tail lights whose Y axis position difference is smaller than threshold are collected as a pairing candidate. Features for pairing classification are extracted from the pairing candidates. Random forest classifier is also used to classify pairing candidates as a vehicle or a non-vehicle. Experiments show that the proposed method effectively detects vehicles in the several different environments.