A Region Tracking-Based Vehicle Detection Algorithm in Nighttime Traffic Scenes

Sensors

Jianqiang Wang²  Xiaoyan Sun¹ 

[1] Suzhou INVO Automotive Electronics Co., Ltd., Suzhou 215200, China; E-Mail:;State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China

关键词: advanced driver assistance system;    nighttime vehicle detection;    vehicle taillights;    pairing;    tracking;    time-series analysis model;    adaptive thresholds;   

DOI  :  10.3390/s131216474

来源: mdpi

【 摘 要 】

The preceding vehicles detection technique in nighttime traffic scenes is an important part of the advanced driver assistance system (ADAS). This paper proposes a region tracking-based vehicle detection algorithm via the image processing technique. First, the brightness of the taillights during nighttime is used as the typical feature, and we use the existing global detection algorithm to detect and pair the taillights. When the vehicle is detected, a time series analysis model is introduced to predict vehicle positions and the possible region (PR) of the vehicle in the next frame. Then, the vehicle is only detected in the PR. This could reduce the detection time and avoid the false pairing between the bright spots in the PR and the bright spots out of the PR. Additionally, we present a thresholds updating method to make the thresholds adaptive. Finally, experimental studies are provided to demonstrate the application and substantiate the superiority of the proposed algorithm. The results show that the proposed algorithm can simultaneously reduce both the false negative detection rate and the false positive detection rate.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.