Title :
A new vehicle detection algorithm using gray-level features
Author :
Qin Gu ; Liangchao Li ; Jianyu Yang
Author_Institution :
Sch. of Electron. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
Abstract :
Vehicle detection has become a necessary part of advanced driver assistance systems (ADAS). In this paper, our main focus is on improving the performance of single camera based vehicle detection system. A new gray-level feature (GLF) obtained from gray-scale map is a description of the difference of potential target area (PTA) and potential background area (PBA). According to the result of density filtering of GLF, the existence of vehicle in extracted block can be verified. Experiments prove that in different scenes, this algorithm utilizing GLF is extremely fast and effective.
Keywords :
cameras; driver information systems; feature extraction; filtering theory; grey systems; object detection; GLF; PBA; PTA; advanced driver assistance systems; density filtering; gray-level feature; gray-scale map; potential background area; potential target area; single camera based vehicle detection system; vehicle detection algorithm; Feature extraction; Filtering; Gray-scale; Image edge detection; Roads; Vehicle detection; Vehicles; density filtering; gray-level feature; vehicle detection;
Conference_Titel :
Computational Problem-solving (ICCP), 2013 International Conference on
Conference_Location :
Jiuzhai
DOI :
10.1109/ICCPS.2013.6893537
