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

fYear

2013

fDate

26-28 Oct. 2013

Firstpage

346

Lastpage

349

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Problem-solving (ICCP), 2013 International Conference on

Conference_Location

Jiuzhai

Type

conf

DOI

10.1109/ICCPS.2013.6893537

Filename

6893537