Night-Time Road Boundary Detection with Infrared Channel Features Classifier

Author

Jing Dai ; Yuqiang Fang ; Tao Wu ; Dawei Zhao ; Hangen He

Author_Institution

Coll. of Mechatron. & Autom., Nat. Univ. of Defense Technol., Changsha, China

fYear

2014

fDate

11-13 Sept. 2014

Firstpage

751

Lastpage

755

Abstract

Road boundary detection is very important to Intelligent Vehicle (IV) System. Recently, road boundary detection during night-time driving condition attracts more and more attentions. In this paper, we propose a novel and fast method for night-time road boundary detection on infrared images. Firstly, a set of novel Infrared Channel Features (ICF) are proposed for describing infrared image patterns. Furthermore, we proposed an Infrared Edge classifier to generate a task-driven probability edge map. Finally, road boundary extraction is performed on the edge map by two steps: searching available road boundaries and second order polynomial approximation. Experiment show that the proposed method performs well with effectiveness and efficiency.

Keywords

feature extraction; image classification; intelligent transportation systems; night vision; object detection; polynomial approximation; probability; road traffic; road vehicles; ICF; IV system; infrared channel features classifier; infrared edge classifier; infrared image patterns; intelligent vehicle system; night-time driving condition; night-time road boundary detection; road boundary extraction; second order polynomial approximation; task-driven probability edge map; Decision trees; Feature extraction; Image edge detection; Polynomials; Roads; Training; Vegetation; curve fitting; infrared channel features; random forests; road boundary detection;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Information Technology (CIT), 2014 IEEE International Conference on

Conference_Location

Xi´an

Type

conf

DOI

10.1109/CIT.2014.35

Filename

6984745