Title :
Automatic road detection for highway surveillance using frequency-domain information
Author :
Qing-Jie Kong ; Zhou, Liang ; Gang Xiong ; Fenghua Zhu
Author_Institution :
State Key Lab. of Manage. & Control for Complex Syst., Inst. of Autom., Beijing, China
Abstract :
Video detection is one of the primary collection means of traffic states in Parallel traffic Management Systems (PtMS). In order to accurately and automatically obtain road areas in highway surveillance videos, this paper presents an automatic detection algorithm based on the frequency-domain information of video images. This algorithm uses the frequency-domain feature that is produced by the vehicles passing through road areas in videos, to realize automatic segmentation and recognition of the road areas. The experiment comparing with the traditional vehicle-tracking-based method, which uses the information in the time-space domain, illustrates the advantages of the proposed algorithm.
Keywords :
feature extraction; frequency-domain analysis; image segmentation; object detection; object recognition; object tracking; traffic engineering computing; video surveillance; PtMS; automatic road detection algorith; frequency-domain feature; frequency-domain information; highway surveillance videos; parallel traffic management systems; road area automatic segmentation; road area recognition; time-space domain; vehicle-tracking-based method; video detection; video images; Fitting; Frequency-domain analysis; Roads; Surveillance; Vehicles; frequency information; road detection; visual surveillance;
Conference_Titel :
Service Operations and Logistics, and Informatics (SOLI), 2013 IEEE International Conference on
Conference_Location :
Dongguan
Print_ISBN :
978-1-4799-0529-4
DOI :
10.1109/SOLI.2013.6611375