DocumentCode
1791397
Title
Vehicle video detection based on pulsed coupled neural network
Author
Yongsheng Xu ; Shuwen Wang ; Xiangqun Li
Author_Institution
Electr. Eng. Dept., Northwest Univ. for Nat., Lanzhou, China
fYear
2014
fDate
14-16 Oct. 2014
Firstpage
731
Lastpage
735
Abstract
Vehicle Video detection is an important part of intelligent transportation system for its characteristics of effectiveness and accuracy, and it provides important data for the security of urban traffic operation. However, in order to improve the reliability of vehicle detection in the traffic video detection system, in this paper, a pulse-coupled neural network (PCNN) is used for the image segmentation to obtain the target vehicle, automatic propagation characteristic of the pulse-coupled neural network is utilized to perform the morphological restoration of the vehicles, which is resulted from the consideration of the impact from the external environment and the interference in the transmission of data as well as the real-time requirements of video detection. The experimental results show that a good effect is obtained in video detection by using the proposed method.
Keywords
automobiles; image restoration; image segmentation; intelligent transportation systems; interference (signal); neural nets; object detection; road traffic; video signal processing; PCNN; automatic propagation characteristic; data transmission; external environment; image segmentation; intelligent transportation system; interference; morphological restoration; pulsed coupled neural network; real-time requirements; target vehicle; traffic video detection system; urban traffic operation security; vehicle detection reliability improvement; vehicle video detection; Adaptation models; Cameras; Educational institutions; Image segmentation; Neural networks; Streaming media; Vehicles; image processing; pulse coupled neural network; vehicle target; video detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Image and Signal Processing (CISP), 2014 7th International Congress on
Conference_Location
Dalian
Type
conf
DOI
10.1109/CISP.2014.7003874
Filename
7003874
Link To Document