DocumentCode :
175624
Title :
Rapid vehicle edge detection based on cellular neural network
Author :
Deshui Hao ; Luping Ji ; Long Zhou
Author_Institution :
Sch. of Comput. Sci. & Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
fYear :
2014
fDate :
19-21 Aug. 2014
Firstpage :
118
Lastpage :
122
Abstract :
This paper presents a rapid edge detection method for vehicle using the two-dimensional cellular neural network (CNN). In the method, two adaptive templates for edge detection are experimentally designed, and background noise elimination is also concerned. Finally, the performance of the proposed CNN detector is evaluated on different vehicle images, and it is also compared with some other edge detectors. Simulation experiment results shows that the CNN method could achieve good performance in vehicle edge detection.
Keywords :
cellular neural nets; edge detection; image denoising; road vehicles; traffic engineering computing; CNN; adaptive templates; background noise elimination; rapid vehicle edge detection method; two-dimensional cellular neural network; vehicle images; Cellular neural networks; Detectors; Digital images; Image edge detection; Noise; Particle swarm optimization; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2014 10th International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4799-5150-5
Type :
conf
DOI :
10.1109/ICNC.2014.6975820
Filename :
6975820
Link To Document :
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