Title :
Coherence vector of Oriented Gradients for traffic sign recognition using Neural Networks
Author :
Rajesh, R. ; Rajeev, K. ; Suchithra, K. ; Lekhesh, V.P. ; Gopakumar, V. ; Ragesh, N.K.
Author_Institution :
Network Syst. & Technol., Thiruvananthapuram, India
fDate :
July 31 2011-Aug. 5 2011
Abstract :
This paper makes use of Coherence Vector of Oriented Gradients (CVOG) for traffic sign recognition. Experiments are conducted on German Traffic Sign benchmark dataset. The results on traffic sign recognition using CVOG features with neural network classifier is promising. The results based on the combination of other features gave better recognition rates.
Keywords :
image recognition; neural nets; pattern classification; traffic engineering computing; CVOG features; coherence vector of oriented gradients; neural networks; traffic sign recognition; Biological neural networks; Coherence; Feature extraction; Image color analysis; Image edge detection; Pattern recognition; Roads; CCV; Coherence Vector of Oriented Gradients; Neural Network Classifier; Traffic Sign Recognition;
Conference_Titel :
Neural Networks (IJCNN), The 2011 International Joint Conference on
Conference_Location :
San Jose, CA
Print_ISBN :
978-1-4244-9635-8
DOI :
10.1109/IJCNN.2011.6033318
