TECHNIQUES FOR TRAFFIC SIGN CLASSIFICATION USING MACHINE LEARNING-A SURVEY
Keywords:
Computer Vision System, Traffic Sign Detection, Traffic Sign Classification, Neural Network, Image Classification Technique, Support Vector Machine (SVM), Kernel-Based Neural Network (K-NN)Abstract
The Road Sign Recognition is a field of applied computer vision research concerned with the automatic detection and classification of traffic signs in traffic scene images. The aim of this research paper is to study the various classification techniques that can be used to construct a system that recognizes road signs in images. The primary objective is to develop an algorithm which will identify various types of road signs from static digital images in a reasonable time frame. In this research paper, we will study the various learning systems that are based on prior knowledge for classification. A road sign recognition system faces a classical problem of pattern recognition, classifying between different road signs. On top of that, the location of the road sign in the picture is unknown. Once these obstacles are overcome, such system could be integrated in a Smart Driver system. A variety of MATLAB Image processing toolbox commands can be used to determine if a road sign is present in the image. Neural network or other classification techniques can be applied in order to classify the road signs.
References
Shawkat Ali, M. Ameer Ali, G.M. Shafiullah, Colin Cole, “Smart Driving: A New Approach to Meeting Driver Needs”, International Conference on Industrial Engineering and Operations Management”, 2010.
Tang Jin, Liang Xiong, Xie Bin, Chen Fangyan, Liu Bo, “A Method of Traffic Sign Detection, Tracking and Recognition”, IEEE International Conference (ICCSE), 2010.
Jesmin F. Khan, Sharif M., A. Bhuiyan and Reza R. Adhami, “Image Segmentation and Shape Analysis for Road Sign Detection”, IEEE Transactions on Intelligent Transportation Systems, Vol. 12, No. 1, March 2011.
Auranuch Lorsakull and Jackrit Suthakorn, “Traffic Sign Recognition Using Neural Network on Open CV: Towards Intelligent Vehicle/Driver Assistance System”, 4th International Conference on Ubiquitous Robots and Ambient Intelligence, 2007.
Yong-Jian Zheng, Werner Ritter, Reinhard Jatnessen, “An Adaptive System for Traffic Sign Recognition”, Intelligent Vehicles ‘94 Symposium, 24-26 October, August 2002.
Y. Aoyagi, T. Asakura, “A Study on Traffic Sign Recognition in scene image using genetic algorithms and neural networks”, 22nd International Conference on Industrial Electronics, Control and Instrumentation, IEEE August 1996.
Chiung-Yao Fang, Sei Wang Chen and Chiou-ShannFuh, Member, “Road Sign Detection and Tracking”, IEEE Transactions on Vehicular Technology, Vol. 52, No. 5, September 2003.
Robert E. Uhrig, ”Introduction to Artificial Neural Networks”, Proceedings of the 1995 IEEE IECON 21st International Conference, 1995.
M. Seetha, Muralikrishna, B.L. Deekshatulu, B.L. Malleswari, Nagaratna, P. Hegde, “Artificial Neural Networks and Other Methods of Image Classification”, Journal of Theoretical and Applied Information Technology, 2008.
O.R. Vincent, O. Folorunso, “A Descriptive Algorithm for Sobel Image Edge Detection”, Proceedings of Informing Science & IT, Education Conference (InSITE), 2009.
Yok-Yen Nguwi and Abbas Z. Kouzani, “Automatic Road Sign Recognition Using Neural Networks”, 2006 International Joint Conference on Neural Networks, July 2006.
Mrs. C. Maithili and Dr. V. Kavitha, “Efficient Technique for Color Image Noise Reduction”, The Research Bulletin ACM, Volume 2(3), 2011.
Kiran C., G. Lekhesh, V. Prabhu, Abdurrahiman V. and Rajeev K. “Traffic Sign Detection and Pattern Recognition Using Support Vector Machine”, Seventh International Conference on Advances in Pattern Recognition, 2009.
P. Gil-Jim’enez, S. Lafuente-Arroyo, S. Maldonado-Basc’on and H. G’omezMoreno, “Shape Classification Algorithm Using Support Vector Machines for Traffic Sign Recognition”, LNCS 3512, pp. 873-880, 2005.
Prof. Abhinav v. Deshpande, System Designing and Modelling Using FPGA, International journal of Electronics and communication Engineering & Technology, Volume 5, Issue 11, 2015, pp. 47-52.
Prof. Abhinav V. Deshpande. Implementation of A Robust and Safe Cyber Security System by Preventing The Intrusion of Outsiders by Formulation of A Novel and Efficient Cyber Law Enforcement Policy. International Journal of Information Technology, 6(2), 2015, pp. 01-10.
Prof. Abhinav v. Deshpande, Application of Open Source Software In Science and Engineering, International journal of Computer Engineering & Technology, Volume 6, Issue 8, 2015, pp. 1-10.
Prof. Abhinav V. Deshpande and Prof. Ram Meghe, Nanomaterials and Nanotechnology: Future Emerging Technology, International Journal of Advanced Research in Engineering & Technology, Volume 5, Issue 12, 2014, pp. 41 - 47.
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Copyright (c) 2015 Abhinav V. Deshpande (Author)
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