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A Survey on Road Traffic Sign Recognition System using Convolution Neural Network


Author : Yuga Hatolkar, Poorva Agarwal and Seema Patil

Pages : 104-108, DOI: https://doi.org/10.14741/ijcet/v.8.1.21
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Abstract

Road Traffic accidents is one of the major reason for deaths taking place in India. These accidents not only result into serious injuries but may also lead to deaths. Image recognition technology is one of the widely used techniques used in various fields in research like agriculture, medicine, automobile etc. At present, majority of the Image recognition techniques use artificial feature extraction technique which is not only time consuming but also is very complex. Hence, various researchers are basically working in order to improve the algorithms, and make them more and more efficient and robust. Initially, traditional principle of convolution neural network was introduced briefly. Its numerous applications in the domain of Image Processing were presented. Finally, the challenges faced by Convolution Neural Network in terms of time complexity and accuracy were analyzed, and then our recent work was introduced in order to overcome the efficiency related issues.

Keywords: Image Processing, Canny Edge detection algorithm, Frame extraction, Frame normalization, Gray scale image, Convolution Neural Network, Fuzzy Classification

Article published in International Journal of Current Engineering and Technology, Vol.8, No.1 (Jan/Feb 2018)

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