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Neural Network Based Smart Vision System for Driver Assistance in Extracting Traffic Signposts by Meeta Kumar; Jayshree Ghorpade; V. Y. Kulkarni; Rajni Bedi is a scholarly article available to read on EtoBox.

What is Neural Network Based Smart Vision System for Driver Assistance in Extracting Traffic Signposts about?

A vision-based driver assistance system using image processing technology consists of three main modules: road detection, traffic sign detection/identification, obstacle detection. Traffic Sign Recognition is an upcoming research field under applied Computer Vision and Machine Learning which deals with the automatic detection and classification of traffic signs in traffic scene images. In the current paper, we discuss the methodology used to detect the road sign from a traffic sign scene image and present a technique that can be used to construct a system that recognizes road signs in images. Such a system will ensure that each driver is aware of the rules & hazards on the road & will thus help in improving road safety. Also, the location of the road sign in the traffic sign image is unknown. Once these obstacles are overcome, such a system could be integrated in a Driver Assistance System. The primary objective is to develop an algorithm, which will identify various types of road signs from streaming video of real time road scenes in a reasonable time frame. The algorithm has two main parts: the first one, detection which uses the color and shape information to detect a road sign

Author

Meeta Kumar; Jayshree Ghorpade; V. Y. Kulkarni; Rajni Bedi

Publisher

ACM

Published

2012

Language

EN