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Traffic Sign Board Detection using Canny Edge Detection for Compressed Images

Publication Type : Journal Article

Publisher : Journal of Advanced Research in Dynamical and Control Systems, Institute of Advanced Scientific Research, Inc.,

Source : Journal of Advanced Research in Dynamical and Control Systems, Institute of Advanced Scientific Research, Inc., Volume 10, Issue 12, p.474 - 477 (2018)

Url : https://www.scopus.com/record/display.uri?eid=2-s2.0-85042754489&origin=resultslist

Campus : Mysuru

School : School of Arts and Sciences

Department : Computer Science

Year : 2018

Abstract : Following rules and regulations of traffic sign is one of main aspect of each individual driver. Traffic sign detection and recognition (TSDR) is a system that aims on developing an application of computer vision. This application will automatically recognize various traffic signs. TSDR in general is an application that can be implemented with two main modules: Detector and Classifier. Detector can be implemented using algorithms such as color based. Detected traffic signs may need to be pre-processed and corrected with their appearance before classification stage. This detection can be done through canny edge detection algorithm. Canny Edge Detector is the best and widely used algorithm for edge detection and we used Wavelet Compression technique for compression of images to reduce computational time. In this work we represent broad area on TSDR, and some fundamental techniques to recognition of traffic signs. © 2018, Institute of Advanced Scientific Research, Inc. All rights reserved.

Cite this Research Publication : Akshay S., A., R., and M., Y. Brahma B., “Traffic Sign Board Detection Using Canny Edge Detection for Compressed Images”, Journal of Advanced Research in Dynamical and Control Systems, vol. 10, no. 12, pp. 474 - 477, 2018.

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