An Automatic Road Sign Recognizer for an Intelligent Transport System | Zendy

Md Sipon Miah | Zendy; Insoo Koo | Zendy

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An Automatic Road Sign Recognizer for an Intelligent Transport System

Author(s) -

Md Sipon Miah,

Insoo Koo

Publication year - 2012

Publication title -

journal of information and communication convergence engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.28

H-Index - 6

eISSN - 2234-8883

pISSN - 2234-8255

DOI - 10.6109/jicce.2012.10.4.378

Subject(s) - grayscale , computer science , computer vision , artificial intelligence , sign (mathematics) , canny edge detector , rgb color model , segmentation , process (computing) , intelligent transportation system , enhanced data rates for gsm evolution , image segmentation , image processing , edge detection , pattern recognition (psychology) , image (mathematics) , engineering , mathematical analysis , civil engineering , mathematics , operating system

This paper presents the implementation of an automatic road sign recognizer for an intelligent transport system. In this system, lists of road signs are processed with actions such as line segmentation, single sign segmentation, and storing an artificial sign in the database. The process of taking the video stream and extracting the road sign and storing in the database is called the road sign recognition. This paper presents a study on recognizing traffic sign patterns using a segmentation technique for the efficiency and the speed of the system. The image is converted from one scale to another scale such as RGB to grayscale or grayscale to binary. The images are pre-processed with several image processing techniques, such as threshold techniques, Gaussian filters, Canny edge detection, and the contour technique.

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