Open AccessA Survey on Traffic Sign Detection Techniques Using Text Mining
Author(s) -
S. Murugan,
R. Karthika
Publication year - 2019
Publication title -
asian journal of computer science and technology
Language(s) - English
Resource type - Journals
eISSN - 2583-7907
pISSN - 2249-0701
DOI - 10.51983/ajcst-2019.8.s1.1975
Subject(s) - computer science , field (mathematics) , sign (mathematics) , traffic sign , focus (optics) , image (mathematics) , traffic sign recognition , image processing , digital image , digital image processing , artificial intelligence , data mining , computer vision , mathematical analysis , physics , mathematics , pure mathematics , optics
Traffic Sign Detection and Recognition (TSDR) technique is a critical step for ensuring vehicle safety. This paper provides a comprehensive survey on traffic sign detection and recognition system based on image and video data. The main focus is to present the current trends and challenges in the field of developing an efficient TSDR system. The ultimate aim of this survey is to analyze the various techniques for detecting traffic signs in real time applications. Image processing is a prominent research area, where multiple technologies are associated to convert an image into digital form and perform some functions on it, in order to get an enhanced image or to extract some useful information from it.