Welcome to the InfoSci Platform
Reference Hub1
Traffic-Signs Recognition System Based on FCM and Content-Based Image Retrieval

Traffic-Signs Recognition System Based on FCM and Content-Based Image Retrieval

Yue Li, Wei Wang
Copyright: © 2011 |Volume: 2 |Issue: 4 |Pages: 12
ISSN: 1947-9077|EISSN: 1947-9085|EISBN13: 9781613506523|DOI: 10.4018/jdls.2011100101
Cite Article Cite Article

MLA

Li, Yue, and Wei Wang. "Traffic-Signs Recognition System Based on FCM and Content-Based Image Retrieval." IJDLS vol.2, no.4 2011: pp.1-12. http://doi.org/10.4018/jdls.2011100101

APA

Li, Y. & Wang, W. (2011). Traffic-Signs Recognition System Based on FCM and Content-Based Image Retrieval. International Journal of Digital Library Systems (IJDLS), 2(4), 1-12. http://doi.org/10.4018/jdls.2011100101

Chicago

Li, Yue, and Wei Wang. "Traffic-Signs Recognition System Based on FCM and Content-Based Image Retrieval," International Journal of Digital Library Systems (IJDLS) 2, no.4: 1-12. http://doi.org/10.4018/jdls.2011100101

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

Artificial intelligent (AI) driving is an emerging technology, freeing the driver from driving. Some techniques for automatically driving have been developed; however, most can only recognize the traffic signs in particular groups, such as triangle signs for warning, circle signs for prohibition, and so forth, but cannot tell the exact meaning of every sign. In this paper, a framework for a traffic system recognition system is proposed. This system consists of two phases. The segmentation method, fuzzy c-means (FCM), is used to detect the traffic sign, whereas the Content-Based Image Retrieval (CBIR) method is used to match traffic signs to those in a database to find the exact meaning of every detected sign.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.