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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: © 2013 |Pages: 13
ISBN13: 9781466629288|ISBN10: 1466629282|EISBN13: 9781466629295
DOI: 10.4018/978-1-4666-2928-8.ch005
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MLA

Li, Yue, and Wei Wang. "Traffic-Signs Recognition System Based on FCM and Content-Based Image Retrieval." Modern Library Technologies for Data Storage, Retrieval, and Use, edited by Chia-Hung Wei, IGI Global, 2013, pp. 60-72. https://doi.org/10.4018/978-1-4666-2928-8.ch005

APA

Li, Y. & Wang, W. (2013). Traffic-Signs Recognition System Based on FCM and Content-Based Image Retrieval. In C. Wei (Ed.), Modern Library Technologies for Data Storage, Retrieval, and Use (pp. 60-72). IGI Global. https://doi.org/10.4018/978-1-4666-2928-8.ch005

Chicago

Li, Yue, and Wei Wang. "Traffic-Signs Recognition System Based on FCM and Content-Based Image Retrieval." In Modern Library Technologies for Data Storage, Retrieval, and Use, edited by Chia-Hung Wei, 60-72. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-2928-8.ch005

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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.

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