NDLI: Intelligence approach of traffic sign recognition based on color standardization

Content Provider	IEEE Xplore Digital Library
Author	Zhu Shuangdong Jiang Tian-tian
Copyright Year	2005
Description	Author affiliation: Ningbo Univ., China (Zhu Shuangdong; Jiang Tian-tian)
Abstract	Nowadays, for the BP neural network based outdoor traffic sign recognition problems, the recognition rate is generally between 60% and 70%. Based on the results analysis, one may come to a conclusion that the key factors affecting recognition rate are the color distortion caused by the color complexity. This paper present a new solution according to the idea of simplifying the complex problem, using color information and intelligent approach. The first step is to break the complex color information down to 5 kinds of standard color, and then employ BP neural network to classification. In this article BP network is used for color standardization, selecting 23 normalization signs as training set and 531 real signs as testing set for BP network. By doing so 100% average recognition rate is achieved. At the same time, it shows the better robustness of the proposed approach for the color distortion of traffic sign in terms of either the structure parameter or the training parameter of network.
Starting Page	296
Ending Page	300
File Size	1715478
Page Count	5
File Format	PDF
ISBN	0780394356
DOI	10.1109/ICVES.2005.1563660
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-10-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Intelligent networks Image color analysis Roads Neural networks Nonlinear distortion Humans Standardization Telecommunication traffic Optical distortion Intelligent transportation systems
Content Type	Text
Resource Type	Article

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