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Proceedings Paper

Intelligence approach of traffic sign recognition based on color standardization
Author(s): Shuangdong Zhu; Tiantian Jiang; Lanlan Liu
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Paper 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.

Paper Details

Date Published: 24 October 2006
PDF: 5 pages
Proc. SPIE 6357, Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence, 63571C (24 October 2006); doi: 10.1117/12.716971
Show Author Affiliations
Shuangdong Zhu, Ningbo Univ. (China)
Tiantian Jiang, Zhejiang Atmosphere Environmental Protection Group Co., Ltd. (China)
Lanlan Liu, Ningbo Univ. (China)


Published in SPIE Proceedings Vol. 6357:
Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence
Jiancheng Fang; Zhongyu Wang, Editor(s)

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