[1]GU Mingqin,CAI Zixing,HE Fenfen.Traffic sign recognition based on shape signature and Gabor wavelets[J].CAAI Transactions on Intelligent Systems,2011,6(6):526-530.
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CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
6
Number of periods:
2011 6
Page number:
526-530
Column:
学术论文—智能系统
Public date:
2011-12-25
- Title:
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Traffic sign recognition based on shape signature and Gabor wavelets
- Author(s):
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GU Mingqin; CAI Zixing; HE Fenfen
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School of Information Science and Engineering, Central South University, Changsha 410083, China
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- Keywords:
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traffic sign recognition; signature; Gabor wavelet; support vector machine
- CLC:
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TP391
- DOI:
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- Abstract:
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Traffic sign recognition provides valuable information on road conditions for intelligent vehicles. The traffic sign recognition process was outlined as follows: 1) The main colors of traffic signs were enhanced by transforming the RGB pixel values of the image and then segmented by a threshold. Noise points of the binary image were filtered by morphological image processing. 2) The signature of the region of interest (RoI) was extracted as a shape feature, and the shape of the RoI was primarily classified by Euclidean distance. 3) The gray images of traffic signs was transformed into various orientations and scale wavelet images by the Gabor wavelet, and the main features were extracted by a 2dimensional independent component analysis (2DICA) algorithm while the linear support vector machine was applied to judge the type of traffic signs. Experimental results show that the proposed algorithm may stably and effectively detect and identify the roadside traffic signs.