¹Department of Computer Science, Jiangyin Polytechnic College, Wuxi, China, 214405
²Jiangsu Engineering R&D Center for Information Fusion Software, Jiangsu Jiangyin, China, 214405

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Abstract—Using wavelet transform to handle auto-mobile image with complex background for license localization, then preprocess license characters on vehicle licenses, and extracting the textural features of license characters in wavelet space, this paper proposed a novel algorithm for vehicle license localization and character recognition which is based on adaptive wavelet neural networks. Firstly, it uses the wavelet transform to preprocess color vehicle image into index image which undergoes wavelet transform to obtain wavelet feature coefficients. Secondly, license position could be located through morphological operation. Thirdly, it extracts the features of localized license characters in wavelet space which is presented to the wavelet neural network as inputs. At last, an adaptive wavelet neural network based on wavelet transform is constructed to recognize license characters. Experimental results demonstrate that the proposed approach could efficiently be used as a vehicle license characters recognition system with high convergence, which is robust for license-size, licensecolor and background complexity.

Index Terms—License localization, character recognition, wavelet transform, feature extraction, wavelet neural network.

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Cite: Pan Yonghui, Fan Rui, "A Wavelet Neural Networks License Recognition Algorithm and Its Application," Journal of Computers vol. 7, no. 7, pp. 1583-1590, 2012.