A method for license plate recognition in vehicle based on Gabor feature and synergetic neural network

doi:10.3969/j.issn.1000-1565.2016.02.017

Abstract

Abstract: Vehicle license recognition has been studied under the climate and light conditions.The feature extraction of Gabor and synergetic neural network has been used to enhance the recognition rate.First,the characters of vehicle license go through the binarization and segmenting to extract the characteristic parameters of the license characters by Gabor filter.Then,the synergetic mode is used to train the characteristic parameters and work out the training sample.Finally,the synergetic neural network is utilized to recognize the license character.Under a variety of environments and light conditions, this approach achieves a much higher rate of recognition rate compared with the traditional mode suggesting that this new method is very effective in the field of vehicle license recognition.

Key words: Feature extraction, Neural network, license plate recognition, character segmentation, Gabor filter

CLC Number:

TP391

SHI Guimin,YU Wensen,XIAO Zhongjie. A method for license plate recognition in vehicle based on Gabor feature and synergetic neural network[J]. Journal of Hebei University (Natural Science Edition), 2016, 36(2): 210-217.

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