Vehicle license plate character recognition based on lifting wavelet transform and invariant moment

Abstract

Abstract: The key of the license plate recognition system is the character recognition and the core of the character recognition is to extract character features. The wavelet transformation can obtain the details and the structural features for characters and the invariant moment can describe it well. So we combine the two to extract the features of the characters. Meanwhile the directional high frequency sub-images which are decomposed by the tensor product wavelet can be extracted the character strokes feature. Finally we get the alliance feature vector that reflect the structural and statistical features of characters using the second generation lifting wavelet algorithm to further reduce the computational complexity. The experiments results show that the proposed method can achieve 98% recognition rate and can meet the requirements of practical application.

Key words: pattern recognition; lifting wavelet transform; invariant moment; statistical features; structural features; character strokes

GAO Qiang, LIU Bin. Vehicle license plate character recognition based on lifting wavelet transform and invariant moment[J]. J4, 2016, 33(6): 662-670.

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