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To study the characteristics of license plate characters recognition,this paper proposes a method for fea- ture extraction of license plate characters based on two-dimensional wavelet packet.We decompose license plate character images with two dimensional-wavelet packet and search for the optimal wavelet packet basis.This paper pre- sents a criterion of searching for the optimal wavelet packet basis,and a practical algorithm.The obtained optimal wavelet packet basis is used as the feature of license plate character,and a BP neural network is used to classify the character.The test- ing results show that the proposed method achieved higher recognition rate than the traditional methods.
To study the characteristics of license plate characters recognition, this paper proposes a method for fea- ture extraction of license plate characters based on two-dimensional wavelet packet. We decompose license plate character images with two dimensional-wavelet packet and search for the optimal wavelet packet basis. This paper pre- sents a criterion of searching for the optimal wavelet packet basis, and a practical algorithm. The obtained optimal wavelet packet basis is used as the feature of license plate character, and a BP neural network is used to classify the character.The test- ing results show that the proposed method achieved higher recognition rate than the traditional methods.