Affiliations: School of Mathematics and Information Engineering, Puyang Vocational and Technical College, Puyang, China
Correspondence:
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Corresponding author. Yuan Sun, School of Mathematics and Information Engineering, Puyang Vocational and Technical College, Puyang, 457001, China. E-mail: sunyuan_y@sina.com.
Abstract: When using the current authentication code recognition system to identify the character authentication code, there are the problems of low integrity and low recognition accuracy. In this regard, a design method of artificial intelligence recognition system for cracking character type authentication code is proposed in this paper. The denoising algorithm based on the connected domain is used to remove the noise in the character type authentication code, and the character authentication code after the denoising is normalized. The feature extraction module is used to extract color moments, color correlation diagrams and LBP texture features of character authentication codes, and complete the feature extraction of character authentication codes. The similarity matching module is used to match the characters of the character authentication code. In the recognition module, the character authentication code is classified by the classification algorithm based on multi-feature SVM, and the recognition of the character authentication code is completed. The experimental results show that the proposed method has high information integrity and high recognition accuracy.
Keywords: Character authentication code, artificial intelligence, recognition system, feature extraction
