Text verification code recognition method and device based on cross-domain element learning and storage medium

A recognition method and meta-learning technology, applied in the fields of computer vision and image processing, can solve problems such as poor cross-domain effects of meta-learning algorithms and unbalanced data
CN113139536AActive Publication Date: 2021-07-20HARBIN INST OF TECH AT WEIHAI
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Patent Information

Authority / Receiving Office
CN Β· China
Current Assignee / Owner
HARBIN INST OF TECH AT WEIHAI
Publication Date
2021-07-20

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Abstract

The invention relates to a text verification code recognition method and device based on cross-domain element learning and a storage medium. The method comprises the steps of (1) an element training stage: firstly, generating a large number of verification code pictures with different security features as basic training data; then, carrying out character segmentation, and inputting segmented characters into the ResNet neural network model for feature extraction; and finally, obtaining a loss value of the pre-estimated category; and (2) a fine tuning stage: marking a small number of verification code pictures of different types from the basic training data in the meta-training stage, and performing fine tuning on the ResNet neural network model to obtain a final recognition result. The method has the characteristics of extremely small marked sample size, high model training speed, strong generalization ability and high recognition accuracy, solves the problems that an existing verification code recognition method needs a large amount of labeled data and the model migration difficulty is large, can meet the industrial requirements, and has wide application prospects.
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Description

technical field

[0001] The invention relates to a text verification code recognition method, device and storage medium based on cross-domain meta-learning, and belongs to the technical fields of computer vision and image processing. Background technique

[0002] Captcha, also known as the anti-Turing test, is an automated mechanism for distinguishing between humans and computers. At present, verification codes are widely used by major commercial websites to prevent malicious cracking of passwords, swiping tickets, flooding and hacker attacks, etc., so as to ensure the information security of the websites. Although many new types of verification codes have been proposed in recent years, text verification codes are still one of the most widely used types of verification codes. Therefore, research on text verification codes will help to design a more secure and effective human-machine discrimination mechanism, thereby Promote the development of the field of information securit...

Claims

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