Verification code identification method based on window sliding and convolutional neural network

A convolutional neural network and recognition method technology, applied in biological neural network models, character and pattern recognition, neural architecture, etc., can solve the problems of low labor cost and low time complexity, and achieve low labor cost and good recognition effect. , the effect of reducing the sliding range of the window

Active Publication Date: 2018-04-27
广州探迹科技有限公司
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Problems solved by technology

[0006] The purpose of the present invention is to overcome the shortcomings and deficiencies of the prior art, and provide a verification code recognition method based on window sliding and convolutional neural network, which can e

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  • Verification code identification method based on window sliding and convolutional neural network

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[0035] Example

[0036] see figure 1 , the steps of a verification code identification method based on window sliding and convolutional neural network of the present embodiment are:

[0037] S1: Collect the verification code data samples that need to be cracked, and perform binarization and preprocessing on each sample image.

[0038] Binarization can use the traditional ostu binarization algorithm. The otsu algorithm is an efficient algorithm for image binarization proposed by Japanese scholar Otsu in 1979. First the algorithm will automatically select an appropriate threshold; then all pixels on the image will be binarized based on the threshold. The process of automatically selecting an appropriate threshold is to enumerate all possible thresholds, and calculate the inter-class variance for each threshold in the binarized black and white image. The inter-class variance g=w0*w1*(u0-u1)*(u0-u1), the average gray level of the category with a value of 0 is u0, the proportion...

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Abstract

The invention provides a verification code identification method based on window sliding and the convolutional neural network for traditional English letter+digit+Chinese character verification code pictures. According to the method, firstly, a small quantity of verification code pictures are acquired, after noise reduction, to-be-identified character sets of the verification codes are extracted,each character set is turned and distorted, and background noise is added to each character set; secondly, the convolutional neural network is then utilized for the character sets, and each characterset is trained to acquire a single character classifier; and lastly, after the to-be-identified verification code pictures are pre-processed, connected domain segmentation is carried out, for each connected domain, window sliding is carried out, the trained single character classifiers are utilized for classification, and the final identification result is acquired. The method is advantaged in that a problem of segmentation difficulty caused by overlapping of the verification codes and excessive random character jitter can be effectively solved, through the method of employing the small quantity of verification code pictures, extracting the character sets from the pictures and autonomously generating the correlation training sets, data acquisition and data marking cost is greatly reduced.

Description

technical field [0001] The invention relates to the research fields of computer vision and image processing, in particular to a verification code recognition method based on window sliding and convolutional neural network. Background technique [0002] Verification code, usually refers to a series of randomly generated numbers or symbols to generate a picture, add some interference to the picture, such as randomly draw a few straight lines, draw some points (to prevent OCR), and let the user identify the verification code information with naked eyes , enter the form to submit website verification, and a function can only be used after the verification is successful. Generally, the place where the user ID is registered and the major forums must enter the verification code. [0003] The reason why the verification code is set is mainly to automatically distinguish whether the current user is a computer or a human, so as to prevent malicious password cracking, swiping tickets,...

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Application Information

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IPC IPC(8): G06K9/34G06K9/40G06N3/04
CPCG06V30/153G06V10/30G06N3/045
Inventor 陈开冉缪伟宏
Owner 广州探迹科技有限公司
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