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CNN for breaking text-based CAPTCHA with noise
Author(s): Kaixuan Liu; Rong Zhang; Ke Qing
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Paper Abstract

A CAPTCHA (“Completely Automated Public Turing test to tell Computers and Human Apart”) system is a program that most humans can pass but current computer programs could hardly pass. As the most common type of CAPTCHAs , text-based CAPTCHA has been widely used in different websites to defense network bots. In order to breaking textbased CAPTCHA, in this paper, two trained CNN models are connected for the segmentation and classification of CAPTCHA images. Then base on these two models, we apply sliding window segmentation and voting classification methods realize an end-to-end CAPTCHA breaking system with high success rate. The experiment results show that our method is robust and effective in breaking text-based CAPTCHA with noise.

Paper Details

Date Published: 21 July 2017
PDF: 5 pages
Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 104202V (21 July 2017); doi: 10.1117/12.2281743
Show Author Affiliations
Kaixuan Liu, Univ. of Science and Technology of China (China)
Rong Zhang, Univ. of Science and Technology of China (China)
Ke Qing, Univ. of Science and Technology of China (China)


Published in SPIE Proceedings Vol. 10420:
Ninth International Conference on Digital Image Processing (ICDIP 2017)
Charles M. Falco; Xudong Jiang, Editor(s)

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