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Study of Hollow Letter CAPTCHAs Recognition Technology Based on Color Filling Algorithm

  • Huishuang Shao (College of Computer Science and Technology, Chongqing University of Posts and Telecommunications) ;
  • Yurong Xia (Dept. of Training Center, Jining Polytechnic) ;
  • Kai Meng (China Unicom Shanxi Industrial Internet Limited Company) ;
  • Changhao Piao (School of Automation, Chongqing University of Posts and Telecommunications)
  • Received : 2021.02.09
  • Published : 2023.08.31

Abstract

The hollow letter CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) is an optimized version of solid CAPTCHA, specifically designed to weaken characteristic information and increase the difficulty of machine recognition. Although convolutional neural networks can solve CAPTCHA in a single step, a good attack result heavily relies on sufficient training data. To address this challenge, we propose a seed filling algorithm that converts hollow characters to solid ones after contour line restoration and applies three rounds of detection to remove noise background by eliminating noise blocks. Subsequently, we utilize a support vector machine to construct a feature vector for recognition. Security analysis and experiments show the effectiveness of this algorithm during the pre-processing stage, providing favorable conditions for subsequent recognition tasks and enhancing the accuracy of recognition for hollow CAPTCHA.

Keywords

Acknowledgement

This paper is supported by the National Natural Science Foundation of China (No. 61703068).

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