关键词: 对抗学习, 验证码识别, 分割, 神经网络

Abstract:

In human-computer intelligent interaction, it is a basic technology for machine to recognize captcha automatically. Text-based captcha recognition usually preprocesses the captcha images, then cuts them, and finally classifies and recognizes the characters. The accuracy of character cutting directly affects the final recognition result. This paper proposes a method based on adversarial network to recognize text captchas. First, a Pix2pix network is trained to preprocess the captcha image, and then a pair of segmentation and recognition networks are obtained by using the method of confrontation training. The segmentation network can not only separate the pasting characters, but also filter out the hard-to-divide verification codes. The identification network adopts a context-dependent multi-channel convolution network, which can effectively solve the problem that the information cannot be identified due to information loss during the segmentation process. Experimental results show that this method can improve the accuracy of text-based captchas recognition.

Key words: adversarial learning, captcha cracking, segmentation, neural network