关键词: 卷积神经网络, 验证码, 模式识别, 预训练, 二值化

Abstract: At present, captcha is widely used on the Internet. This paper introduces convolutional neural networks method to captcha recognition. By customizing new convolutional training networks, this paper uses k-means algorithm method for divisible idiom character segmentation, and through model pre-training to auto-generate images to enrich training dataset. Pre-training makes training network have a good initial value, thus speeds up the network convergence. Aiming at indivisible captcha, it leaves out character segmentation and inputs whole image to the convolutional networks model. It uses affine transformation, flood fill, and SVM classification or combines multi-label learning for captcha recognition. Finally, experimental study confirms that the method which is based on convolutional neural network, on average, achieves test accuracy of around 99% in the three types of CAPTCHA.

Key words: convolutional neural networks, captcha, pattern recognition, pre-training, binarization