一种多样变换的手写验证码自动识别算法的研究及应用

Research on Automatically Identifying Algorithm and Application about Handwritten CAPTCHA of Kinds of Diverse Transformation

摘要: 研究验证码自动识别技术可以进一步提升人识别验证码的可读性，增强机器识别的难度，从而提高网络安全性。针对目前提出的验证码识别方法基本都是采用光学字符识别(OCR)方法对机器写的标准字符进行识别，本文提出了一种多样变换的手写验证码自动识别算法，对彩色验证码进行识别主要包括彩色验证码的二值化、手写字符的区域分割、同一字符的区域连接、使用卷积神经网络对手写字符进行训练、手写字符识别。本文的实现结果明显优于OCR的识别结果。结果表明通过该网站的测试，基本上能自动识别该网站的验证码。

Abstract: Research on technique of automatically identifying CAPTCHA can promote people to identify the readability of verifying the code further and strengthen the difficulty that the machine identifies and raises a network safety thus. Currently aiming at the CAPTCHA identification methods are basically used optical character recognition (OCR) method to identify the standard characters written by the machine. The paper puts forward color CAPTCHA identifies to mainly include color verification code binary by threshold, the connect district segmentation of the handwritten character list, the near district of the same character list links, use convolution neural network to train a character and to identify handwritten character. The paper realization obviously surpasses an identifying of OCR result. The result shows CAPTCHA of the website that is basically passed by the website test; the website can automatically identify CAPTCHA of the website.