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Design and implementation of verification code identification based on anisotropic heat kernel

机译:基于各向异性热核的验证码识别设计与实现

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摘要

Many websites use verification codes to prevent users from using the machine automatically to register, login, malicious vote or irrigate but it brought great burden to the enterprises involved in internet marketing as entering the verification code manually. Improving the verification code security system needs the identification method as the corresponding testing system. We propose an anisotropic heat kernel equation group which can generate a heat source scale space during the kernel evolution based on infinite heat source axiom, design a multi-step anisotropic verification code identification algorithm which includes core procedure of building anisotropic heat kernel, settingwave energy information parameters, combing outverification codecharacters and corresponding peripheral procedure of gray scaling, binarizing, denoising, normalizing, segmenting and identifying, give out the detail criterion and parameter set. Actual test show the anisotropic heat kernel identification algorithm can be used on many kinds of verification code including text characters, mathematical, chinese, voice, 3D, programming, video, advertising, it has a higher rate of 25% and 50% than neural network and context matching algorithm separately for Yahoo site, 49% and 60% for Captcha site, 20% and 52% for Baidu site, 60% and 65% for 3DTakers site, 40% and 51% for MDP site.
机译:许多网站使用验证码来防止用户自动使用该机器进行注册,登录,恶意投票或灌溉,但是由于手动输入验证码,这给参与互联网营销的企业带来了沉重负担。完善验证码安全系统需要采用识别方法作为相应的测试系统。我们提出了一个基于无限热源公理的可在核演化过程中产生热源尺度空间的各向异性热核方程组,设计了包括建立各向异性热核,设置波能量信息的核心过程在内的多步各向异性验证码识别算法。参数,梳理验证码字符以及相应的灰度,二值化,去噪,归一化,分割和识别的外围过程,给出了详细的判据和参数集。实际测试表明,各向异性热核识别算法可用于文本字符,数学,中文,语音,3D,编程,视频,广告等多种验证码,其识别率比神经网络高25%和50%和上下文匹配算法分别用于Yahoo网站,Captcha网站的49%和60%,百度网站的20%和52%,3DTakers网站的60%和65%,MDP网站的40%和51%。

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