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一种扭曲粘连字符验证码识别方法 被引量：19

A Recognition Method for Distorted and Merged Text-Based CAPTCHA
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摘要 验证码识别研究能及时发现验证码的安全漏洞,使其变得更加安全.扭曲粘连字符验证码能抵抗字符分割,是验证码识别中的难点.针对由扭曲粘连字符构成的验证码,提出一种基于密集尺度不变特征变换(DENSE SIFT)和随机抽样一致性算法(RANSAC)的识别方法.首先通过DENSE SIFT特征匹配获得匹配点集,再利用RANSAC算法获取匹配信息,最后采用队列式分析算法得出识别结果.实验表明,该方法对不同难度级别的扭曲粘连验证码均有较好的效果. The study of CAPTCHA recognition can discover CAPTCHA security vulnerabilities in time to make it more secure. Distorted and merged CAPTCHA can resist character segmentation, which is the difficult in CAPTCHA recognition. An approach based on DENSE SIFT and RANSAC algorithm is presented for recognition of distorted and merged CAPTCHA. Firstly, matching set is obtained through the matching of DENSE SIFT. Then, matching information is got by using RANSAC algorithm. Finally, recognition results are acquired by means of queue-analysis algorithm. The experimental results show that the proposed method has good performance on CAPTCHAs in different levels of difficulty.
作者 尹龙 尹东 张荣 王德建
机构地区 中国科学技术大学信息科学技术学院合肥
出处 《模式识别与人工智能》 EI CSCD 北大核心 2014年第3期235-241,共7页 Pattern Recognition and Artificial Intelligence
关键词 验证码识别 扭曲粘连字符 密集尺度不变特征变换(DENSE SIFT) 随机抽样一致性算法(RANSAC) CAPTCHA Recognition, Distorted and Merged Character, Dense Scale Invariant FeatureTransform （DENSE SIFT）, Random Sample Consensus （RANSAC）
分类号 TP391.41 [自动化与计算机技术—计算机应用技术]
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参考文献12

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二级参考文献27

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共引文献38

同被引文献93

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引证文献19

二级引证文献43

模式识别与人工智能
2014年 第3期

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