扭曲粘連字符驗證碼識別技術(shù)研究
[Abstract]:Network security problems, such as using network robots to register email boxes in batches, forum irrigation, malicious ticket brushing, violent password cracking and so on, not only cause waste of resources, affect the normal use of users, but also bring hidden trouble to user's account security. Twisted and conglutinated verification codes can increase the difficulty of being recognized by machines. The research on this kind of verification codes can not only design more secure and easy-to-use verification codes from the point of view of counter-recognition of the verification codes, but also discover the security vulnerabilities of the verification codes in a timely manner. Improve the safety of users online. In this paper, the image preprocessing technology of verification code and the theory of verification code recognition are deeply studied. Because there are many abnormal points in the distorted and conglutinated verification codes, and the noise interference is serious, the traditional recognition methods such as shape context have poor ability to deal with the deformation invariance problem of this type of verification code. In this paper, a method based on relative shape context and point pattern recognition is proposed, and the existing NetEase mailbox and CSDN verification code are recognized, which effectively solves the problem of the character adhesion between NetEase mailbox and CSDN verification code. In addition, the traditional shape context algorithm also has some defects, such as the shape and noise sensitivity of the character, the inaccuracy of describing the shape feature, and the complexity and time consuming of calculating the centroid. In this paper, an algorithm combining SIFT (Scale-invariantfeaturetransform) features with improved shape context is proposed, in which the SIFT descriptor is used to collect the shape structure information of the verification code and the partial least squares algorithm is used to eliminate the error matching points. In this paper, the experimental results are compared and analyzed, and the matching accuracy of character verification codes is improved.
【學(xué)位授予單位】:上海應(yīng)用技術(shù)大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2016
【分類號】:TP391.41;TP393.08
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