A Projection-based Segmentation Algorithm for Breaking MSN and YAHOO CAPTCHAs

Defeating a CAPTCHA test requires two procedures: segmentation and recognition. Recent research shows that the problem of segmentation is much harder than recognition. In this paper, a new projection-based segmentation algorithm is proposed for the MSN and Yahoo CAPTCHAs. Experimental results show that the proposed algorithm can improve correct segmentation rates ranging from 9% to 14% over the traditional one.

[1]  D.J. Russomanno,et al.  2D Captchas from 3D Models , 2006, Proceedings of the IEEE SoutheastCon 2006.

[2]  M. Shirali-Shahreza,et al.  Drawing CAPTCHA , 2006, 28th International Conference on Information Technology Interfaces, 2006..

[3]  Mary Czerwinski,et al.  Computers beat Humans at Single Character Recognition in Reading based Human Interaction Proofs (HIPs) , 2005, CEAS.

[4]  Henry S. Baird,et al.  Pessimal print: a reverse Turing test , 2001, Proceedings of Sixth International Conference on Document Analysis and Recognition.

[5]  Henry S. Baird,et al.  Implicit CAPTCHAs , 2005, DRR.

[6]  Clark Pope,et al.  Is it human or computer? Defending e-commerce with Captchas , 2005, IT Professional.

[7]  Patrice Y. Simard,et al.  Using Machine Learning to Break Visual Human Interaction Proofs (HIPs) , 2004, NIPS.

[8]  G. Moy,et al.  Distortion estimation techniques in solving visual CAPTCHAs , 2004, CVPR 2004.

[9]  Jitendra Malik,et al.  Recognizing objects in adversarial clutter: breaking a visual CAPTCHA , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[10]  Kris Gaj,et al.  Face Recognition CAPTCHAs , 2006, Advanced Int'l Conference on Telecommunications and Int'l Conference on Internet and Web Applications and Services (AICT-ICIW'06).