An efficient segmentation algorithm for CAPTCHAs with line cluttering and character warping

Authors:
Shih-Yu Huang;Yeuan-Kuen Lee;Graeme Bell;Zhan-He Ou
Affiliations:
Department of Computer Science and Information Engineering, Ming Chuan University, Taipei, Taiwan;Department of Computer Science and Information Engineering, Ming Chuan University, Taipei, Taiwan;Department of Computer Science and Information Engineering, Ming Chuan University, Taipei, Taiwan;Department of Computer Science and Information Engineering, Ming Chuan University, Taipei, Taiwan
Venue:
Multimedia Tools and Applications
Year:
2010

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Abstract

A CAPTCHA is a test designed to distinguish computer programs from human beings, in order to prevent the abuse of networked resources. Academic research into CAPTCHAs includes designing friendly and secure CAPTCHA systems and defeating existing CAPTCHA systems. Traditionally, 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, two new segmentation techniques called projection and middle-axis point separation are proposed for CAPTCHAs with line cluttering and character warping. Experimental results show the proposed techniques can achieve segmentation rates of about 75%.