Human Interactive Proofs: Second International Workshop, HIP by Kumar Chellapilla, Kevin Larson, Patrice Y. Simard, Mary

By Kumar Chellapilla, Kevin Larson, Patrice Y. Simard, Mary Czerwinski (auth.), Henry S. Baird, Daniel P. Lopresti (eds.)

This publication constitutes the refereed lawsuits of the second one foreign Workshop on Human Interactive Proofs, HIP 2005, held in Bethlehem, PA, united states in may possibly 2005.

The nine revised complete papers awarded have been conscientiously reviewed and chosen for presentation. This e-book is the 1st archival e-book dedicated to the hot type of safeguard protocols referred to as human interactive proofs. The variation of HIPs getting used in e-commerce and internet prone this day is totally computerized public Turing exams to inform pcs and people aside, CAPTCHAs. The papers during this booklet are prepared in topical sections on CAPTCHAs and function research, HIP architectures, HIP as safeguard structures components.

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Extra info for Human Interactive Proofs: Second International Workshop, HIP 2005, Bethlehem, PA, USA, May 19-20, 2005. Proceedings

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Fig. 5. Examples of handwritten images where OCR systems fail. The truth words are: Young America, Clinton, Blasdell Method 4: Add occlusion using the same pixels as the foreground pixels (black pixels), arcs, or lines. Gestalt laws: Law of familiarity, background (Fig. 6). Visual CAPTCHA with Handwritten Image Analysis 47 Fig. 6. Examples of handwritten images where OCR systems fail. The truth words are: Rockport, Albany, Buffalo Method 5: Change word orientation entirely, or the orientation for few letters only.

A Highly Legible CAPTCHA That Resists Segmentation Attacks 41 References [BAL00] M. Blum, L. A. von Ahn, and J. Langford, The CAPTCHA Project, “Completely Automatic Public Turing Test to tell Computers and Humans Apart,” Dept. net, and personal communications, November, 2000. [BK02] H. S. Baird and K. , 5th IAPR Int’l Workshop on Document Analysis Systems, Princeton, NJ, SpringerVerlag (Berlin) LNCS 2423, pp. 507–518, August 2002. [BR05] H. S. Baird and T. , IS&T/SPIE Document Recognition & Retrieval XII Conf,, San Jose, CA, January 16–20, 2005.

Horizontal mirror, vertical mirror, flip-flop. Seneca We need to mention that all the methods described here would clearly work for machine-printed text images, the same as the other methods described so far in literature for machine-printed text images would work for handwritten text images. However, the advantage of using handwriting is that most handwritten text challenges are uniquely problematic and usually more severe than problems encountered in recognizing machine-printed text. By using handwriting we are adding more difficulties to the machine recognition task but we do not alter the human recognition capabilities in any way since handwriting recognition is the most common task for humans.

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