Effects of Typefaces, Rotations and Sets of Characters of text-based CAPTCHA on Human Affirmative Rates
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Abstract
- Text-based CAPTCHAs are still a problem for humans. One of the effectiveness indicators for CAPTCHAs, a human-affirmative rate is the proportion of those who are able to correctly decode the text-based CAPTCHAs to those who have made an attempt to do it. It is thus interesting to examine the effects of (1) rotations of characters (2) typefaces and (3) sets of characters of CAPTCHAs on the human affirmative rates. The analysis of a lab experiment indicated that the effect of typefaces and sets of characters of CAPTCHA are statistically significant on the human affirmative rates at the 0.05 level, but the effects of rotations of characters of CAPTCHA were not significant. In addition to extending knowledge of text-based CAPTCHA’s design, developers could apply the findings to select typeface, rotations and sets of characters of text-based CAPTCHA that easy for human.
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