Gestalt geometric CAPTCHA

Nuttanont Hongwarittorrn, Suttikiat Meelap
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Abstract

This research investigated a new Image-Based CAPTCHA called Gestalt Geometric CAPTCHA, which does not require the use of a database of images, and is based on the Gestalt Theory of human recognition. The aim was to develop a type of CAPTCHA that is easier for human users and harder for bots. We experimentally tested the use and effectiveness of Gestalt Geometric CAPTCHA in terms of time for completion, authentication pass rate, and user satisfaction, in comparison with reCAPTCHA, Ironclad CAPTCHA, and ShapeCAPTCHA. We also tested our novel CAPTCHA for robustness against two shape detection and classification programs, ShapeChecker and Shape-detect. The results were promising, but some issues remain for future improvement.
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格式塔几何验证码
本研究研究了一种新的基于图像的CAPTCHA,称为格式塔几何CAPTCHA,它不需要使用图像数据库,并且基于人类识别的格式塔理论。其目的是开发一种对人类用户更容易、对机器人更难的验证码。我们通过实验测试了格式塔几何验证码在完成时间、认证通过率和用户满意度方面的使用和有效性,并与reCAPTCHA、Ironclad CAPTCHA和ShapeCAPTCHA进行了比较。我们还测试了我们的新CAPTCHA对两种形状检测和分类程序(ShapeChecker和shape -detect)的鲁棒性。结果令人鼓舞,但仍有一些问题有待改进。
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