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CAPTCHA Research Group
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FACEDCAPTCHA

FaceDCAPTCHA is designed to prevent face detection by automated bots through
incorporating visual occlusions (black bars hiding face parts), applying visual
distortions, and blending embedded images into the background. Adversarial
learning is used to optimize the distortions that are applied to the CAPTCHA.

This CAPTCHA incorporates images of human faces, cartoons, and sketches on a
multi-colored background. To solve FaceDCAPTCHA, users must tap or click on all
the human face photographs.


RESULTS

In testing, humans averaged 97%-100% accuracy in solving FaceDCAPTCHA images
depending upon the distortions applied. Software face detection algorithms were
completely unsucessful in solving this CAPTCHA. [1]


DEMOS

Try FaceDCAPTCHA


PUBLICATIONS


JOURNAL ARTICLES

 1. G. Goswami, B. M. Powell, M. Vatsa, R. Singh, and A. Noore, “FaceDCAPTCHA:
    Face Detection based Color Image CAPTCHA,” Future Generation Computer
    Systems, vol. 31, pp. 59–68, Feb. 2014. PDF Publisher's Website

 * FaceDCAPTCHA
 * Demo

Dr. Brian M. Powell, Faculty Director
205 Armstrong Hall
94 Beechurst Avenue | PO Box 6109 | Morgantown, WV 26506-6109
P: 304.288.1549 | brian.powell@mail.wvu.edu
Lane Department of Computer Science and Electrical Engineering
Advanced Engineering Research Building
109 Research Way | PO Box 6109 | Morgantown, WV 26506-6109
P: 304.293.0405
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