AgeCAPTCHA: an Image-based CAPTCHA that Annotates Images of Human Faces with their Age Groups

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Annotating images with tags that describe the content of the images facilitates image retrieval. However, this task is challenging for both humans and computers. In response, a new approach has been proposed that converts the manual image annotation task into CAPTCHA challenges. However, this approach has not been widely used because of its weak security and the fact that it can be applied only to annotate for a specific type of attribute clearly separated into mutually exclusive categories (e.g., gender). In this paper, we propose a novel image annotation CAPTCHA scheme, which can successfully differentiate between humans and computers, annotate image content difficult to separate into mutually exclusive categories, and generate verified test images difficult for computers to identify but easy for humans. To test its feasibility, we applied our scheme to annotate images of human faces with their age groups and conducted user studies. The results showed that our proposed system, called AgeCAPTCHA, annotated images of human faces with high reliability, yet the process was completed by the subjects quickly and accurately enough for practical use. As a result, we have not only verified the effectiveness of our scheme but also increased the applicability of image annotation CAPTCHAs.
Publisher
KSII-KOR SOC INTERNET INFORMATION
Issue Date
2014-03
Language
English
Article Type
Article
Keywords

RECOGNITION; SECURITY

Citation

KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, v.8, no.3, pp.1071 - 1092

ISSN
1976-7277
DOI
10.3837/tiis.2014.03.021
URI
http://hdl.handle.net/10203/189066
Appears in Collection
GCT-Journal Papers(저널논문)
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