• DocumentCode
    579737
  • Title

    Face recognition CAPTCHA

  • Author

    Goswami, Gaurav ; Singh, Richa ; Vatsa, Mayank ; Powell, Brian ; Noore, Afzel

  • Author_Institution
    IIIT-Delhi, New Delhi, India
  • fYear
    2012
  • fDate
    23-27 Sept. 2012
  • Firstpage
    412
  • Lastpage
    417
  • Abstract
    CAPTCHA is one of the Turing tests used to classify human users and automated scripts. Existing CAPTCHAs, especially text-based CAPTCHAs, are used in many applications, however they pose challenges due to language dependency and high attack rates. In this paper, we propose a face recognition-based CAPTCHA as a potential solution. To solve the CAPTCHA, users must correctly find one pair of human face images, that belong to same subject, embedded in a complex background without selecting any nonface image or impostor pair. The proposed algorithm generates CAPTCHA that offer better human accuracy and lower attack rates compared to existing approaches.
  • Keywords
    face recognition; image classification; Turing test; automated script classification; face recognition CAPTCHA; human user classification; text-based CAPTCHA; Accuracy; Algorithm design and analysis; Face; Face recognition; Humans; Image color analysis; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biometrics: Theory, Applications and Systems (BTAS), 2012 IEEE Fifth International Conference on
  • Conference_Location
    Arlington, VA
  • Print_ISBN
    978-1-4673-1384-1
  • Electronic_ISBN
    978-1-4673-1383-4
  • Type

    conf

  • DOI
    10.1109/BTAS.2012.6374608
  • Filename
    6374608