• DocumentCode
    3751984
  • Title

    Gestalt geometric CAPTCHA

  • Author

    Nuttanont Hongwarittorrn;Suttikiat Meelap

  • Author_Institution
    Department of Computer Science, Faculty of Science and Technology, Thammasat University, Pathumthani, Thailand
  • fYear
    2015
  • Firstpage
    325
  • Lastpage
    330
  • 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.
  • Keywords
    "CAPTCHAs","Standards","Robustness","Psychology","Distortion","Image recognition","Semantics"
  • Publisher
    ieee
  • Conference_Titel
    Advanced Computer Science and Information Systems (ICACSIS), 2015 International Conference on
  • Type

    conf

  • DOI
    10.1109/ICACSIS.2015.7415185
  • Filename
    7415185