International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Most Trusted Research Journal Since Year 2012

ISSN: 2319-7064



Survey Paper | Computer Science & Engineering | India | Volume 4 Issue 11, November 2015

Image Recapture Discovery Algorithms: A Survey

Pradnya Sanas, Poonam Gupta

With the development of multimedia technology and digital devices, it is very easier to recapture image of high quality from LCD screens and the use of such recapture image in authentication can be harmful. An attacker may choose to recapture a forged image in order to hide imperfections and to increase its authenticity. To do forensic analysis of such images for evidence is very important. So detection of recapture images from set of images is very important in this case. In this paper we did survey of various recapture image detection algorithms with their pros and cons. Also we studied various features like aliasing, blurriness etc. of recaptured images, which can differentiate recapture image from original one.

Keywords: Multimedia Technology, LCD, Image Forensic, Recapture Detection, Aliasing, Blurriness

Edition: Volume 4 Issue 11, November 2015

Pages: 926 - 929


How to Cite this Article?

Pradnya Sanas, Poonam Gupta, "Image Recapture Discovery Algorithms: A Survey", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=NOV151302, Volume 4 Issue 11, November 2015, 926 - 929

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The Biometric used for authentication process of a person is Fingerprint which is more securable and unique for a persons to authenticate. A minutia matching is broadly used for fingerprint recognition and can be classified as ridge bifurcation and ridge ending. In this paper I projected Fingerprint Recognition using Minutia Matching Technique (FRMM). For Fingerprint thinning, the Thinning Filter is used to reduce the thickness from the binarized image, which scans the image at the boundary to preserves the quality of the image and extract the minutiae from the converted thinned image. The false matching ratio is better correlated to the existing algorithm.