A smart phone image database for single image recapture detection

Xinting Gao, Bo Qiu, Jingjing Shen, Tian Tsong Ng, Yun Qing Shi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

Image recapture detection (IRD) is to distinguish real-scene images from the recaptured ones. Being able to detect recaptured images, a single image based counter-measure for rebroadcast attack on a face authentication system becomes feasible. Being able to detect recaptured images, general object recognition can differentiate the objects on a poster from the real ones, so that robot vision is more intelligent. Being able to detect recaptured images, composite image can be detected when recapture is used as a tool to cover the composite clues. As more and more methods have been proposed for IRD, an open database is indispensable to provide a common platform to compare the performance of different methods and to expedite further research and collaboration in the field of IRD. This paper describes a recaptured image database captured by smart phone cameras. The cameras of smart phones represent the middle to low-end market of consumer cameras. The database includes real-scene images and the corresponding recaptured ones, which targets to evaluate the performance of image recapture detection classifiers as well as provide a reliable data source for modeling the physical process to obtain the recaptured images. There are three main contributions in this work. Firstly, we construct a challenging database of recaptured images, which is the only publicly open database up to date. Secondly, the database is constructed by the smart phone cameras, which will promote the research of algorithms suitable for consumer electronic applications. Thirdly, the contents of the real-scene images and the recaptured images are in pair, which makes the modeling of the recaptured process possible.

Original languageEnglish (US)
Title of host publicationDigital Watermarking - 9th International Workshop, IWDW 2010, Revised Selected Papers
PublisherSpringer Verlag
Pages90-104
Number of pages15
ISBN (Print)9783642184048
DOIs
StatePublished - 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6526 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Keywords

  • image database
  • image forensics
  • image recapture detection

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