COVERAGE - A novel database for copy-move forgery detection

Bihan Wen, Ye Zhu, Ramanathan Subramanian, Tian Tsong Ng, Xuanjing Shen, Stefan Winkler

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

57 Citations (Scopus)

Abstract

We present COVERAGE - a novel database containing copy-move forged images and their originals with similar but genuine objects. COVERAGE is designed to highlight and address tamper detection ambiguity of popular methods, caused by self-similarity within natural images. In COVERAGE, forged-original pairs are annotated with (i) the duplicated and forged region masks, and (ii) the tampering factor/similarity metric. For benchmarking, forgery quality is evaluated using (i) computer vision-based methods, and (ii) human detection performance. We also propose a novel sparsity-based metric for efficiently estimating forgery quality. Experimental results show that (a) popular forgery detection methods perform poorly over COVERAGE, and (b) the proposed sparsity based metric best correlates with human detection performance. We release the COVERAGE database to the research community.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings
EditorsLina Karam, Fernando Pereira, Gaurav Sharma
Place of PublicationUnited States
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages161-165
Number of pages5
ISBN (Electronic)9781467399616
ISBN (Print)9781467399623
DOIs
Publication statusPublished - 3 Aug 2016
Externally publishedYes
Event23rd IEEE International Conference on Image Processing, ICIP 2016 - Phoenix, United States
Duration: 25 Sep 201628 Sep 2016

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2016-August
ISSN (Print)1522-4880

Conference

Conference23rd IEEE International Conference on Image Processing, ICIP 2016
CountryUnited States
CityPhoenix
Period25/09/1628/09/16

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