Digital image forgery detection using JPEG features and local noise discrepancies

Bo Liu, Chi Man Pun, Xiao Chen Yuan

Research output: Contribution to journalArticlepeer-review

33 Citations (Scopus)

Abstract

Wide availability of image processing software makes counterfeiting become an easy and low-cost way to distort or conceal facts. Driven by great needs for valid forensic technique, many methods have been proposed to expose such forgeries. In this paper, we proposed an integrated algorithm which was able to detect two commonly used fraud practices: copy-move and splicing forgery in digital picture. To achieve this target, a special descriptor for each block was created combining the feature from JPEG block artificial grid with that from noise estimation. And forehand image quality assessment procedure reconciled these different features by setting proper weights. Experimental results showed that, compared to existing algorithms, our proposed method is effective on detecting both copy-move and splicing forgery regardless of JPEG compression ratio of the input image.

Original languageEnglish
Article number230425
JournalThe Scientific World Journal
Volume2014
DOIs
Publication statusPublished - 2014
Externally publishedYes

Fingerprint

Dive into the research topics of 'Digital image forgery detection using JPEG features and local noise discrepancies'. Together they form a unique fingerprint.

Cite this