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  1. Proceedings of the First ACM workshop on Multimedia in forensics (MiFor '09)
  2. A new approach for JPEG resize and image splicing detection
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Graffiti-ID: matching and retrieval of graffiti images
Videntifierâ„¢ forensic: a new law enforcement service for automatic identification of illegal video material
Digital forgery estimation into DCT domain: a critical analysis
Single view geometry and active camera networks made easy
Temporal normalization of videos using visual speech
Image spam clustering: an unsupervised approach
A new approach for JPEG resize and image splicing detection
Multi-target tracking in time-lapse video forensics
Video surveillance and multimedia forensics: an application to trajectory analysis
Design and deployment of a digital forensics service platform for online videos
Exposing digital video forgery by ghost shadow artifact

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A new approach for JPEG resize and image splicing detection

Content Provider ACM Digital Library
Author Liu, Qingzhong Sung, Andrew H.
Abstract Today's ubiquitous digital media are easily tampered by, e.g., removing or adding objects from or into images without leaving any obvious clues. JPEG is a most widely used standard in digital images and it can be easily doctored. It is therefore necessary to have reliable methods to detect forgery in JPEG images for applications in law enforcement, forensics, etc. In this paper, based on the correlation of neighboring Discrete Cosine Transform (DCT) coefficients, we propose a method to detect resized JPEG images and spliced images, which are widely used in image forgery. In detail, the neighboring joint density features of the DCT coefficients are extracted; then Support Vector Machines (SVM) are applied to the features for detection. To improve the evaluation of JPEG resized detection, we utilize the shape parameter of generalized Gaussian distribution (GGD) of DCT coefficients to measure the image complexity. The study shows that our method is highly effective in detecting JPEG images resizing and splicing forgery. In the detection of resized JPEG image, the performance is related to both image complexity and resize scale factor. At the same scale factor, the detection performance in high image complexity is, as can be expected, lower than that in low image complexity.
Starting Page 43
Ending Page 48
Page Count 6
File Format PDF
ISBN 9781605587554
DOI 10.1145/1631081.1631092
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2009-10-23
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Joint density Splicing Image resize Generalized gaussian distribution Jpeg Svm Forgery detection
Content Type Text
Resource Type Article
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