Detecting Resized Double JPEG Compressed Images – Using Support Vector Machine - Communications and Multimedia Security Access content directly
Conference Papers Year : 2013

Detecting Resized Double JPEG Compressed Images – Using Support Vector Machine

Abstract

Since JPEG is the most widely used compression standard, detection of forgeries in JPEG images is necessary. In order to create a forged JPEG image, the image is usually loaded into a photo editing software, manipulated and then re-saved as JPEG. This yields to double JPEG compression artifacts, which can possibly reveal the forgery. Many techniques for the detection of double JPEG compressed images have been proposed. However, when the image is resized before the second compression step, the blocking artifacts of the first JPEG compression are destroyed. Therefore, most reported techniques for detecting double JPEG compression do not work for this case. In this paper, we propose a technique for detecting resized double JPEG compressed (called RD-JPEG) images. We first identify features that can discriminate RD-JPEG images from JPEG images and then use Support Vector Machines (SVM) as a classification tool. Experiments with many RD-JPEG images with different quality and scaling factors indicate that our technique works well.
Fichier principal
Vignette du fichier
978-3-642-40779-6_9_Chapter.pdf (557.38 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-01492837 , version 1 (20-03-2017)

Licence

Attribution

Identifiers

Cite

Hieu Cuong Nguyen, Stefan Katzenbeisser. Detecting Resized Double JPEG Compressed Images – Using Support Vector Machine. 14th International Conference on Communications and Multimedia Security (CMS), Sep 2013, Magdeburg,, Germany. pp.113-122, ⟨10.1007/978-3-642-40779-6_9⟩. ⟨hal-01492837⟩
93 View
370 Download

Altmetric

Share

Gmail Facebook X LinkedIn More