Statistical Detector of Resampled TIFF Images - Université de technologie de Troyes Access content directly
Conference Papers Year : 2018

Statistical Detector of Resampled TIFF Images

Abstract

Resampling is a common manipulation in creating tampered digital images. The goal of this paper is to develop an efficient detector to distinguish between a resampled TIFF image from an original TIFF image. To this end, we first propose a statistical model for resampled TIFF images by analyzing the complete processing process from a RAW image to a resampled TIFF image. Next, we formulate the detection problem as a likelihood ratio test between the models of original and resampled TIFF images. The test power is analytically evaluated in the context that all model parameters of original TIFF images are unknown. Numerous numerical experiments justify the performances of the detector.
No file

Dates and versions

hal-02362378 , version 1 (13-11-2019)

Identifiers

Cite

Nhan Le, Florent Retraint. Statistical Detector of Resampled TIFF Images. 2018 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), Dec 2018, Louisville, United States. pp.398-401, ⟨10.1109/ISSPIT.2018.8642747⟩. ⟨hal-02362378⟩
29 View
0 Download

Altmetric

Share

Gmail Mastodon Facebook X LinkedIn More