Detecting Recompression of JPEG Images via Periodicity Analysis of Compression Artifacts for Tampering Detection

Authors:
Yi-Lei Chen; Chiou-Ting Hsu
Affiliations:
Dept. of Comput. Sci., Nat. Tsing Hua Univ., Hsinchu, Taiwan;-
Venue:
IEEE Transactions on Information Forensics and Security
Year:
2011

Citing 0
Cited 2

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MiFor '11 Proceedings of the 3rd international ACM workshop on Multimedia in forensics and intelligence
Shift recompression-based feature mining for detecting content-aware scaled forgery in JPEG images

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Abstract

Due to the popularity of JPEG as an image compression standard, the ability to detect tampering in JPEG images has become increasingly important. Tampering of compressed images often involves recompression and tends to erase traces of tampering found in uncompressed images. In this paper, we present a new technique to discover traces caused by recompression. We assume all source images are in JPEG format and propose to formulate the periodic characteristics of JPEG images both in spatial and transform domains. Using theoretical analysis, we design a robust detection approach which is able to detect either block-aligned or misaligned recompression. Experimental results demonstrate the validity and effectiveness of the proposed approach, and also show it outperforms existing methods.