IVIRJun 23, 2018

Robust Image Identification for Double-Compressed JPEG Images

arXiv:1807.06928v16 citations
Originality Incremental advance
AI Analysis

This addresses image identification and integrity detection for social network users and providers, but it is incremental as it builds on existing schemes with a specific improvement.

The paper tackles the problem of identifying single-compressed JPEG images that share the same original as double-compressed ones, commonly re-compressed on social networks, by using only DC coefficient signs and a threshold to avoid double-compression errors, and it outperforms conventional methods in querying performance.

It is known that JPEG images uploaded to social networks (SNs) are mostly re-compressed by the social network providers. Because of such a situation, a new image identification scheme for double-compressed JPEG images is proposed in this paper. The aim is to detect single-compressed images that have the same original image as that of a double-compressed one. In the proposed scheme, the signs of only DC coefficients in DCT coefficients and one threshold value are used for the identification. The use of them allows us to robustly avoid errors caused by double-compression, which are not considered in conventional schemes. The proposed scheme has applications not only to find uploaded images corresponding to double-compressed ones, but also to detect some image integrity. The simulation results demonstrate that the proposed one outperforms conventional ones including state-of-art image hashing one in terms of the querying performance.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes