An efficient statistical-based retrieval approach for JPEG2000 compressed images

Chaker, Amani; Kaaniche, Mounir; Benazza-Benyahia, Amel; Antonini, Marc

doi:10.1109/eusipco.2015.7362700

Cited by 7 publications

(2 citation statements)

References 24 publications

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“…So far, several identification schemes and image hash functions have been developed for authenticating images [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20]. They can be broadly classified into two types according to a difference in extracted features: compression method-depended type, to which the proposed scheme corresponds, and compression methodindependent type.…”

Section: Introductionmentioning

confidence: 99%

“…Most of these schemes not only are robust against a difference in compressed levels but also do not produce false negative matches in any compression level. However, the conventional schemes [3][4][5][6][7][9][10][11] do not consider to identify images securely, since it is impossible to avoid the effect caused by a difference in compression levels.…”

Section: Introductionmentioning

confidence: 99%

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[Paper] Fuzzy Commitment Scheme-Based Secure Identification for JPEG XR Images under Various Compression Ratios

Iida

Kiya

2017

MTA

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A secure identification scheme for JPEG XR images is proposed in this paper.The aim is to securely identify JPEG XR images which are generated from the same original image under various compression levels. The positive and negative signs of lapped biorthogonal transform coefficients are used as features.The proposed scheme is robust against a difference in compression levels, and does not produce false negative matches in any compression level. In addition, to construct a secure identification system, we propose a novel identification system that consists of an error correction technique and a fuzzy commitment scheme, which is a well-known biometric cryptosystem. There is no existing scheme having these properties for JPEG XR images. Moreover, a way for speeding up the identification is also proposed. The experimental results show the proposed scheme is effective for identifying JPEG XR images in terms of true positive matches.

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