Robust image hashing via non-negative matrix factorizations

Vishal Monga, M. Kivanç Mihçak

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Scopus citations

Abstract

In this paper, we propose the use of non-negative matrix factorization (NMF) for robust image hashing. In particular, we view images as matrices and the goal of hashing as a randomized dimensionality reduction that retains the essence of the original image matrix while preventing against intentional attacks of guessing and forgery. Our work is motivated by the fact that standard-rank reduction techniques such as the QR, and Singular Value Decomposition (SVD), produce low rank bases which do not respect the structure (i.e. non-negativity for images) of the original data. We observe that NMFs have two very desirable properties for secure image hashing applications: 1.) The additivity property resulting from the non-negativity constraints results in bases that capture local characteristics of the image, thereby significantly reducing misclassification, and 2.) the effect of geometric attacks on images in the spatial domain manifests (approximately) as independent identically distributed noise on NMF vectors, allowing design of detectors that are both computationally simple and at the same time optimal in the sense of minimizing error probabilities. ROC (receiver operating characteristics) analysis over a large image database reveals that the proposed algorithms significantly outperform existing approaches for robust image hashing.

Original languageEnglish (US)
Title of host publication2006 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings
StatePublished - Dec 1 2006
Event2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006 - Toulouse, France
Duration: May 14 2006May 19 2006

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2
ISSN (Print)1520-6149

Other

Other2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006
CountryFrance
CityToulouse
Period5/14/065/19/06

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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  • Cite this

    Monga, V., & Mihçak, M. K. (2006). Robust image hashing via non-negative matrix factorizations. In 2006 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings [1660320] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2).