Subscribe

Issue No.03 - March (2014 vol.26)

pp: 711-724

Zhenjun Tang , Dept. of Comput. Sci., Guangxi Normal Univ., Guilin, China

Xianquan Zhang , Dept. of Comput. Sci., Guangxi Normal Univ., Guilin, China

Shichao Zhang , Dept. of Comput. Sci., Guangxi Normal Univ., Guilin, China

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TKDE.2013.45

ABSTRACT

This paper designs an efficient image hashing with a ring partition and a nonnegative matrix factorization (NMF), which has both the rotation robustness and good discriminative capability. The key contribution is a novel construction of rotation-invariant secondary image, which is used for the first time in image hashing and helps to make image hash resistant to rotation. In addition, NMF coefficients are approximately linearly changed by content-preserving manipulations, so as to measure hash similarity with correlation coefficient. We conduct experiments for illustrating the efficiency with 346 images. Our experiments show that the proposed hashing is robust against content-preserving operations, such as image rotation, JPEG compression, watermark embedding, Gaussian low-pass filtering, gamma correction, brightness adjustment, contrast adjustment, and image scaling. Receiver operating characteristics (ROC) curve comparisons are also conducted with the state-of-the-art algorithms, and demonstrate that the proposed hashing is much better than all these algorithms in classification performances with respect to robustness and discrimination.

INDEX TERMS

Robustness, Image coding, Algorithm design and analysis, Vectors, Transform coding, Feature extraction, Watermarking,ring partition, Image hashing, multimedia security, nonnegative matrix factorization

CITATION

Zhenjun Tang, Xianquan Zhang, Shichao Zhang, "Robust Perceptual Image Hashing Based on Ring Partition and NMF",

*IEEE Transactions on Knowledge & Data Engineering*, vol.26, no. 3, pp. 711-724, March 2014, doi:10.1109/TKDE.2013.45REFERENCES

- [1] M. Slaney and M. Casey, "Locality-Sensitive Hashing for Finding Nearest Neighbors,"
IEEE Signal Processing Magazine, vol. 25, no. 2, pp.128-131, Mar. 2008.- [2] M.N. Wu, C.C. Lin, and C.C. Chang, "Novel Image Copy Detection with Rotating Tolerance,"
J. Systems and Software, vol. 80, no. 7, pp. 1057-1069, 2007.- [3] S. Wang and X. Zhang, "Recent Development of Perceptual Image Hashing,"
J. Shanghai Univ. (English ed.), vol. 11, no. 4, pp. 323-331, 2007.- [4] F. Ahmed, M.Y. Siyal, and V.U. Abbas, "A Secure and Robust Hash-Based Scheme for Image Authentication,"
Signal Processing, vol. 90, no. 5, pp. 1456-1470, 2010.- [5] C. Qin, C.C. Chang, and P.Y. Chen, "Self-Embedding Fragile Watermarking with Restoration Capability Based on Adaptive Bit Allocation Mechanism,"
Signal Processing, vol. 92, no. 4, pp. 1137-1150, 2012.- [6] C.S. Lu, C.Y. Hsu, S.W. Sun, and P.C. Chang, "Robust Mesh-Based Hashing for Copy Detection and Tracing of Images,"
Proc. IEEE Int'l Conf. Multimedia and Expo, vol. 1, pp. 731-734, 2004.- [7] Z. Tang, S. Wang, X. Zhang, W. Wei, and S. Su, "Robust Image Hashing for Tamper Detection Using Non-Negative Matrix Factorization,"
J. Ubiquitous Convergence and Technology, vol. 2, no. 1, pp. 18-26, 2008.- [8] E. Hassan, S. Chaudhury, and M. Gopal, "Feature Combination in Kernel Space for Distance Based Image Hashing,"
IEEE Trans. Multimedia, vol. 14, no. 4, pp. 1179-1195, Aug. 2012.- [9] W. Lu and M. Wu, "Multimedia Forensic Hash Based on Visual Words,"
Proc. IEEE Int'l Conf. Image Processing, pp. 989-992, 2010.- [10] X. Lv and Z.J. Wang, "Reduced-Reference Image Quality Assessment Based on Perceptual Image Hashing,"
Proc. IEEE Int'l Conf. Image Processing, pp. 4361-4364, 2009.- [11] R. Venkatesan, S.-M. Koon, M.H. Jakubowski, and P. Moulin, "Robust Image Hashing,"
Proc. IEEE Int'l Conf. Image Processing, pp. 664-666, 2000.- [12] J. Fridrich and M. Goljan, "Robust Hash Functions for Digital Watermarking,"
Proc. IEEE Int'l Conf. Information Technology: Coding and Computing, pp. 178-183, 2000.- [13] C.Y. Lin and S.F. Chang, "A Robust Image Authentication System Distinguishing JPEG Compression from Malicious Manipulation,"
IEEE Trans. Circuits System and Video Technology, vol. 11, no. 2, pp. 153-168, Feb. 2001.- [14] D. Wu, X. Zhou, and X. Niu, "A Novel Image Hash Algorithm Resistant to Print-Scan,"
Signal Processing, vol. 89, no. 12, pp. 2415-2424, 2009.- [15] Z. Tang, S. Wang, X. Zhang, W. Wei, and Y. Zhao, "Lexicographical Framework for Image Hashing with Implementation Based on DCT and NMF,"
Multimedia Tools and Applications, vol. 52, no. 2/3, pp. 325-345, 2011.- [16] F. Lefebvre, B. Macq, and J.-D. Legat, "RASH: Radon Soft Hash Algorithm,"
Proc. European Signal Processing Conf., pp. 299-302, 2002.- [17] S.S. Kozat, R. Venkatesan, and M.K. Mihcak, "Robust Perceptual Image Hashing via Matrix Invariants,"
Proc. IEEE Int'l Conf. Image Processing, pp. 3443-3446, 2004.- [18] C.D. Roover, C.D. Vleeschouwer, F. Lefebvre, and B. Macq, "Robust Video Hashing Based on Radial Projections of Key Frames,"
IEEE Trans. Signal Processing, vol. 53, no. 10, pp. 4020-4036, Oct. 2005.- [19] A. Swaminathan, Y. Mao, and M. Wu, "Robust and Secure Image Hashing,"
IEEE Trans. Information Forensics and Security, vol. 1, no. 2, pp. 215-230, June 2006.- [20] V. Monga and M.K. Mihcak, "Robust and Secure Image Hashing via Non-Negative Matrix Factorizations,"
IEEE Trans. Information Forensics and Security, vol. 2, no. 3, pp. 376-390, Sept. 2007.- [21] Y. Lei, Y. Wang, and J. Huang, "Robust Image Hash in Radon Transform Domain for Authentication,"
Signal Processing: Image Comm., vol. 26, no. 6, pp. 280-288, 2011.- [22] USC-SIPI Image Database, http://sipi.usc.edudatabase/, Feb. 2007.
- [23] Ground Truth Database, http://www.cs.washington.edu/ research/imagedatabase groundtruth/, Accessed 8 May 2008.
- [24] M. Schneider and S.F. Chang, "A Robust Content Based Digital Signature for Image Authentication,"
Proc. IEEE Int'l Conf. Image Processing, vol. 3, pp. 227-230, 1996.- [25] V. Monga and B.L. Evans, "Perceptual Image Hashing via Feature Points: Performance Evaluation and Tradeoffs,"
IEEE Trans. Image Processing, vol. 15, no. 11, pp. 3452-3465, Nov. 2006.- [26] V. Monga, A. Banerjee, and B.L. Evans, "A Clustering Based Approach to Perceptual Image Hashing,"
IEEE Trans. Information Forensics and Security, vol. 1, no. 1, pp. 68-79, Mar. 2006.- [27] J.S. Seo, J. Haitsma, T. Kalker, and C.D. Yoo, "A Robust Image Fingerprinting System Using the Radon Transform,"
Signal Processing: Image Comm., vol. 19, no. 4, pp. 325-339, 2004.- [28] Y. Mao and M. Wu, "Unicity Distance of Robust Image Hashing,"
IEEE Trans. Information Forensics and Security, vol. 2, no. 3, pp. 462-467, Sept. 2007.- [29] F. Khelifi and J. Jiang, "Perceptual Image Hashing Based on Virtual Watermark Detection,"
IEEE Trans. Image Processing, vol. 19, no. 4, pp. 981-994, Apr. 2010.- [30] Z. Tang, S. Wang, X. Zhang, and W. Wei, "Structural Feature-Based Image Hashing and Similarity Metric for Tampering Detection,"
Fundamenta Informaticae, vol. 106, no. 1, pp. 75-91, 2011.- [31] X. Lv and Z.J. Wang, "Perceptual Image Hashing Based on Shape Contexts and Local Feature Points,"
IEEE Trans. Information Forensics and Security, vol. 7, no. 3, pp. 1081-1093, June 2012.- [32] Z. Tang, Y. Dai, and X. Zhang, "Perceptual Hashing for Color Images Using Invariant Moments,"
Applied Math. and Information Sciences, vol. 6, no. 2S, pp. 643-650, 2012.- [33] M.K. Hu, "Visual Pattern Recognition by Moment Invariants,"
IRE Trans. Information Theory, vol. 8, no. 2, pp. 179-187, 1962.- [34] Y. Li, Z. Lu, C. Zhu, and X. Niu, "Robust Image Hashing Based on Random Gabor Filtering and Dithered Lattice Vector Quantization,"
IEEE Trans. Image Processing, vol. 21, no. 4, pp. 1963-1980, Apr. 2012.- [35] Z. Tang, Y. Dai, X. Zhang, and S. Zhang, "Perceptual Image Hashing with Histogram of Color Vector Angles,"
Proc. Eight Int'l Conf. Active Media Technology (AMT '12), pp. 237-246, 2012.- [36] Y. Zhao, S. Wang, X. Zhang, and H. Yao, "Robust Hashing for Image Authentication Using Zernike Moments and Local Features,"
IEEE Trans. Information Forensics and Security, vol. 8, no. 1, pp. 55-63, Jan. 2013.- [37] D.D. Lee and H.S. Seung, "Learning the Parts of Objects by Non-Negative Matrix Factorization,"
Nature, vol. 401, pp. 788-791, 1999.- [38] J. Pan and J. Zhang, "Large Margin Based Nonnegative Matrix Factorization and Partial Least Squares Regression for Face Recognition,"
Pattern Recognition Letters, vol. 32, no. 14, pp. 1822-1835, 2011.- [39] I. Buciu and I. Pitas, "NMF, LNMF, and DNMF Modeling of Neural Receptive Fields Involved in Human Facial Expression Perception,"
J. Visual Comm. and Image Representation, vol. 17, no. 5, pp. 958-969, 2006.- [40] R. Sandler and M. Lindenbaum, "Nonnegative Matrix Factorization with Earth Mover's Distance Metric for Image Analysis,"
IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 33, no. 8, pp. 1590-1602, Aug. 2011.- [41] S. Xie, Z. Yang, and Y. Fu, "Nonnegative Matrix Factorization Applied to Nonlinear Speech and Image Cryptosystems,"
IEEE Trans. Circuits and Systems I: Regular Papers, vol. 55, no. 8, pp. 2356-2367, Sept. 2008.- [42] Y. Chen, L. Wang, and M. Dong, "Non-Negative Matrix Factorization for Semisupervised Heterogeneous Data Coclustering,"
IEEE Trans. Knowledge and Data Eng., vol. 22, no. 10, pp. 1459-1474, Oct. 2010.- [43] D.D. Lee and H.S. Seung, "Algorithms for Non-Negative Matrix Factorization,"
Proc. Advances in Neural Information Processing Systems, vol. 13, pp. 556-562, 2000.- [44] I. Kotsia, S. Zafeiriou, and I. Pitas, "A Novel Discriminant Non-Negative Matrix Factorization Algorithm with Applications to Facial Image Characterization Problems,"
IEEE Trans. Information Forensics and Security, vol. 2, no. 3, pp. 588-595, Sept. 2007.- [45] F.A.P. Petitcolas, "Watermarking Schemes Evaluation,"
IEEE Signal Processing Magazine, vol. 17, no. 5, pp. 58-64, Sept. 2000.- [46] T. Fawcett, "An Introduction to ROC Analysis,"
Pattern Recognition Letters, vol. 27, no. 8, pp. 861-874, 2006. |