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Robust image hashing via colour vector angles and discrete wavelet transform

Robust image hashing via colour vector angles and discrete wavelet transform

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Colour vector angle has been widely used in edge detection and image retrieval, but its investigation in image hashing is still limited. In this study, the authors investigate the use of colour vector angle in image hashing and propose a robust hashing algorithm combining colour vector angles with discrete wavelet transform (DWT). Specifically, the input image is firstly resized to a normalised size by bi-cubic interpolation and blurred by a Gaussian low-pass filter. Colour vector angles are then calculated and divided into non-overlapping blocks. Next, block means of colour vector angles are extracted to form a feature matrix, which is further compressed by DWT. Image hash is finally formed by those DWT coefficients in the LL sub-band. Experiments show that the proposed hashing is robust against normal digital operations, such as JPEG compression, watermarking embedding and rotation within 5°. Receiver operating characteristics curve comparisons are conducted and the results show that the proposed hashing is better than some well-known algorithms.

References

    1. 1)
      • N. Chen , W. Wan , H.-D. Xiao .
        1. Chen, N., Wan, W., Xiao, H.-D.: ‘Robust audio hashing based on discrete-wavelet-transform and non-negative matrix factorisation’, IET Commun., 2010, 4, (14), pp. 17221731 (doi: 10.1049/iet-com.2009.0749).
        . IET Commun. , 14 , 1722 - 1731
    2. 2)
      • M. Schneider , S.F. Chang .
        2. Schneider, M., Chang, S.F.: ‘A robust content based digital signature for image authentication’. Proc. IEEE Int. Conf. on Image Processing, Laussane, Switzerland, 16–19 September 1996, vol. 3, pp. 227230.
        . Proc. IEEE Int. Conf. on Image Processing , 227 - 230
    3. 3)
      • R. Venkatesan , S.-M. Koon , M.H. Jakubowski , P. Moulin .
        3. Venkatesan, R., Koon, S.-M., Jakubowski, M.H., Moulin, P.: ‘Robust image hashing’. Proc. IEEE Int. Conf. on Image Processing, Vancouver, Canada, 10–13 September 2000, pp. 664666.
        . Proc. IEEE Int. Conf. on Image Processing , 664 - 666
    4. 4)
      • V. Monga , B.L. Evans .
        4. Monga, V., Evans, B.L.: ‘Perceptual image hashing via feature points: performance evaluation and trade-offs’, IEEE Trans. Image Process., 2006, 15, (11), pp. 34533466 (doi: 10.1109/TIP.2006.881948).
        . IEEE Trans. Image Process. , 11 , 3453 - 3466
    5. 5)
      • F. Ahmed , M.Y. Siyal , V.U. Abbas .
        5. Ahmed, F., Siyal, M.Y., Abbas, V.U.: ‘A secure and robust hash-based scheme for image authentication’, Signal Process., 2010, 90, (5), pp. 14561470 (doi: 10.1016/j.sigpro.2009.05.024).
        . Signal Process. , 5 , 1456 - 1470
    6. 6)
      • Z. Tang , L. Huang , Y. Dai , F. Yang .
        6. Tang, Z., Huang, L., Dai, Y., Yang, F.: ‘Robust image hashing based on multiple histograms’, Int. J. Digital Content Technol. Appl., 2012, 6, (23), pp. 3947 (doi: 10.4156/jdcta.vol6.issue23.5).
        . Int. J. Digital Content Technol. Appl. , 23 , 39 - 47
    7. 7)
      • J. Fridrich , M. Goljan .
        7. Fridrich, J., Goljan, M.: ‘Robust hash functions for digital watermarking’. Proc. IEEE Int. Conf. on Information Technology: Coding and Computing, Las Vergas, USA, Mar. 27–29, 2000, pp. 178183.
        . Proc. IEEE Int. Conf. on Information Technology: Coding and Computing , 178 - 183
    8. 8)
      • C.Y. Lin , S.F. Chang .
        8. Lin, C.Y., Chang, S.F.: ‘A robust image authentication system distinguishing JPEG compression from malicious manipulation’, IEEE Trans. Circuits Syst. Video Technol., 2001, 11, (2), pp. 153168 (doi: 10.1109/76.905982).
        . IEEE Trans. Circuits Syst. Video Technol. , 2 , 153 - 168
    9. 9)
      • F. Lefebvre , B. Macq , J.-D. Legat .
        9. Lefebvre, F., Macq, B., Legat, J.-D.: ‘RASH: Radon soft hash algorithm’. Proc. European Signal Processing Conf., Toulouse, France, Sep. 3–6, 2002, pp. 299302.
        . Proc. European Signal Processing Conf. , 299 - 302
    10. 10)
      • C.D. Roover , C.D. Vleeschouwer , F. Lefebvre , B. Macq .
        10. Roover, C.D., Vleeschouwer, C.D., Lefebvre, F., Macq, B.: ‘Robust video hashing based on radial projections of key frames’, IEEE Trans. Signal Process., 2005, 53, (10), pp. 40204036 (doi: 10.1109/TSP.2005.855414).
        . IEEE Trans. Signal Process. , 10 , 4020 - 4036
    11. 11)
      • Y. Ou , K.H. Rhee .
        11. Ou, Y., Rhee, K.H.: ‘A key-dependent secure image hashing scheme by using Radon transform’. Proc. IEEE Int. Symp. on Intelligent Signal Processing and Communication Systems, Kanazawa, Japan, 7–9 December 2009, pp. 595598.
        . Proc. IEEE Int. Symp. on Intelligent Signal Processing and Communication Systems , 595 - 598
    12. 12)
      • A. Swaminathan , Y. Mao , M. Wu .
        12. Swaminathan, A., Mao, Y., Wu, M.: ‘Robust and secure image hashing’, IEEE Trans. Inf. Forensics Sec., 2006, 1, (2), pp. 215230 (doi: 10.1109/TIFS.2006.873601).
        . IEEE Trans. Inf. Forensics Sec. , 2 , 215 - 230
    13. 13)
      • D. Wu , X. Zhou , X. Niu .
        13. Wu, D., Zhou, X., Niu, X.: ‘A novel image hash algorithm resistant to print–scan’, Signal Process., 2009, 89, (12), pp. 24152424 (doi: 10.1016/j.sigpro.2009.05.016).
        . Signal Process. , 12 , 2415 - 2424
    14. 14)
      • S.S. Kozat , K. Mihcak , R. Venkatesan .
        14. Kozat, S.S., Mihcak, K., Venkatesan, R.: ‘Robust perceptual image hashing via matrix invariants’. Proc. IEEE Int. Conf. on Image Processing, Singapore, 24–27 October 2004, pp. 34433446.
        . Proc. IEEE Int. Conf. on Image Processing , 3443 - 3446
    15. 15)
      • V. Monga , M.K. Mihcak .
        15. Monga, V., Mihcak, M.K.: ‘Robust and secure image hashing via non-negative matrix factorizations’, IEEE Trans. Inf. Forensics Sec., 2007, 2, (3), pp. 376390 (doi: 10.1109/TIFS.2007.902670).
        . IEEE Trans. Inf. Forensics Sec. , 3 , 376 - 390
    16. 16)
      • Z. Tang , S. Wang , X. Zhang , W. Wei , S. Su .
        16. Tang, Z., Wang, S., Zhang, X., Wei, W., Su, S.: ‘Robust image hashing for tamper detection using non-negative matrix factorization’, J. Ubiquit. Convergence Technol., 2008, 2, (1), pp. 1826.
        . J. Ubiquit. Convergence Technol. , 1 , 18 - 26
    17. 17)
      • F. Khelifi , J. Jiang .
        17. Khelifi, F., Jiang, J.: ‘Perceptual image hashing based on virtual watermark detection’, IEEE Trans. Image Process., 2010, 19, (4), pp. 981994 (doi: 10.1109/TIP.2009.2038637).
        . IEEE Trans. Image Process. , 4 , 981 - 994
    18. 18)
      • W. Lu , M. Wu .
        18. Lu, W., Wu, M.: ‘Multimedia forensic hash based on visual words’. Proc. IEEE Int. Conf. on Image Processing, Hong Kong, China, Sept. 26–29, 2010, pp. 989992.
        . Proc. IEEE Int. Conf. on Image Processing , 989 - 992
    19. 19)
      • Y. Zhao , W. Wei .
        19. Zhao, Y., Wei, W.: ‘Perceptual image hash for tampering detection using Zernike moments’. Proc. IEEE Int. Conf. on Progress in Informatics and Computing, Shanghai, China, 10–12 December 2010, vol. 2, pp. 738742.
        . Proc. IEEE Int. Conf. on Progress in Informatics and Computing , 738 - 742
    20. 20)
      • Z. Tang , S. Wang , X. Zhang , W. Wei .
        20. Tang, Z., Wang, S., Zhang, X., Wei, W.: ‘Structural feature-based image hashing and similarity metric for tampering detection’, Fundam. Inform., 2011, 106, (1), pp. 7591.
        . Fundam. Inform. , 1 , 75 - 91
    21. 21)
      • F. Liu , L. Cheng , H. Leung , Q. Fu .
        21. Liu, F., Cheng, L., Leung, H., Fu, Q.: ‘Wave atom transform generated strong image hashing scheme’, Opt. Commun., 2012, 285, (24), pp. 50085018 (doi: 10.1016/j.optcom.2012.08.007).
        . Opt. Commun. , 24 , 5008 - 5018
    22. 22)
      • X. Lv , Z.J. Wang .
        22. Lv, X., Wang, Z.J.: ‘Perceptual image hashing based on shape contexts and local feature points’, IEEE Trans. Inf. Forensics Secur., 2012, 7, (3), pp. 10811093 (doi: 10.1109/TIFS.2012.2190594).
        . IEEE Trans. Inf. Forensics Secur. , 3 , 1081 - 1093
    23. 23)
      • Y. Li , Z. Lu , C. Zhu , X. Niu .
        23. Li, Y., Lu, Z., Zhu, C., Niu, X.: ‘Robust image hashing based on random Gabor filtering and dithered lattice vector quantization’, IEEE Trans. Image Process., 2012, 21, (4), pp. 19631980 (doi: 10.1109/TIP.2011.2171698).
        . IEEE Trans. Image Process. , 4 , 1963 - 1980
    24. 24)
      • C. Qin , C.-C., Chang , P.-L. Tsou .
        24. Qin, C., Chang, C.-C.,, Tsou, P.-L.: ‘Robust image hashing using non-uniform sampling in discrete Fourier domain’, Digital Signal Process., 2013, 23, (2), pp. 578585 (doi: 10.1016/j.dsp.2012.11.002).
        . Digital Signal Process. , 2 , 578 - 585
    25. 25)
      • Y. Zhao , S. Wang , X. Zhang , H. Yao .
        25. Zhao, Y., Wang, S., Zhang, X., Yao, H.: ‘Robust hashing for image authentication using Zernike moments and local features’, IEEE Trans. Inf. Forensics Secur., 2013, 8, (1), pp. 5563. (doi: 10.1109/TIFS.2012.2223680).
        . IEEE Trans. Inf. Forensics Secur. , 1 , 55 - 63
    26. 26)
      • R.D. Dony , S. Wesolkowski .
        26. Dony, R.D., Wesolkowski, S.: ‘Edge detection on color images using RGB vector angles’. Proc. IEEE Canadian Conf. on Electrical and Computer Engineering, Edmonton, Alberta, Canada, May 9–12, 1999, vol. 2, pp. 687692.
        . Proc. IEEE Canadian Conf. on Electrical and Computer Engineering , 687 - 692
    27. 27)
      • H.Y. Lee , H.K. Lee , Y.H. Ha .
        27. Lee, H.Y., Lee, H.K., Ha, Y.H.: ‘Spatial color descriptor for image retrieval and video segmentation’, IEEE Trans. Multimed., 2003, 5, (3), pp. 358367 (doi: 10.1109/TMM.2003.814792).
        . IEEE Trans. Multimed. , 3 , 358 - 367
    28. 28)
      • N.W. Kim , T.Y. Kim , J.S. Choi .
        28. Kim, N.W., Kim, T.Y., Choi, J.S.: ‘Edge-based spatial descriptor for content-based image retrieval’, Lect. Notes Comput. Sci., 2005, 3568, pp. 454464 (doi: 10.1007/11526346_49).
        . Lect. Notes Comput. Sci. , 454 - 464
    29. 29)
      • 29. USC-SIPI Image Database. [Online]. Available: http://sipi.usc.edu/database/, accessed February 2007.
        .
    30. 30)
      • F.A.P. Petitcolas .
        30. Petitcolas, F.A.P.: ‘Watermarking schemes evaluation’, IEEE Signal Process. Mag., 2000, 17, (5), pp. 5864 (doi: 10.1109/79.879339).
        . IEEE Signal Process. Mag. , 5 , 58 - 64
    31. 31)
      • 31. Ground Truth Database. [Online]. Available: http://www.cs.washington.edu/research/imagedatabase/groundtruth/, accessed May 2008.
        .
    32. 32)
      • T. Fawcett .
        32. Fawcett, T.: ‘An introduction to ROC analysis’, Pattern Recognit. Lett., 2006, 27, (8), pp. 861874 (doi: 10.1016/j.patrec.2005.10.010).
        . Pattern Recognit. Lett. , 8 , 861 - 874
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