
Mathematical Biosciences and Engineering, 2019, 16(5): 61036120. doi: 10.3934/mbe.2019305.
Research article Special Issues
Export file:
Format
 RIS(for EndNote,Reference Manager,ProCite)
 BibTex
 Text
Content
 Citation Only
 Citation and Abstract
Robust image hashing via visual attention model and ring partition
Guangxi Key Lab of Multisource Information Mining & Security, and Department of Computer Science, Guangxi Normal University, Guilin 541004, China
Received: , Accepted: , Published:
Special Issues: Security and Privacy Protection for Multimedia Information Processing and communication
Keywords: image hashing; visual attention model; ring partition; saliency map; image copy detection
Citation: Zhenjun Tang, Yongzheng Yu, Hanyun Zhang, Mengzhu Yu, Chunqiang Yu, Xianquan Zhang. Robust image hashing via visual attention model and ring partition. Mathematical Biosciences and Engineering, 2019, 16(5): 61036120. doi: 10.3934/mbe.2019305
References:
 1. Z. Tang, Z. Huang, X. Q. Zhang, et al., Robust image hashing with multidimensional scaling, Signal Process., 137(2017), 240–250.
 2. C. Qin, X. Chen, D. Ye, et al., A novel image hashing scheme with perceptual robustness using block truncation coding, Inform. Sci., 361(2016), 84–99.
 3. Z. Tang, L. Chen, X. Q. Zhang, et al., Robust image hashing with tensor decomposition, IEEE Trans. Knowl. Data En., 31(2019), 549–560.
 4. Z. Tang, S. Wang, X. P. Zhang, et al., Lexicographical framework for image hashing with implementation based on DCT and NMF, Multimed. Tools Appl., 52(2011), 325–345.
 5. F. Lefebvre, B. Macq and J. D. Legat, RASH: Radon soft hash algorithm, In: Proc. of European Signal Processing Conference, Toulouse, France, Sep. 3−6, 2002, pp.299–302.
 6. A. Swaminathan, Y. Mao and M. Wu, Robust and secure image hashing, IEEE Trans. Inf. Foren. Secur., 1(2006), 215–230.
 7. V. Monga and B. L. Evans, Perceptual image hashing via feature points: performance evaluation and tradeoffs, IEEE Trans. Image Process., 15(2006), 3453–3466.
 8. Y. Ou and K. H. Rhee, A keydependent secure image hashing scheme by using Radon transform, In: Proc. of the IEEE International Symposium on Intelligent Signal Processing and Communication Systems, pp.595–598, 2009.
 9. Z. Tang, S. Wang, X. P. Zhang, et al., Structural featurebased image hashing and similarity metric for tampering detection, Fundam. Inf., 106(2011), 75–91.
 10. C. Qin, C. C. Chang and P. L. Tsou, Robust image hashing using nonuniform sampling in discrete Fourier domain, Digit. Signal Process., 23(2013), 578–585.
 11. Z. Tang, X. Q. Zhang, L. Huang, et al., Robust image hashing using ringbased entropies, Signal Process., 93(2013), 2061–2069.
 12. Z. Tang, Y. Dai, X. Q. Zhang, et al., Robust image hashing via colour vector angles and discrete wavelet transform, IET Image Process., 8(2014), 142–149.
 13. L. Ghouti, Robust perceptual color image hashing using quaternion singular value decomposition, In: Proc. of IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP 2014), pp.3794–3798, 2014.
 14. C. Yan, C. Pun and X. Yuan, Quaternionbased image hashing for adaptive tampering localization, IEEE Trans. Inf. Foren. Secur., 11(2016), 2664–2677.
 15. C. Qin, X. Chen, J. Dong, et al., Perceptual image hashing with selective sampling for salient structure features, Displays, 45(2016), 26–37.
 16. Z. Tang, X. Q. Zhang, X. Li, et al., Robust image hashing with ring partition and invariant vector distance, IEEE Trans. Inf. Foren. Secur., 11(2016), 200–214.
 17. R. K. Karsh, R. H. Laskar and B. B. Richhariya, Robust image hashing using ring partitionPGNMF and local features, SpringerPlus, 5(2016), 1–20.
 18. R. K. Karsh, R. H. Laskar and Aditi, Robust image hashing through DWTSVD and spectral residual method, EURASIP J. Image Vide., 2017(2017), 1–17.
 19. R. Davarzani, S. Mozaffariand and K. Yaghmaie, Perceptual image hashing using centersymmetric local binary patterns, Multimed. Tools Appl., 75(2016), 4639–4667.
 20. X. Huang, X. Liu, G. Wang, et al., A robust image hashing with enhanced randomness by using random walk on zigzag blocking, In: Proc. IEEE Trustcom/BigDataSE/ISPA, pp.23–26, 2016.
 21. R. K. Karsh, A. Saikia and R. H. Laskar, Image authentication based on robust image hashing with geometric correction, Multimed. Tools Appl., 77(2018), 25409–25429.
 22. C. Qin, M. Sun and C.C. Chang, Perceptual hashing for color images based on hybrid extraction of structural features, Signal Process., 142(2018), 194–205.
 23. Z. Tang, Z. Huang, H. Yao, et al., Perceptual image hashing with weighted DWT features for reducedreference image quality assessment, Comput. J., 61 (2018), 1695–1709.
 24. L. Itti, C. Koch and E. Niebur, A model of saliency based visual attention for rapid scene analysis, IEEE Trans. Patt. Anal. Mac. Intell., 20(1998), 1254–1259.
 25. D. Walther and C. Koch, Modeling attention to salient protoobjects, Neural Networks, 19(2006), 1395–1407.
 26. X. Hou and L. Zhang, Saliency detection: A spectral residual approach, In: Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.1–8, 2007.
 27. C. Guo, Q. Ma and L. Zhang, Spatiotemporal saliency detection using phase spectrum of quaternion Fourier transform, In: Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.1–8, 2008.
 28. Z. Tang, X. Q. Zhang and S. Zhang, Robust perceptual image hashing based on ring partition and NMF, IEEE Trans. Knowl. Data En., 26(2014), 711–724.
 29. Z. Tang, L. Huang, X. Q. Zhang, et al., Robust image hashing based on color vector angle and canny operator, AEÜInt. J. Electron. Commun., 70(2016), 833–841.
 30. Kodak Lossless True Color Image Suite. Available online: http://r0k.us/graphics/kodak/.
 31. F. A. P. Petitcolas, Watermarking schemes evaluation, IEEE Signal Process. Mag., 17(2000), 58–64.
 32. Z. Wang, A. C. Bovik, H. R. Sheikh, et al., Image quality assessment: from error visibility to structural similarity, IEEE Trans. Image Process., 13(2004), 600–612.
 33. Ground Truth Database. Available online: http://www.cs.washington.edu/research/imagedatabase/groundtruth/.
 34. T. Fawcett, An introduction to ROC analysis, Patt. Recog. Lett., 27(2006), 861–874.
 35. IEEE Std754–2008, IEEE Standard for FloatingPoint Arithmetic, pp.1–70, 2008.
 36. G. Schaefer and M. Stich, UCIDan uncompressed color image database, Proc. SPIE, Storage and Retrieval Methods and Applications for Multimedia, pp.472–480, 2004.
Reader Comments
© 2019 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)
Associated material
Metrics
Other articles by authors
Related pages
Tools
your name: * your email: *