| Histogram-based image hashing scheme robust against geometric deformations |
| Full text |
Pdf
(585 KB)
|
Source
|
International Multimedia Conference
archive
Proceedings of the 9th workshop on Multimedia & security
table of contents
Dallas, Texas, USA
SESSION: Hashing
table of contents
Pages: 121 - 128
Year of Publication: 2007
ISBN:978-1-59593-857-2
|
|
Authors
|
|
| Sponsors |
|
| Publisher |
|
| Bibliometrics |
Downloads (6 Weeks): 10, Downloads (12 Months): 167, Citation Count: 0
|
|
|
ABSTRACT
In this paper, we propose a robust image hash algorithm by using the invariance of the image histogram shape to geometric deformations. Robustness and uniqueness of the proposed hash function are investigated in detail by representing the histogram shape as the relative relations in the number of pixels among groups of two different bins. It is found from extensive testing that the histogram-based hash function has a satisfactory performance to various geometric deformations, and is also robust to most common signal processing operations thanks to the use of Gaussian kernel low-pass filter in the preprocessing phase.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
| |
1
|
EURASIP 2007 Special Issue: Robust perceptual hashing of multimedia content. M. K. Mihçak, O. Koval, S. Voloshynovskiy. Available at: {http://www.hindawi.com/journals/is/si/rph.html}
|
| |
2
|
|
| |
3
|
|
| |
4
|
|
| |
5
|
B. Coskun, B. Sankur, N. Memon. Spatio-temporal transform based video hashing. IEEE Transactions on Multimedia, 8(6):1190--1208, Dec. 2006.
|
| |
6
|
|
| |
7
|
R. Venkatesan, S. M. Koon, M. H. Jakubowski, and P. Moulin. Robust image hashing. In IEEE International Conference Image Processing, pages 664--666, Vancouver, BC, Canada, Sep. 2000.
|
| |
8
|
C. S. Lu, S. W. Sun, and P. C. Chang. Robust mesh-based content-dependent image watermarking with resistance to both geometric attack and watermark-estimation attack. In SPIE: Security, Steganography, and Watermarking of Multimedia, pages 147--163, San Jose, CA, USA, Jan. 2005.
|
| |
9
|
|
| |
10
|
A. Swaminathan, Y. Mao, and M. Wu. Image hashing resilient to geometric and filtering operations. In IEEE Workshop on Multimedia Signal Processing, Siena, Italy, Sep. 2004.
|
| |
11
|
C. S. Lu and C. Y. Hsu. Geometric distortion-resilient image hashing scheme and its applications on copy detection and authentication. Multimedia System, 11(2):159--173, 2005.
|
| |
12
|
A. Swaminathan, Y. Mao, and M. Wu. Robust and secure image hashing. IEEE Transactions on Information Forensics and Security, 1(2):215--230, June 2006.
|
| |
13
|
|
| |
14
|
S. Xiang, J. Huang, and R. Yang. Time-scale invariant audio watermarking based on the statistical features in time domain. In Information Hiding workshop, volume 4437 of LNCS, pages 93--108, Old Town Alexandria, Virginia, USA, July 2006.
|
| |
15
|
|
| |
16
|
|
| |
17
|
A. Olmos and F. A. A. Kingdom. (2004) McGill Calibrated Colour Image Database. Available at: {http://tabby.vision.mcgill.ca}
|
| |
18
|
Standard test image-Wikipedia, the free encyclopedia. Available at: {http://en.wikipedia.org/wiki/Standard test image}
|
| |
19
|
Wacha07 Special Issue: What kind of security does perceptual hashing offer? Available at: {http://wacha07.irisa.fr/Wacha07-call.pdf}
|
| |
20
|
R. Radhakrishnan, Z. Y. Xiong, and N. Memon. On the security of the visual hash function. Journal of Electronic Imaging, 14(1), 013011, 2005.
|
|