DocumentCode :
517353
Title :
A Self-Synchronized Image Hash Algorithm
Author :
Wu, Di ; Niu, Xiamu
Author_Institution :
Shenzhen Grad. Sch., Harbin Inst. of Technol., Shenzhen, China
Volume :
1
fYear :
2010
fDate :
12-14 April 2010
Firstpage :
13
Lastpage :
15
Abstract :
Image searching and authentication have become important issues for the digital world. Image hashing technique has been proposed to meet them. In this paper, a self-synchronized image hashing algorithm resistant to rotation is presented. In the algorithm, the features of the image are extracted by Scale Invariant Feature Transform(SIFT) algorithm. Then a cyclic matrix are generated from the features. Thus, the rotation is translated into the elementary transformation of the matrix. At last, the hash value is calculated by the eigenvalue decomposition. Because the eigenvalues are invariant to the elementary transformation, the rotation is compensated. Thus this algorithm is very robust to rotation attack. Benefited from the efficient image representation capability of SIFT, the robustness and discrimination of proposed method are improved. The experimental results prove that the proposed method is robust to the simple attacks.
Keywords :
cryptography; eigenvalues and eigenfunctions; feature extraction; image representation; matrix decomposition; transforms; cyclic matrix; eigenvalue decomposition; elementary matrix transformation; feature extraction; image authentication; image representation; image searching; scale invariant feature transform algorithm; self-synchronized image hashing algorithm; Authentication; Computer science; Cryptography; Eigenvalues and eigenfunctions; Image edge detection; Matrix decomposition; Mobile communication; Mobile computing; Robustness; Shape;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications and Mobile Computing (CMC), 2010 International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4244-6327-5
Electronic_ISBN :
978-1-4244-6328-2
Type :
conf
DOI :
10.1109/CMC.2010.233
Filename :
5471395
Link To Document :
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