DocumentCode :
3230518
Title :
Noise removal using Cohen-Grossberg neural network for improving the quality of the decrypted image in color encryption
Author :
Liu, Yanling ; Zhang, Jianxiong ; Tang, Wansheng
Author_Institution :
Inst. of Syst. Eng., Tianjin Univ., Tianjin, China
fYear :
2011
fDate :
27-29 May 2011
Firstpage :
25
Lastpage :
29
Abstract :
In this paper, a color image encryption method is proposed with the removal of noise generated during the transmission based on Cohen-Grossberg neural networks, where the color image is expressed in terms of the standard red-green-blue (RGB) space, and the corresponding pixel matrix is hidden by Arnold transform (AT). The Cohen-Grossberg neural network is added to store the hidden message as the stable equilibria, which achieves the noise removal. The hidden message without noise is recovered by performing AT with accurate iteration numbers. Experimental results show that the proposed method achieves effective resistance against transmission noise.
Keywords :
cryptography; image colour analysis; image denoising; image resolution; message authentication; transforms; Arnold transform; Cohen-Grossberg neural network; color image encryption; decrypted image; hidden message; noise removal; pixel matrix; red-green-blue space; stable equilibria; transmission noise; Cryptography; Arnold transform; Cohen-Grossberg neural network; Color image encryption; Noise removal;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communication Software and Networks (ICCSN), 2011 IEEE 3rd International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-61284-485-5
Type :
conf
DOI :
10.1109/ICCSN.2011.6014210
Filename :
6014210
Link To Document :
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