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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 11/2019

19.07.2018 | Original Article

Color image encryption approach based on memetic differential evolution

verfasst von: Manjit Kaur, Vijay Kumar, Li Li

Erschienen in: Neural Computing and Applications | Ausgabe 11/2019

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Abstract

In this paper, the initial conditions of an intertwining logistic map are generated by utilizing the memetic differential evolution. Initially, the color image is decomposed into red, green, and blue channels. Arnold map is used to shuffle the pixels position of all three channels to develop the shuffled channels. Afterward, memetic differential evolution is implemented to optimize the parameters required by intertwining logistic map. The correlation coefficient and entropy are used as a fitness function. The intertwining map generates the secret keys to encrypt the shuffled color channels. The encrypted color channels are combined to obtain the encrypted image. Extensive experiments are carried out by considering the memetic differential evolution-based image encryption and existing competitive image encryption approaches over five benchmark images. Experimental results show that the proposed approach provides higher efficiency and security as compared to the existing image encryption approaches.
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Metadaten
Titel
Color image encryption approach based on memetic differential evolution
verfasst von
Manjit Kaur
Vijay Kumar
Li Li
Publikationsdatum
19.07.2018
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 11/2019
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-018-3642-7

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