Optimal Dual Watermarking of Color Images with SWT and SVD Through Genetic Algorithm

Author(s):  
P. Sivananthamaitrey ◽  
P. Rajesh Kumar
2015 ◽  
Author(s):  
P. Sneha Latha ◽  
Pawan Kumar ◽  
Samruddhi Kahu ◽  
Kishor M. Bhurchandi

Author(s):  
Sudipta Kr Ghosal ◽  
Jyotsna Kumar Mandal

In this chapter, a fragile watermarking scheme based on One-Dimensional Discrete Hartley Transform (1D-DHT) has been proposed to verify the authenticity of color images. One-Dimensional Discrete Hartley Transform (1D-DHT) converts each 1 x 2 sub-matrix of pixel components into transform domain. Watermark (along with a message digest MD) bits are embedded into the transformed components in varying proportion. To minimize the quality distortion, genetic algorithm (GA) based optimization is applied which yields the optimized component corresponding to each embedded component. Applying One-Dimensional Inverse Discrete Hartley Transform (1D-IDHT) on 1 x 2 sub-matrices of embedded components re-generates the pixel components in spatial domain. The reverse approach is followed by the recipient to retrieve back the watermark (along with the message digest MD) which in turn is compared against the re-computed Message Digest (MD') for authentication. Simulation results demonstrate that the proposed technique offers variable payload and less distortion as compared to existing schemes.


Author(s):  
Sourav De ◽  
Siddhartha Bhattacharyya ◽  
Susanta Chakraborty

The proposed chapter is intended to propose a self supervised image segmentation method by a multi-objective genetic algorithm based optimized MUSIG (OptiMUSIG) activation function with a multilayer self organizing neural network architecture to segment multilevel gray scale intensity images. The multiobjective genetic algorithm based parallel version of the OptiMUSIG (ParaOptiMUSIG) activation function with a parallel self organizing neural network architecture is also discussed to segment true color images. These methods are quite efficient enough to overcome the drawbacks of the single objective based OptiMUSIG and ParaOptiMUSIG activation functions to segment gray scale and true color images, respectively. The proposed multiobjective genetic algorithm based optimization methods are applied on three standard objective functions to measure the quality of the segmented images. These functions form the multiple objective criteria of the multiobjective genetic algorithm based image segmentation method.


2015 ◽  
Vol 719-720 ◽  
pp. 1140-1147 ◽  
Author(s):  
G. Lokeshwari ◽  
S. Udaya Kumar ◽  
Sree Vidya Susarla

The proliferation of digitized media due to rapid growth of network multimedia systems has created an urgent need for information security due to the ever increasing unauthorized manipulation and reproduction of original digital data. In this paper an approach based on Merkle-Hellman, ElGamal and Genetic algorithms is proposed for data encryption and decryption. The strength of the cipher is increased further by using genetic algorithm. Experimental results show that the proposed approach can be implemented on images of any size which retain the quality of the image while retrieving the original image. This aspect helps in providing the reduction in block size without compromise in the quality of the image and security as well.


2017 ◽  
Vol 77 (11) ◽  
pp. 13047-13074 ◽  
Author(s):  
Kevin Rangel-Espinoza ◽  
Eduardo Fragoso-Navarro ◽  
Clara Cruz-Ramos ◽  
Rogelio Reyes-Reyes ◽  
Mariko Nakano-Miyatake ◽  
...  

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