Steganography using Bit Plane Complexity Segmentation and Artificial Neural Network
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Abstract
Steganography is a technique to hide information in some other vessel data without leaving any apparent evidence of vessel data alteration. There are different techniques for steganography namely substitution technique, transform domain technique, spread spectrum technique, statistical method, distortion technique and cover generation technique. The three characteristics which are taken care of are:- capacity, undetectibility and imperceptibility.
Multilayer neural network is used to achieve image compression. The input pixels are used as target values and the hidden layer output is the compressed image.
Our proposed technique uses an image as the vessel data and embeds a secret image that is compressed by artificial neural network in the bit-planes of the vessel image without deteriorating image quality. This technique makes use of the characteristics of the human vision system whereby a human cannot perceive any change in the information in a very complicated binary pattern. Its information hiding capacity can be made large.
Multilayer neural network is used to achieve image compression. The input pixels are used as target values and the hidden layer output is the compressed image.
Our proposed technique uses an image as the vessel data and embeds a secret image that is compressed by artificial neural network in the bit-planes of the vessel image without deteriorating image quality. This technique makes use of the characteristics of the human vision system whereby a human cannot perceive any change in the information in a very complicated binary pattern. Its information hiding capacity can be made large.
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