High Impact Factor : 4.396 icon | Submit Manuscript Online icon |

Efficient And Improved Video Steganography using DCT and Neural Network


Fozia .R .Khan , Noble Group of Institution, Junagadh, Gujarat, India; Prof. Sujata Anandwani , 2Assistant Professor


Video Steganography, least significant bit, discrete cosine transform, neural network


As per the demand of modern communication it is important to establish secret communication which is obtain by seganography .Video Steganography is the technique of hiding some covert message inside a video. The addition of this information to the video is not recognizable through the human eye as modify of a pixel color is negligible. In the proposed method Discrete Cosine Transform (DCT) and neural network is used. Input image is divided into blocks and is processed to generate quantization matrix of cover and stego images by using Discrete Cosine Transform (DCT).And using neural network performance of this method can be further improved. The neural network is trained and on the basis of training and segmentation done, neural network provide efficient positions where data can be merge. The performance and efficiency is measured by PSNR and MSE value.

Other Details

Paper ID: IJSRDV3I100347
Published in: Volume : 3, Issue : 10
Publication Date: 01/01/2016
Page(s): 432-437

Article Preview

Download Article