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Performance Evaluation of DCT and DWT Features for Blind Image Steganalysis using Neural Networks
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 114 - Number 5 |
| Year of Publication: 2015 |
| Authors: Manisha Saini, Rita Chhikara |
10.5120/19974-1868
|
Manisha Saini, Rita Chhikara . Performance Evaluation of DCT and DWT Features for Blind Image Steganalysis using Neural Networks. International Journal of Computer Applications. 114, 5 ( March 2015), 20-23. DOI=10.5120/19974-1868
Abstract
In this paper, we are comparing 72 DWT feature set with 274 DCT feature set on the basis of parameters MSE (Mean square error), Accuracy and time for Blind Image Steganalysis. Dataset is created consisting of cover images and stego images, which are obtained by using two steganography tools steghide and outguess. Extracted features are then fed to Neural network Back propagation classifier, to compare the performance. Experimental results show that DCT feature set has higher performance as compared to DWT feature set.
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