| Paper Details: | Downloads: 523 |
| Serial Number: | P1151123630
|
| Title: | Block Level Entropy Thresholding For High Volume Image Adaptive Data Hiding
|
| Authors: | Mansi Subhedar and Gajanan Birajdar
|
| Abstract: | Digital image steganography is the art of hiding data in other digital images in such a way that it is imperceptible to human observer. The significant aspects of steganographic system are the stego image quality and capacity of data hiding. In the proposed algorithm, high volume data hiding is achieved by taking the JPEG image into account, as JPEG is the most popular file format in digital images. In the first approach, after dividing cover image into 8X8 non overlapping blocks, DCT is computed and based on Entropy Threshold (ET) scheme, these blocks are selected for information embedding decision. Second approach performs same processing steps by dividing the cover image into 16X16 non overlapping blocks. After data embedding, the quality of resulting stego image is analysed using various metrics like PSNR (Peak Signal to Noise Ratio), RMSE (Root Mean Square Error), SNR (Signal to Noise Ratio) and MSSIM (Mean Structural Similarity Index). It is evident from the simulation results that stego object with minimum distortion is obtained while maintaining the high capacity of data embedding using the second approach.
|
| Keywords: | Steganography, JPEG, Data hiding, Entropy thresholding, DCT, MSSIM
|
| Journal/Conference: | International Journal of Graphics, Vision and Image Processing
|
| Volume: | 11
|
| Issue: | 3
|
| Submission Date: | 6/8/2011 12:00:00 AM
|
| Review Date: | 6/23/2011 12:00:00 AM
|
| Publishing Date: | 7/9/2011 12:00:00 AM
|
| Article Downloads: | 523
|
| Download: |
|