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# LSB Matching Revisited - PowerPoint PPT Presentation

LSB Matching Revisited. Source: IEEE Signal Processing Letters (Accepted for future publication) Authors: Jarno Mielikainen Speaker: Chia-Chun Wu ( 吳佳駿 ) Date: 2006/03/13. Outline. Introduction LSB replacement The proposed scheme Experimental results Conclusions Comments.

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### LSB Matching Revisited

Source: IEEE Signal Processing Letters (Accepted for future publication)

Authors: Jarno Mielikainen

Speaker: Chia-Chun Wu (吳佳駿)

Date: 2006/03/13

• Introduction

• LSB replacement

• The proposed scheme

• Experimental results

• Conclusions

Introduction

• Steganographic

Stego image

Cover image

Secret message: 01011001110…

xi

xi+1

mi

mi+1

yi

yi+1

f (161, 150) = 0

f (163, 150) = 1

f (162, 150) = 1

f (162, 150) = 1

f (162, 151) = 0

The proposed scheme

• Modified version of the LSB method

• Binary function f (l, n)

Property 1:

Property 2:

Embedding algorithm for a pair of pixels.

Case 1: embedding “0”, “0”

10100010

10010111

0

0

162

151

yi

yi+1

mi

mi+1

Case 2: embedding “0”, “1”

162

150

0

1

10100010

10010110

yi

yi+1

mi

mi+1

Embedding messages (1/3)

xi

xi+1

Case 3: embedding “1”, “0”

xi

xi+1

mi+1

mi

yi

yi+1

f (163, 150) = 1

f (161, 150) = 0

Case 4: embedding “1”, “1”

xi

xi+1

mi

mi+1

yi

yi+1

f (163, 150) = 1

f (161, 150) = 0

xi

xi+1

• 1000 JPEG images

• All size 384×256

• HCF COM detectors

The center of mass (COM) of the histogram characteristic

function (HCF) introduced by Harmsen et al. [4]

Ker [5] proposed using the adjacency histogram instead of the usual histogram.

The x-axis has been scaled to focus on a region of interest.

ROC curves for the calibrated