臺灣博碩士論文加值系統

For the surveillance, home security and medical applications a digital watermarking scheme is needed to provide full correlation which is trivial in the normal techniques when any attack is predicted to occur. The correlation of decoded data varies according to the variations of length of the embedding data for the type of attack predicted. We believe that proper selection of length for the embedding data for any watermarking system can assure full correlation. In this thesis, we propose a framework which adds a preprocessor and a splitter for any regular watermark scheme at the embedder and a combiner at the decoder. A length boundary database is constructed with the congregation of various lookup tables which contain the maximum length values for various types of attacks predicted. In the framework, the preprocessor obtains the maximum length for the type of attack predicted from the length boundary database and checks this length with that of the embedding data. If the embedding data length is more than the maximum length obtained, the splitter divides it into pieces of data each of length equal to that of the maximum length chosen. The embedding data is thus embedded with the acceptable length to obtain full correlation.

TABLE OF CONTENTS
Page
No.

Abstract I
Acknowledgment II
Table of Contents III
List of Figures V
List of Table VI

CHAPTER 1


Introduction 1
1. 1. Background 1
1. 2. Motivation 3
1. 3. Synopsis 4

CHAPTER 2
Related Work 5

CHAPTER 3
Proposed Framework 9
3. 1. Objective 9
3. 2. Design Concepts 10
3. 3. Components 12
3. 3. 1. Sender 12
3. 3. 2. Receiver 15
3. 4. Length Boundary Database 15

CHAPTER 4
Implementation 18
4. 1. Software module 18
4. 2. Sender program 19
4.3 Receiver program 21

CHAPTER 5
Construction of Length Boundary Database 23
5. 1. Lookup tables for Different Attacks 23
5. 1. 1. JPEG compression Attack 23
5. 1. 2. Mosaic Attack 25
5. 1. 3. Noise Addition Attack 26
5. 1. 4. Permutation Attack 27
5. 1. 5. Generalized lookup table for Lena.pgm 28
5. 2. Example Length Boundary Database 29

CHAPTER 6
Case Study 37
CHAPTER 7
Conclusions and Future Work 40
Reference 41

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