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Message digests for photographic images and video contents
First Edition
Edited by Similar
New multimedia database search tools require rapidity, compression, image quality and copyright control. The two latter are often covered by embedding a hidden watermark signal in the multimedia content. More effective and recognized multimedia search methods are using hash functions. Hash functions compute very short signatures characteristically very different from one media to another. Typical requirement of hash functions are: easily computable, provide short output bit length, and collision resistant.
In this thesis, an image hashing method for multimedia contents is presented as an innovative solution for content identification and indexing. This new one-way function for images extract some image features by different computations along radial projections. The magnitude of change is related to the amount of the change of the media (image, video). In watermarking, hashing enables the creation of payloads that depend on the media content, and which are thus resistant to the "copy attack" and collusion.
This thesis is available in the SIMILAR collection under the label « Presses universitaires de Louvain » (ISBN 2-930344-58-X) and may be purchased online at www.i6doc.com.
In this thesis, an image hashing method for multimedia contents is presented as an innovative solution for content identification and indexing. This new one-way function for images extract some image features by different computations along radial projections. The magnitude of change is related to the amount of the change of the media (image, video). In watermarking, hashing enables the creation of payloads that depend on the media content, and which are thus resistant to the "copy attack" and collusion.
This thesis is available in the SIMILAR collection under the label « Presses universitaires de Louvain » (ISBN 2-930344-58-X) and may be purchased online at www.i6doc.com.
Paperback
- In English
9.40 €
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- Publisher
- Presses universitaires de Louvain
- Title Part
-
Numéro 1
- Author
- Frédéric Lefèbvre,
- Edited by
- Similar,
- Collection
- SIMILAR | n° 1
- Language
- English
- Publisher Category
- Applied Sciences > Computer Science > Networks and telecommunications
- Publisher Category
- Applied Sciences > Electricity
- Publisher Category
- Applied Sciences
- BISAC Subject Heading
- COM000000 COMPUTERS
- Onix Audience Codes
- 06 Professional and scholarly
- CLIL (Version 2013-2019)
- 3238 Réseaux et Télécommunications
- Title First Published
- 2004
- Type of Work
- Thesis
Paperback
- Publication Date
- 01 January 2004
- ISBN-13
- 9782930344584
- Extent
- Main content page count : 124
- Code
- 70212
- Dimensions
- 16 x 24 x 0.7 cm
- Weight
- 216 grams
- List Price
- 9.40 €
- ONIX XML
- Version 2.1, Version 3
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Contents
Introduction 1
1 Image and content security: Overview 7
1.1 Digital Signature Standard . . . . . . . . . . . . . . . . . . . . 8
1.1.1 DSA-ECDSA . . . . . . . . . . . . . . . . . . . . . . . 9
1.1.2 Hash function, one-way function . . . . . . . . . . . . 9
1.2 Image hashing . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
1.2.1 Overview of our contribution . . . . . . . . . . . . . . 12
1.2.2 Related works . . . . . . . . . . . . . . . . . . . . . . . 13
1.3 Watermarking . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
1.3.1 The psychovisual mask . . . . . . . . . . . . . . . . . 16
1.3.2 The watermarking pattern . . . . . . . . . . . . . . . . 16
1.3.3 The synchronized block . . . . . . . . . . . . . . . . . 17
1.3.4 Related work in content-based watermarking design 18
2 Authentication and Geometrical Attacks Detection for Image Signature 23
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.2 Radon Transform . . . . . . . . . . . . . . . . . . . . . . . . . 25
2.2.1 Continuous Radon transform . . . . . . . . . . . . . . 26
2.2.2 Discrete Radon transform . . . . . . . . . . . . . . . . 28
2.3 Radon Soft Hash Function . . . . . . . . . . . . . . . . . . . . 30
2.3.1 Points extraction . . . . . . . . . . . . . . . . . . . . . 30
2.3.2 Features extraction algorithm . . . . . . . . . . . . . . 33
2.3.3 Geometrical deformation detection . . . . . . . . . . . 34
2.3.4 Detection and experiments . . . . . . . . . . . . . . . 35
2.4 Message digest for digital signature . . . . . . . . . . . . . . 37
2.4.1 Normalized RASH . . . . . . . . . . . . . . . . . . . . 37
2.4.2 Final message digest . . . . . . . . . . . . . . . . . . . 38
2.4.3 Detection . . . . . . . . . . . . . . . . . . . . . . . . . . 39
2.5 The theoretical threshold computation . . . . . . . . . . . . . 42
2.5.1 Working hypothesis . . . . . . . . . . . . . . . . . . . 43
2.5.2 Estimator model . . . . . . . . . . . . . . . . . . . . . 43
2.5.3 Estimator Efficiency . . . . . . . . . . . . . . . . . . . 45
2.5.4 Confidence interval . . . . . . . . . . . . . . . . . . . . 47
2.5.5 Theoretical optimal threshold . . . . . . . . . . . . . . 49
2.6 Radon Transform and Principal Component Analysis . . . . 53
2.6.1 Description . . . . . . . . . . . . . . . . . . . . . . . . 53
2.6.2 Experiments . . . . . . . . . . . . . . . . . . . . . . . . 59
2.6.3 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . 60
3 A video digest based on the robust hashing of representative frames 63
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
3.2 Image robust hashing . . . . . . . . . . . . . . . . . . . . . . 64
3.2.1 Robust image digest based on radial projections . . . 65
3.2.2 Visual hash experimental validation . . . . . . . . . . 68
3.3 Extension to video hashing . . . . . . . . . . . . . . . . . . . 73
3.3.1 From ‰image hash‰ to ‰video hash‰: the notion of representative frames . . . . . 74
3.3.2 Representative frames . . . . . . . . . . . . . . . . . . 75
3.3.3 Video hash experimental validation . . . . . . . . . . 82
3.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
4 An advanced architecture for movie Digital Right Management 93
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
4.1.1 Acces Control context . . . . . . . . . . . . . . . . . . 94
4.1.2 Fingerprinting context . . . . . . . . . . . . . . . . . . 96
4.1.3 Screen distortion and temporal distortion context . . 98
4.2 Watermarking . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
4.2.1 Description of the light algorithm . . . . . . . . . . . 101
4.2.2 Watermarking detection performance . . . . . . . . . 106
4.2.3 Hardware implementation . . . . . . . . . . . . . . . 108
4.3 Digital signature real time process . . . . . . . . . . . . . . . 111
4.3.1 Hardware implementations . . . . . . . . . . . . . . . 112
4.3.2 Efficient implementation of a serial-parallel architecture . . . . 114
4.4 Fingerprinting/video digest for movie authentication and tracking . . . . . . . 116
5 Conclusions and perspectives 119
A Publications 123