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E-book: Digital Imaging for Cultural Heritage Preservation: Analysis, Restoration, and Reconstruction of Ancient Artworks

Edited by (University of Catania, Italy), Edited by (University of Catania, Italy), Edited by (University of Catania, Italy)
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"Preface Paintings, frescos, antique photographic prints, incunabulas, old books, handwritten documents, sculptures, ceramic fragments and other ancient manufacts constitute the elements of an extremely valuable and immense historical patrimony. Their digitalization opens up the possibility to use various image processing and analysis and Computer Graphics techniques to preserve this Cultural Heritage for future generations. Digital imaging solutions can be used to generate virtually restored versions ofthe original artworks to be presented in online museums and/or for further development of historical studies. Application of various feature extraction and image data analysis techniques is useful to address problems of authorship and artwork style categorization in the history of arts. Three-dimensional reconstruction of ancient artworks or entire archeological sites allows the creation of multidimensional models that incorporate information coming from excavations, archaeological knowhow and heterogeneous historical sources. Pioneer work in this area has sprung from the close, but too often occasional, cooperation of scientists with historians and archaeologists"--

"This edition presents the most prominent topics and applications of digital image processing, analysis, and computer graphics in the field of cultural heritage preservation. The text assumes prior knowledge of digital image processing and computer graphics fundamentals. Each chapter contains a table of contents, illustrations, and figures that elucidate the presented concepts in detail, as well as a chapter summary and a bibliography for further reading. Well-known experts cover a wide range of topics and related applications, including spectral imaging, automated restoration, computational reconstruction, digital reproduction, and 3D models"--

Provided by publisher.
Preface vii
Editors xi
Contributors xiii
1 Experiencing the Past: Computer Graphics in Archaeology
1(36)
Filippo Stanco
Davide Tanasi
1.1 The Past and the Future: Archaeology and Computer Science
1(1)
1.2 From the Field to the Screen: 3D Computer Graphics and the Archaeological Heritage
2(2)
1.2.1 3D Computer Graphics and the Archaeological Fieldwork
2(1)
1.2.2 Monitoring the Heritage
3(1)
1.2.3 The Virtual Museum
3(1)
1.2.4 3D Modeling as a Cognitive Tool
4(1)
1.3 The Archeomatica Project
4(1)
1.4 Archaeological 3D Modeling
5(1)
1.5 Haghia Triada, Crete
6(8)
1.5.1 Propylon
8(1)
1.5.2 House of the Razed Rooms
9(1)
1.5.3 VAP House
10(4)
1.6 Polizzello Mountain, Sicily
14(4)
1.6.1 Buildings A, B, C, D, E
14(3)
1.6.2 Temenos and Room III
17(1)
1.6.3 Precinct F, East House, Temenos House
17(1)
1.6.4 The Virtual Acropolis and the Multilayered 3D Model
18(1)
1.7 Digital Restoration
18(8)
1.7.1 Minoan Model
21(1)
1.7.2 Asclepius
21(3)
1.7.3 Female Torso
24(1)
1.7.4 Hellenistic Thysia
25(1)
1.8 Dealing with Image Data in Archaeology: New Perspectives
26(11)
Acknowledgments
28(1)
Bibliography
28(9)
2 Using Digital 3D Models for Study and Restoration of Cultural Heritage Artifacts
37(32)
Matteo Dellepiane
Marco Callieri
Massimiliano Corsini
Roberto Scopigno
2.1 Introduction
37(1)
2.2 Visual Communication of Art
38(5)
2.2.1 Computer-Generated Animations
39(1)
2.2.2 Interactive Visualization
40(2)
2.2.3 Geographic Web Browsers Deploying 3D Models
42(1)
2.3 Art Catalogs and Digital Repositories
43(1)
2.4 Digital 3D as a Tool for Art Scholars
43(6)
2.4.1 Using 3D Scanning to Analyze an Attribution Proposal
44(3)
2.4.2 The CENOBIUM Project: An Integrated Visual Comparison of Historiated Capitals
47(1)
2.4.3 Classifying and Archiving Carved Faces: The Bayon Digital Archival Project
48(1)
2.5 Physical Reproduction from the Digital Model
49(1)
2.6 Virtual Reconstruction and Reassembly
50(5)
2.6.1 Virtual Reconstruction
50(2)
2.6.2 Virtual Reassembly
52(2)
2.6.3 Virtual Repainting
54(1)
2.7 Supporting the Restoration Process
55(8)
2.7.1 Tools for Investigation and Diagnostics
56(3)
2.7.2 Tools Supporting Knowledge Management
59(4)
2.8 Conclusions
63(6)
Acknowledgments
63(1)
Bibliography
63(6)
3 Processing Sampled 3D Data: Reconstruction and Visualization Technologies
69(32)
Marco Callieri
Matteo Dellepiane
Paolo Cignoni
Roberto Scopigno
3.1 Introduction
69(3)
3.1.1 Sources of Sampled 3D Data
70(2)
3.2 Basic Geometric Processing of Scanned Data
72(7)
3.2.1 The 3D Scanning Pipeline
73(3)
3.2.2 Implementing Range Maps Alignment as an Automatic Process
76(2)
3.2.3 Enhancing Incomplete Surface Sampling
78(1)
3.3 Color Sampling and Processing
79(6)
3.3.1 Basic Acquisition of Color Data
80(1)
3.3.2 Recovering Camera Parameters
80(2)
3.3.3 Mapping Complex Photographic Detail on 3D Models
82(1)
3.3.4 Advanced Color Data Acquisition: Sampling Surface Reflection Properties
83(2)
3.4 MeshLab: An Open Source Tool for Processing 3D Scanned Data
85(2)
3.5 Efficient Visualization and Management of Sampled 3D Data
87(4)
3.5.1 Simplification and Mulfiresolution Management of Huge Models
87(1)
3.5.2 Mesh-Based versus Point-Based Encoding and Rendering
88(1)
3.5.3 Usability of Virtual Heritage Worlds
89(1)
3.5.4 Not Just 3D Data: Adding Other Knowledge
90(1)
3.5.5 Presenting 3D Data on the Web
90(1)
3.6 3D Digitization: How to Improve Current Procedures and Make It More Practical and Successful
91(2)
3.6.1 Technology -- Limitations Perceived by Practitioners
91(1)
3.6.2 Misuse of Technology
91(1)
3.6.3 Better Management of 3D Data
92(1)
3.7 Conclusions
93(8)
Acknowledgments
93(1)
Bibliography
94(7)
4 ARC3D: A Public Web Service That Turns Photos into 3D Models
101(26)
David Tingdahl
Maarten Vergauwen
Luc Van Gool
4.1 Introduction
102(1)
4.2 System Overview
102(5)
4.2.1 System Components
103(1)
4.2.2 Upload Tool
103(3)
4.2.3 Modelviewer Tool
106(1)
4.3 Automatic Reconstruction Pipeline
107(2)
4.3.1 Pipeline Overview
107(2)
4.3.2 Opportunistic Pipeline
109(1)
4.3.3 Hierarchical Pipeline
109(1)
4.3.4 Parallel Pipeline
109(1)
4.4 Practical Guidelines for Shooting Images
109(3)
4.4.1 Introduction
109(1)
4.4.2 Image Shooting
110(2)
4.4.3 Scene Selection
112(1)
4.5 Case Study: Reconstruction of the Mogao Caves of Dunhuang
112(7)
4.5.1 3D Reconstruction of Mogao Cave 322
113(2)
4.5.2 Image Capturing
115(3)
4.5.3 Result
118(1)
4.6 Examples
119(6)
4.6.1 A Complete Building: Arc de Triomphe
119(1)
4.6.2 Environment Scene
119(1)
4.6.3 Further Examples
119(6)
4.7 Conclusions
125(2)
Acknowledgments
125(1)
Bibliography
125(2)
5 Accurate and Detailed Image-Based 3D Documentation of Large Sites and Complex Objects
127(32)
Fabio Remondino
5.1 Introduction
127(1)
5.2 Reality-Based 3D Modeling
128(4)
5.2.1 Techniques and Methodologies
129(1)
5.2.2 Multi-Sensor and Multi-Source Data Integration
130(1)
5.2.3 Standards in Digital 3D Documentation
131(1)
5.3 Photogrammetry
132(16)
5.3.1 Image Data Acquisition
134(1)
5.3.2 Camera Calibration and Image Orientation
135(5)
5.3.3 3D Measurements
140(3)
5.3.4 Structuring and Modeling
143(2)
5.3.5 Texturing and Visualization
145(1)
5.3.6 Main Applications and Actual Problems
146(2)
5.4 Conclusions
148(11)
Acknowledgments
149(1)
Bibliography
149(10)
6 Digitizing the Parthenon: Estimating Surface Reflectance under Measured Natural Illumination
159(24)
Paul Debevec
Chris Tchou
Andrew Gardner
Tim Hawkins
Chans Poullis
Jessi Stumpfel
Andrew Jones
Nathaniel Yun
Per Einarsson
Therese Lundgren
Marcos Fajardo
Philippe Martinez
6.1 Introduction
159(2)
6.2 Background and Related Work
161(1)
6.3 Data Acquisiton and Calibration
162(10)
6.3.1 Camera Calibration
162(1)
6.3.2 BRDF Measurement and Modeling
163(3)
6.3.3 Natural Illumination Capture
166(4)
6.3.4 3D Scanning
170(1)
6.3.5 Photograph Acquisition and Alignment
171(1)
6.4 Reflectometry
172(4)
6.4.1 General Algorithm
172(1)
6.4.2 Multiresolution Reflectance Solving
173(3)
6.5 Results
176(1)
6.6 Discussion and Future Work
177(2)
6.7 Conclusion
179(4)
Acknowledgments
179(1)
Bibliography
180(3)
7 Applications of Spectral Imaging and Reproduction to Cultural Heritage
183(32)
Simone Bianco
Alessandro Colombo
Francesca Gasparini
Raimondo Schettini
Silvia Zuffi
7.1 Introduction
183(1)
7.2 Colorimetric and Multispectral Color Imaging
184(1)
7.3 Capturing a Multispectral Image
185(3)
7.4 Imaging and Signal Processing Techniques
188(6)
7.4.1 "Narrow-Band" Multispectral Imaging
188(1)
7.4.2 "Wide-Band" Multispectral Imaging
189(2)
7.4.3 Training Set Selection
191(1)
7.4.4 Filters Selection
192(2)
7.5 Recovery Multispectral Information from RGB Images
194(2)
7.5.1 Spectral Based Color Imaging Using RGB Digital Still Cameras
194(2)
7.6 Storing a Multispectral Image
196(2)
7.7 Evaluating System Performance
198(1)
7.8 Multispectral Image Reproduction
198(4)
7.8.1 Colorimetric Reproduction
198(1)
7.8.2 Spectral Characterization
199(1)
7.8.3 Spectral Reproduction
200(1)
7.8.4 Viewpoint and Lighting Position Invariant Reproduction
201(1)
7.9 Final Remarks
202(13)
Bibliography
203(12)
8 Did Early Renaissance Painters Trace Optically Projected Images? The Conclusion of Independent Scientists, Art Historians, and Artists
215(28)
David G. Stork
Jacob Collins
Marco Duarte
Yasuo Furuichi
Dave Kale
Ashutosh Kulkarni
M. Dirk Robinson
Sara J. Schechner
Christopher W. Tyler
Nicholas C. Williams
8.1 Introduction
216(1)
8.2 The Projection Theory
217(5)
8.2.1 Philosophical and Logical Foundations of the Projection Theory
217(5)
8.3 Image Evidence
222(10)
8.3.1 Background
222(1)
8.3.2 Lorenzo Lotto, Husband and Wife (1543)
223(1)
8.3.3 Jan van Eyck, Portrait of Giovanni Arnolfini and His Wife (1434)
224(2)
8.3.4 Jan van Eyck, Portrait of Niccolo Albergati (1431 and 1432)
226(2)
8.3.5 Robert Campin, The Merode Altarpiece (1430)
228(1)
8.3.6 Georges de la Tour, Christ in the Carpenter's Studio (1645)
228(1)
8.3.7 Caravaggio, The Calling of St. Matthew (1599--1600)
229(1)
8.3.8 Hans Memling, Flower Still-Life (c. 1490)
230(1)
8.3.9 Hans Holbein, The Ambassadors (1533)
230(1)
8.3.10 Hans Holbein, Georg Gisze (1532)
231(1)
8.4 Documentary Evidence
232(1)
8.5 Material Culture and Re-Enactments
233(2)
8.5.1 Re-Enactments
234(1)
8.6 Non-Optical Contexts
235(1)
8.7 The "Value" in Tracing
235(1)
8.8 Scholarly Consensus
236(1)
8.9 Conclusions
237(6)
Acknowledgments
237(1)
Bibliography
238(5)
9 A Computer Analysis of the Mirror in Hans Memling's Virgin and Child and Maarten van Nieuwenhove
243(20)
Silvio Savarese
David G. Stork
Andrey Del Pozo
Ron Spronk
9.1 Introduction
243(3)
9.2 Memling's Diptych
246(2)
9.3 Computer Vision Analysis
248(3)
9.4 Modeling Reflections Off a Mirror Surface
251(5)
9.4.1 Direct Map
253(1)
9.4.2 Inverse Map
253(1)
9.4.3 Experimental Validation
253(3)
9.5 Results
256(1)
9.6 Conclusions
256(7)
Acknowledgments
258(1)
Bibliography
258(5)
10 Virtual Restoration of Antique Books and Photographs
263(36)
Filippo Stanco
Alfredo Restrepo Palacios
Giovanni Ramponi
10.1 Introduction
263(4)
10.1.1 Photographic Prints
264(2)
10.1.2 Antique Books
266(1)
10.2 Detection of the Defects
267(7)
10.2.1 Foxing
267(1)
10.2.2 Water Blotches
268(1)
10.2.3 Cracks
269(5)
10.2.4 Fragmented Glass Support
274(1)
10.3 Virtual Restoration of Antique Photographic Prints Affected by Foxing and Water Blotches
274(3)
10.3.1 Inpainting
275(1)
10.3.2 Additive/Multiplicative Model
275(1)
10.3.3 Interpolation
276(1)
10.4 Restoration of the Fragmented Glass Plate Photographs
277(3)
10.5 Restoration of Yellowing and Foxing in Antique Books
280(7)
10.5.1 Foxing
281(2)
10.5.2 Page Enhancement
283(1)
10.5.3 OCR in Antique Documents
284(3)
10.6 On Image Quality
287(7)
10.6.1 On the Measurement of Local Luminance and Local Contrast (Statistics of Location and Dispersion)
287(1)
10.6.2 On the Relationship between Local Contrast and Local Luminance
288(3)
10.6.3 Effect of γ-Correction on Scatter Plots of Local Contrast versus Local Luminance
291(1)
10.6.4 Word Descriptors
292(2)
10.7 Conclusions
294(5)
Acknowledgments
294(1)
Bibliography
295(4)
11 Advances in Automated Restoration of Archived Video
299(24)
Anil Kokaram
Francois Pitie
David Corrigan
Domenico Vitulano
Vittoria Bruni
Andrew Crawford
11.1 Dirt and Missing Data
301(5)
11.1.1 Simple Detection
301(1)
11.1.2 Better Modeling
302(2)
11.1.3 Further Refinement
304(2)
11.2 Semi-Transparent Defects
306(4)
11.2.1 Reconstruction
308(2)
11.3 Line Scratches
310(3)
11.4 Global Defects
313(4)
11.4.1 Modeling
316(1)
11.5 An Evolving Industry
317(6)
Bibliography
318(5)
12 Computational Analysis of Archaeological Ceramic Vessels and Their Fragments
323(30)
Andrew R. Willis
12.1 Introduction
323(4)
12.1.1 Significance of Generic Artifact Reconstruction
324(1)
12.1.2 Significance of Ceramic Vessel Reconstruction
325(1)
12.1.3 Traditional Puzzle Solving and Artifact Reconstruction
325(2)
12.2 Artifact Reconstruction Systems: Basic Components and Concepts
327(6)
12.2.1 Digitizing Artifacts
328(1)
12.2.2 Approaches for Computational Sherd Analysis
328(2)
12.2.3 Computerized Typology for Automated Sherd Classification
330(2)
12.2.4 Computerized Vessel Reconstruction by Fragment Matching
332(1)
12.3 Computational Models for Vessels and Their Fragments
333(7)
12.3.1 Modeling Ceramic Vessels as Surfaces of Revolution
333(1)
12.3.2 Estimating the Vessel Axis from Digitized Sherds
334(1)
12.3.3 Estimating Profile Curves from Digitized Sherds
335(3)
12.3.4 Simultaneously Solving for the Axis and Profile Curve
338(1)
12.3.5 Dealing with Asymmetries in Archaeological Ceramic Sherds
338(2)
12.3.6 Vessel Reconstruction by Matching Axis/Profile Curve Models
340(1)
12.4 Vessel Reconstruction by Sherd Matching: 3D Puzzle Solving
340(5)
12.4.1 The Bayesian Formulation
341(3)
12.4.2 Searching for the Solution
344(1)
12.5 Current Trends in Computational Artifact Reconstruction
345(8)
12.5.1 Going beyond Geometry: Textures and Patterns on Sherd Surfaces
345(2)
12.5.2 Discussion and Future Work
347(1)
12.5.3 Conclusion
348(1)
Acknowledgments
348(1)
Bibliography
348(5)
13 Digital Reconstruction and Mosaicing of Cultural Artifacts
353(32)
Efthymia Tsamoura
Nikos Nikolaidis
Ioannis Pitas
13.1 Introduction
353(3)
13.2 The Three-Step Object Reconstruction Procedure
356(6)
13.2.1 Fragment Preprocessing
360(1)
13.2.2 Matching of Candidate Adjacent Fragments
361(1)
13.2.3 Multi-Fragment Merging
361(1)
13.3 Approaches for Object Reconstruction
362(4)
13.3.1 Torn by Hand Document Reassembly
362(1)
13.3.2 3D Objects Reconstruction
362(3)
13.3.3 2D Puzzles Reassembly
365(1)
13.3.4 2D Objects Reassembly
366(1)
13.4 Automatic Color-Based Reassembly of Fragmented Images and Paintings
366(6)
13.4.1 Discovery of Adjacent Image Fragments
367(1)
13.4.2 Discovery of Matching Contour Segments of Adjacent Image Fragments
367(2)
13.4.3 Contour Alignment of Fragments
369(1)
13.4.4 Overall Image Reassembly
370(1)
13.4.5 Image Reassembly Experiments
371(1)
13.5 Reduced Complexity Image Mosaicing Utilizing Spanning Trees
372(8)
13.5.1 Two-Image Mosaicing
374(1)
13.5.2 Spanning Tree Mosaicing
375(1)
13.5.3 Sub-Graph Spanning Tree Mosaicing
376(1)
13.5.4 Experimental Evaluation
377(3)
13.6 Conclusions
380(5)
Bibliography
381(4)
14 Analysis of Ancient Mosaic Images for Dedicated Applications
385(24)
Lamia Benyoussef
Stephane Derrode
14.1 Introduction
385(4)
14.1.1 Some Historical Facts about Mosaics
386(1)
14.1.2 Mosaics, Images, and Digital Applications
387(2)
14.2 Recent Image-Processing Projects Concerned with Mosaics
389(3)
14.2.1 St. Vitus Cathedral Mosaic Restoration
389(2)
14.2.2 Arabo-Moresque and Islamic Mosaic Pattern Classification
391(1)
14.2.3 Roman Mosaics Indexation
391(1)
14.3 Tesserae Extraction
392(4)
14.4 Tessera-Based Segmentation and Coding
396(4)
14.4.1 Segmentation of Ancient Mosaic Images
396(1)
14.4.2 Tessera-Based Coding and Lossy Compression
396(4)
14.5 Guidelines Estimation for Mosaic Structure Retrieval
400(4)
14.6 Open Issues and Research Directions in Mosaic Image Analysis
404(5)
Bibliography
405(4)
15 Digital Reproduction of Ancient Mosaics
409(20)
Sebastiano Battiato
Giovanni Gallo
Giovanni Puglisi
Gianpiero Di Blasi
15.1 Art and Computer Graphics
409(2)
15.2 History of Ancient Mosaics
411(1)
15.3 The Digital Mosaic Problem
411(2)
15.4 The Crystallization Mosaics
413(1)
15.5 The Ancient Mosaics
414(6)
15.6 The Ancient Mosaics in a 3D Environment
420(1)
15.7 Final Discussions
420(9)
15.7.1 Final Summary
426(1)
Bibliography
426(3)
16 Pattern Discovery from Eroded Rock Art
429(22)
Yang Cai
16.1 Introduction
429(1)
16.2 Surface Imaging Methods
430(8)
16.2.1 Laser Scan
431(2)
16.2.2 Pattern Projection
433(1)
16.2.3 Stick Shadow
433(2)
16.2.4 Multiview Imaging
435(1)
16.2.5 Polynomial Texture Maps (PTM)
436(2)
16.3 Pattern Discovery Methods
438(7)
16.3.1 Simulated Lighting
438(1)
16.3.2 Data Transformation
438(3)
16.3.3 Transformation Examples
441(1)
16.3.4 Off-Line Handwriting Recognition
441(3)
16.3.5 Interactive versus Automatic Discovery
444(1)
16.4 From Reconstruction to Knowledge
445(1)
16.5 Interaction Design
445(1)
16.6 Conclusions
446(5)
Acknowledgments
447(1)
Bibliography
447(4)
17 Copyright Protection of Digital Images of Cultural Heritage
451(32)
Vito Cappellini
Roberto Caldelli
Andrea Del Mastio
Francesca Uccheddu
17.1 Introduction
452(4)
17.1.1 A Brief History of Watermarking
452(1)
17.1.2 Watermarking Basics
452(2)
17.1.3 Watermarking Application Scenarios
454(2)
17.2 2D Watermarking
456(10)
17.2.1 Capacity
458(1)
17.2.2 Insertion of Multiple Watermarking Codes
458(1)
17.2.3 Robustness
458(2)
17.2.4 Blind and Non-Blind Techniques
460(1)
17.2.5 Private and Public Techniques
460(1)
17.2.6 Readable and Detectable Watermarks
460(1)
17.2.7 Invertibility and Quasi-Invertibility
461(1)
17.2.8 Reversibility
462(1)
17.2.9 Asymmetry
462(1)
17.2.10 Examples
463(3)
17.3 3D Watermarking
466(11)
17.3.1 Requirements
466(3)
17.3.2 3D Objects Representation
469(2)
17.3.3 State of the Art
471(6)
17.4 Conclusions
477(6)
Bibliography
478(5)
Index 483
Filippo Stanco, Sebastiano Battiato, and Giovanni Gallo are with the University of Catania, Italy.