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E-raamat: Document Analysis And Text Recognition: Benchmarking State-of-the-art Systems

Edited by (Technische Univ Braunschweig, Germany), Edited by (Univ Of Salford, Uk), Edited by (Indian Statistical Inst, India)
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Document Analysis And Text Recognition: Benchmarking State-of-the-art SystemsSuurem pilt
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The compendium presents the latest results of the most prominent competitions held in the field of Document Analysis and Text Recognition. It includes a description of the participating systems and the underlying methods on one hand and the datasets used together with evaluation metrics on the other hand. This volume also demonstrates with examples, how to organize a competition and how to make it successful. It will be an indispensable handbook to the document image analysis community.
Foreword v
About the Editors ix
List of Contributors
xiii
Introduction xxi
Part I Logical Structure and Segmentation
1(64)
Chapter 1 Logical Structure Extraction from Digitized Books
3(26)
Antoine Doucet
1.1 Introduction
3(5)
1.2 Book Collection
8(2)
1.3 Setting Up the Competition
10(11)
1.4 Related Publications
21(1)
1.5 Conclusions and Perspectives
22(7)
References
24(5)
Chapter 2 Handwriting Segmentation
29(36)
Nikolaos Stamatopoulos
Georgios Louloudis
Basilis Gatos
2.1 Introduction
29(1)
2.2 General Approaches
30(2)
2.3 Methods Participating in the Competitions
32(10)
2.4 Recently Published Methods Using the Competition Data Sets
42(3)
2.5 Benchmarking Data Sets
45(5)
2.6 Evaluation Methodology
50(2)
2.7 Evaluation Results: Discussion
52(8)
2.8 Conclusions
60(5)
References
61(4)
Part II Digits and Mathematical Expressions
65(54)
Chapter 3 Handwritten Digit and Digit String Recognition
67(22)
Markus Diem
Stefan Fiel
Florian Kleber
3.1 Introduction
67(1)
3.2 Digit and Digit String Data Sets
68(4)
3.3 General Approaches for Digit and Digit String Recognition
72(3)
3.4 Approaches Submitted to the Competitions
75(4)
3.5 Competition Results
79(7)
3.6 Conclusions
86(3)
References
87(2)
Chapter 4 Handwritten Mathematical Expressions
89(30)
Harold Mouchere
Christian Viard-Gaudin
Richard Zanibi
Utpal Garain
4.1 Introduction
89(2)
4.2 Description of Data Set
91(6)
4.3 Evaluation Methodology
97(5)
4.4 Overview of Participant Strategies
102(3)
4.5 Description of Approaches Submitted to Competition
105(3)
4.6 Detailed Results from CROHME 2014
108(5)
4.7 Conclusions and Recommendations
113(6)
References
114(5)
Part III Writer Identification and Signature Verification
119(92)
Chapter 5 Writer Identification
121(34)
Georgios Louloudis
Nikolaos Stamatopoulos
Basilis Gatos
5.1 Introduction
121(1)
5.2 General Approaches
122(1)
5.3 Methods Participating to the Competitions
123(6)
5.4 Recently Published Methods Using the Competition Datasets
129(3)
5.5 Benchmarking Datasets
132(5)
5.6 Evaluation Methodology
137(1)
5.7 Evaluation Results
137(13)
5.8 Conclusions
150(5)
References
151(4)
Chapter 6 Arabic Writer Identification Using AHTID/MW and KHATT Database
155(22)
Fouad Slimane
Sameh Awaida
6.1 Introduction
155(1)
6.2 Related Work
156(3)
6.3 Databases Used
159(3)
6.4 Competition Using the AHTID and KHATT Databases
162(2)
6.5 Evaluated Systems
164(6)
6.6 Evaluation
170(2)
6.7 Conclusions and Recommendations
172(5)
Acknowledgments
173(1)
References
173(4)
Chapter 7 Signature Verification: Recent Developments and Perspectives
177(34)
Muhammad Imran Malik
Sheraz Ahmed
Andreas Dengel
Marcus Liwicki
7.1 Introduction
177(4)
7.2 Signature Verification Competition (SigComp2009)
181(2)
7.3 Forensic Signature Verification Competition (4NSigComp2010)
183(2)
7.4 Signature Verification Competition (SigComp2011)
185(3)
7.5 Forensic Signature Verification Competition (4NSigComp2012)
188(3)
7.6 Signature Verification and Writer Identification Competitions (SigWiComp2013)
191(5)
7.7 Signature Verification and Writer Identification Competition (SigWiComp2015)
196(5)
7.8 Discussions and Future Perspectives
201(10)
References
204(7)
Part IV Text Recognition
211(64)
Chapter 8 Handwritten Text Recognition Competitions With the tranScriptorium Dataset
213(28)
Joan Andrea Sanchez
Veronica Romero
Alejandro H. Toselli
Enrique Vidal
8.1 Introduction
213(2)
8.2 The Bentham Datasets Used in the HTR Contests
215(6)
8.3 Contest Protocol and Evaluation Methodology
221(3)
8.4 Existing State-of-the-Art Approaches
224(4)
8.5 HTR Approaches Employed in the Contests
228(4)
8.6 Presentation and Analysis of HTR Contest Results
232(4)
8.7 Remarks and Conclusions
236(5)
References
236(5)
Chapter 9 Multifont and Multisize Low-resolution Arabic Text Recognition Using APTI Database
241(34)
Fouad Slimane
Christine Vanoirbeek
9.1 Introduction
241(1)
9.2 The APTI Database
242(3)
9.3 Organized Competitions Using APTI Database
245(2)
9.4 Text Recognition Systems Evaluated with APTI
247(10)
9.5 Text Segmentation Systems Evaluated with APTI
257(1)
9.6 Font-identification Systems Evaluated with APTI
257(2)
9.7 Evaluation
259(11)
9.8 Conclusions and Recommendations
270(5)
References
271(4)
Index 275
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