Writer identification and verification:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Berlin
Akad. Verl.-Ges. Aka
2008
|
| Schriftenreihe: | Dissertationen zur künstlichen Intelligenz (DISKI)
311 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Zugl.: Bern, Univ., Diss., 2007 |
| Beschreibung: | XI, 144 S. Ill., graph. Darst. |
| ISBN: | 9783898383110 9781586038250 |
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| adam_text | Titel: Writer identification and verification
Autor: Schlapbach, Andreas
Jahr: 2008
Contents
Writer Identification and Verification 1
1.1 Introduction.............................. 1
1.2 Writer Identification ......................... 2
1.3 Writer Verification........................... 3
1.4 Applications.............................. 4
1.5 Contribution and Outline ...................... 6
Related Work 9
2.1 Writer Identification and Verification................ 9
2.1.1 Off-line Writer Identification and Verification....... 10
2.1.2 On-line Writer Identification and Verification....... 12
2.2 Signature Identification and Verification.............. 13
2.2.1 Off-line Signature Verification................ 14
2.2.2 On-line Signature Verification................ 16
2.3 Remarks................................ 18
Off-line Writer Identification and Verification 21
3.1 Introduction.............................. 21
3.2 IAM Handwriting Database..................... 23
3.3 Text Normalisation.......................... 26
3.4 Feature Set............................... 28
3.5 Modelling............................... 29
3.5.1 Hidden Markov Models................... 30
3.5.2 Gaussian Mixture Models.................. 33
3.6 Confidence Measures......................... 35
3.6.1 Confidence Measures for Writer Identification...... 36
3.6.2 Confidence Measures for Writer Verification....... 37
Evaluation of the Two Systems 39
4.1 HMM-based Writer Identification and Verification System ... 39
4.2 GMM-based Writer Identification and Verification System ... 41
4.3 Experimental Setup.......................... 43
4.4 Results................................. 46
4.4.1 Writer Identification Results................. 46
4.4.2 Writer Verification Results.................. 54
4.5 Discussion............................... 61
4.6 Future Work.............................. 61
Improving a Writer Identification System 63
5.1 Introduction.............................. 63
5.2 System Overview........................... 65
5.2.1 Text Normalisation...................... 65
5.2.2 Feature Set........................... 66
5.2.3 Classifier............................ 69
5.3 Feature Selection Algorithms.................... 70
5.3.1 Feature Set Search Algorithms ............... 70
5.3.2 Genetic Algorithms...................... 71
5.3.3 Feature Set Transformation Algorithms.......... 72
5.4 Experimental Setup.......................... 73
5.5 Results................................. 74
5.6 Discussion............................... 76
5.7 Future Work.............................. 76
Writer Identification for On-line Whiteboard Data 79
6.1 Introduction.............................. 79
6.2 IAM On-line Handwriting Database................ 81
6.3 System Overview........................... 82
6.4 Text Normalisation.......................... 83
6.5 Feature Sets for Whiteboard Writer Identification......... 87
6.5.1 Point-based Feature Set................... 87
6.5.2 Stroke-based Feature Set................... 88
6.5.3 Extended Point-based Feature Set ............. 89
6.5.4 Point-based Off-line Feature Set .............. 91
6.5.5 All Point-based Feature Set................. 92
6.6 Fusion of Asynchronous Streams of Features........... 92
6.7 Model Training............................ 94
7 Evaluation of the Whiteboard Writer Identification System 97
7.1 Writer Identification Task ...................... 97
7.2 Evaluation of Feature Sets...................... 98
7.2.1 Experimental Setup...................... 98
7.2.2 Results............................. 100
7.2.3 Discussion........................... 102
7.3 Evaluation of Training Methods................... 102
7.3.1 Experimental Setup...................... 102
7.3.2 Results............................. 104
7.3.3 Discussion........................... 104
7.4 Evaluation of Reducing Training Data............... 104
7.4.1 Experimental Setup...................... 104
7.4.2 Results............................. 105
7.4.3 Discussion........................... 106
7.5 Evaluation of Fusing Asynchronous Streams of Features .... 106
7.5.1 Experimental Setup...................... 106
7.5.2 Results............................. 107
7.5.3 Discussion........................... 110
7.6 Overall Discussion.......................... 110
7.7 Future Work.............................. Ill
8 Conclusions and Future Work 113
List of Figures 119
List of Tables 123
Bibliography 125
Index 142
|
| adam_txt |
Titel: Writer identification and verification
Autor: Schlapbach, Andreas
Jahr: 2008
Contents
Writer Identification and Verification 1
1.1 Introduction. 1
1.2 Writer Identification . 2
1.3 Writer Verification. 3
1.4 Applications. 4
1.5 Contribution and Outline . 6
Related Work 9
2.1 Writer Identification and Verification. 9
2.1.1 Off-line Writer Identification and Verification. 10
2.1.2 On-line Writer Identification and Verification. 12
2.2 Signature Identification and Verification. 13
2.2.1 Off-line Signature Verification. 14
2.2.2 On-line Signature Verification. 16
2.3 Remarks. 18
Off-line Writer Identification and Verification 21
3.1 Introduction. 21
3.2 IAM Handwriting Database. 23
3.3 Text Normalisation. 26
3.4 Feature Set. 28
3.5 Modelling. 29
3.5.1 Hidden Markov Models. 30
3.5.2 Gaussian Mixture Models. 33
3.6 Confidence Measures. 35
3.6.1 Confidence Measures for Writer Identification. 36
3.6.2 Confidence Measures for Writer Verification. 37
Evaluation of the Two Systems 39
4.1 HMM-based Writer Identification and Verification System . 39
4.2 GMM-based Writer Identification and Verification System . 41
4.3 Experimental Setup. 43
4.4 Results. 46
4.4.1 Writer Identification Results. 46
4.4.2 Writer Verification Results. 54
4.5 Discussion. 61
4.6 Future Work. 61
Improving a Writer Identification System 63
5.1 Introduction. 63
5.2 System Overview. 65
5.2.1 Text Normalisation. 65
5.2.2 Feature Set. 66
5.2.3 Classifier. 69
5.3 Feature Selection Algorithms. 70
5.3.1 Feature Set Search Algorithms . 70
5.3.2 Genetic Algorithms. 71
5.3.3 Feature Set Transformation Algorithms. 72
5.4 Experimental Setup. 73
5.5 Results. 74
5.6 Discussion. 76
5.7 Future Work. 76
Writer Identification for On-line Whiteboard Data 79
6.1 Introduction. 79
6.2 IAM On-line Handwriting Database. 81
6.3 System Overview. 82
6.4 Text Normalisation. 83
6.5 Feature Sets for Whiteboard Writer Identification. 87
6.5.1 Point-based Feature Set. 87
6.5.2 Stroke-based Feature Set. 88
6.5.3 Extended Point-based Feature Set . 89
6.5.4 Point-based Off-line Feature Set . 91
6.5.5 All Point-based Feature Set. 92
6.6 Fusion of Asynchronous Streams of Features. 92
6.7 Model Training. 94
7 Evaluation of the Whiteboard Writer Identification System 97
7.1 Writer Identification Task . 97
7.2 Evaluation of Feature Sets. 98
7.2.1 Experimental Setup. 98
7.2.2 Results. 100
7.2.3 Discussion. 102
7.3 Evaluation of Training Methods. 102
7.3.1 Experimental Setup. 102
7.3.2 Results. 104
7.3.3 Discussion. 104
7.4 Evaluation of Reducing Training Data. 104
7.4.1 Experimental Setup. 104
7.4.2 Results. 105
7.4.3 Discussion. 106
7.5 Evaluation of Fusing Asynchronous Streams of Features . 106
7.5.1 Experimental Setup. 106
7.5.2 Results. 107
7.5.3 Discussion. 110
7.6 Overall Discussion. 110
7.7 Future Work. Ill
8 Conclusions and Future Work 113
List of Figures 119
List of Tables 123
Bibliography 125
Index 142 |
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| title | Writer identification and verification |
| title_auth | Writer identification and verification |
| title_exact_search | Writer identification and verification |
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| title_full | Writer identification and verification Andreas Schlapbach |
| title_fullStr | Writer identification and verification Andreas Schlapbach |
| title_full_unstemmed | Writer identification and verification Andreas Schlapbach |
| title_short | Writer identification and verification |
| title_sort | writer identification and verification |
| topic | Computer vision Graphology Writing Identification Verifikation (DE-588)4135577-5 gnd Handschrift Grafologie (DE-588)4113845-4 gnd Identifikation (DE-588)4072712-9 gnd Whiteboard (DE-588)4567558-2 gnd Hidden-Markov-Modell (DE-588)4352479-5 gnd Mustererkennung (DE-588)4040936-3 gnd Schreiber (DE-588)4130947-9 gnd |
| topic_facet | Computer vision Graphology Writing Identification Verifikation Handschrift Grafologie Identifikation Whiteboard Hidden-Markov-Modell Mustererkennung Schreiber Hochschulschrift |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016318422&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV005345280 |
| work_keys_str_mv | AT schlapbachandreas writeridentificationandverification |