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Arabic and Chinese handwriting recognition : SACH 2006 summit, College Park, MD, USA, September 27-28, 2006 : selected papers / / David Doermann, Stefan Jaeger (eds.)
| Arabic and Chinese handwriting recognition : SACH 2006 summit, College Park, MD, USA, September 27-28, 2006 : selected papers / / David Doermann, Stefan Jaeger (eds.) |
| Edizione | [1st ed. 2008.] |
| Pubbl/distr/stampa | Berlin, Germany ; ; New York, New York : , : Springer, , [2008] |
| Descrizione fisica | 1 online resource (VIII, 279 p.) |
| Disciplina | 006.424 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical character recognition devices
Chinese language - Writing - Data processing Writing, Arabic - Data processing |
| ISBN | 3-540-78199-4 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Visual Recognition of Arabic Handwriting: Challenges and New Directions -- A Review on Persian Script and Recognition Techniques -- Human Reading Based Strategies for Off-Line Arabic Word Recognition -- Versatile Search of Scanned Arabic Handwriting -- A Two-Tier Arabic Offline Handwriting Recognition Based on Conditional Joining Rules -- Databases and Competitions: Strategies to Improve Arabic Recognition Systems -- Handwritten Chinese Character Recognition: Effects of Shape Normalization and Feature Extraction -- How to Deal with Uncertainty and Variability: Experience and Solutions -- An Efficient Candidate Set Size Reduction Method for Coarse-Classification in Chinese Handwriting Recognition -- Techniques for Solving the Large-Scale Classification Problem in Chinese Handwriting Recognition -- Recent Results of Online Japanese Handwriting Recognition and Its Applications -- Segmentation-Driven Offline Handwritten Chinese and Arabic Script Recognition -- Multi-character Field Recognition for Arabic and Chinese Handwriting -- Multi-lingual Offline Handwriting Recognition Using Hidden Markov Models: A Script-Independent Approach -- Handwritten Character Recognition of Popular South Indian Scripts -- Ensemble Methods to Improve the Performance of an English Handwritten Text Line Recognizer. |
| Record Nr. | UNISA-996466074503316 |
| Berlin, Germany ; ; New York, New York : , : Springer, , [2008] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Arabic and Chinese handwriting recognition : SACH 2006 summit, College Park, MD, USA, September 27-28, 2006 : selected papers / / David Doermann, Stefan Jaeger (eds.)
| Arabic and Chinese handwriting recognition : SACH 2006 summit, College Park, MD, USA, September 27-28, 2006 : selected papers / / David Doermann, Stefan Jaeger (eds.) |
| Edizione | [1st ed. 2008.] |
| Pubbl/distr/stampa | Berlin, Germany ; ; New York, New York : , : Springer, , [2008] |
| Descrizione fisica | 1 online resource (VIII, 279 p.) |
| Disciplina | 006.424 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical character recognition devices
Chinese language - Writing - Data processing Writing, Arabic - Data processing |
| ISBN | 3-540-78199-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Visual Recognition of Arabic Handwriting: Challenges and New Directions -- A Review on Persian Script and Recognition Techniques -- Human Reading Based Strategies for Off-Line Arabic Word Recognition -- Versatile Search of Scanned Arabic Handwriting -- A Two-Tier Arabic Offline Handwriting Recognition Based on Conditional Joining Rules -- Databases and Competitions: Strategies to Improve Arabic Recognition Systems -- Handwritten Chinese Character Recognition: Effects of Shape Normalization and Feature Extraction -- How to Deal with Uncertainty and Variability: Experience and Solutions -- An Efficient Candidate Set Size Reduction Method for Coarse-Classification in Chinese Handwriting Recognition -- Techniques for Solving the Large-Scale Classification Problem in Chinese Handwriting Recognition -- Recent Results of Online Japanese Handwriting Recognition and Its Applications -- Segmentation-Driven Offline Handwritten Chinese and Arabic Script Recognition -- Multi-character Field Recognition for Arabic and Chinese Handwriting -- Multi-lingual Offline Handwriting Recognition Using Hidden Markov Models: A Script-Independent Approach -- Handwritten Character Recognition of Popular South Indian Scripts -- Ensemble Methods to Improve the Performance of an English Handwritten Text Line Recognizer. |
| Record Nr. | UNINA-9910483791603321 |
| Berlin, Germany ; ; New York, New York : , : Springer, , [2008] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Character recognition systems [[electronic resource] ] : a guide for students and practioners / / Mohamed Cheriet ... [et al.]
| Character recognition systems [[electronic resource] ] : a guide for students and practioners / / Mohamed Cheriet ... [et al.] |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2007 |
| Descrizione fisica | 1 online resource (360 p.) |
| Disciplina |
006.4/24
006.424 |
| Altri autori (Persone) | CherietM (Mohamed) |
| Soggetto topico | Optical character recognition devices |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-281-13472-4
9786611134723 0-470-17653-9 0-470-17652-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
CHARACTER RECOGNITION SYSTEMS; CONTENTS; Preface; Acknowledgments; List of Figures; List of Tables; Acronyms; 1 Introduction: Character Recognition, Evolution, and Development; 1.1 Generation and Recognition of Characters; 1.2 History of OCR; 1.3 Development of New Techniques; 1.4 Recent Trends and Movements; 1.5 Organization of the Remaining Chapters; References; 2 Tools for Image Preprocessing; 2.1 Generic Form-Processing System; 2.2 A Stroke Model for Complex Background Elimination; 2.2.1 Global Gray Level Thresholding; 2.2.2 Local Gray Level Thresholding
2.2.3 Local Feature Thresholding-Stroke-Based Model2.2.4 Choosing the Most Efficient Character Extraction Method; 2.2.5 Cleaning Up Form Items Using Stroke-Based Model; 2.3 A Scale-Space Approach for Visual Data Extraction; 2.3.1 Image Regularization; 2.3.2 Data Extraction; 2.3.3 Concluding Remarks; 2.4 Data Preprocessing; 2.4.1 Smoothing and Noise Removal; 2.4.2 Skew Detection and Correction; 2.4.3 Slant Correction; 2.4.4 Character Normalization; 2.4.5 Contour Tracing/Analysis; 2.4.6 Thinning; 2.5 Chapter Summary; References; 3 Feature Extraction, Selection, and Creation 3.1 Feature Extraction3.1.1 Moments; 3.1.2 Histogram; 3.1.3 Direction Features; 3.1.4 Image Registration; 3.1.5 Hough Transform; 3.1.6 Line-Based Representation; 3.1.7 Fourier Descriptors; 3.1.8 Shape Approximation; 3.1.9 Topological Features; 3.1.10 Linear Transforms; 3.1.11 Kernels; 3.2 Feature Selection for Pattern Classification; 3.2.1 Review of Feature Selection Methods; 3.3 Feature Creation for Pattern Classification; 3.3.1 Categories of Feature Creation; 3.3.2 Review of Feature Creation Methods; 3.3.3 Future Trends; 3.4 Chapter Summary; References; 4 Pattern Classification Methods 4.1 Overview of Classification Methods4.2 Statistical Methods; 4.2.1 Bayes Decision Theory; 4.2.2 Parametric Methods; 4.2.3 Nonparametric Methods; 4.3 Artificial Neural Networks; 4.3.1 Single-Layer Neural Network; 4.3.2 Multilayer Perceptron; 4.3.3 Radial Basis Function Network; 4.3.4 Polynomial Network; 4.3.5 Unsupervised Learning; 4.3.6 Learning Vector Quantization; 4.4 Support Vector Machines; 4.4.1 Maximal Margin Classifier; 4.4.2 Soft Margin and Kernels; 4.4.3 Implementation Issues; 4.5 Structural Pattern Recognition; 4.5.1 Attributed String Matching; 4.5.2 Attributed Graph Matching 4.6 Combining Multiple Classifiers4.6.1 Problem Formulation; 4.6.2 Combining Discrete Outputs; 4.6.3 Combining Continuous Outputs; 4.6.4 Dynamic Classifier Selection; 4.6.5 Ensemble Generation; 4.7 A Concrete Example; 4.8 Chapter Summary; References; 5 Word and String Recognition; 5.1 Introduction; 5.2 Character Segmentation; 5.2.1 Overview of Dissection Techniques; 5.2.2 Segmentation of Handwritten Digits; 5.3 Classification-Based String Recognition; 5.3.1 String Classification Model; 5.3.2 Classifier Design for String Recognition; 5.3.3 Search Strategies 5.3.4 Strategies for Large Vocabulary |
| Record Nr. | UNINA-9910145585503321 |
| Hoboken, N.J., : Wiley-Interscience, c2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Character recognition systems [[electronic resource] ] : a guide for students and practioners / / Mohamed Cheriet ... [et al.]
| Character recognition systems [[electronic resource] ] : a guide for students and practioners / / Mohamed Cheriet ... [et al.] |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2007 |
| Descrizione fisica | 1 online resource (360 p.) |
| Disciplina |
006.4/24
006.424 |
| Altri autori (Persone) | CherietM (Mohamed) |
| Soggetto topico | Optical character recognition devices |
| ISBN |
1-281-13472-4
9786611134723 0-470-17653-9 0-470-17652-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
CHARACTER RECOGNITION SYSTEMS; CONTENTS; Preface; Acknowledgments; List of Figures; List of Tables; Acronyms; 1 Introduction: Character Recognition, Evolution, and Development; 1.1 Generation and Recognition of Characters; 1.2 History of OCR; 1.3 Development of New Techniques; 1.4 Recent Trends and Movements; 1.5 Organization of the Remaining Chapters; References; 2 Tools for Image Preprocessing; 2.1 Generic Form-Processing System; 2.2 A Stroke Model for Complex Background Elimination; 2.2.1 Global Gray Level Thresholding; 2.2.2 Local Gray Level Thresholding
2.2.3 Local Feature Thresholding-Stroke-Based Model2.2.4 Choosing the Most Efficient Character Extraction Method; 2.2.5 Cleaning Up Form Items Using Stroke-Based Model; 2.3 A Scale-Space Approach for Visual Data Extraction; 2.3.1 Image Regularization; 2.3.2 Data Extraction; 2.3.3 Concluding Remarks; 2.4 Data Preprocessing; 2.4.1 Smoothing and Noise Removal; 2.4.2 Skew Detection and Correction; 2.4.3 Slant Correction; 2.4.4 Character Normalization; 2.4.5 Contour Tracing/Analysis; 2.4.6 Thinning; 2.5 Chapter Summary; References; 3 Feature Extraction, Selection, and Creation 3.1 Feature Extraction3.1.1 Moments; 3.1.2 Histogram; 3.1.3 Direction Features; 3.1.4 Image Registration; 3.1.5 Hough Transform; 3.1.6 Line-Based Representation; 3.1.7 Fourier Descriptors; 3.1.8 Shape Approximation; 3.1.9 Topological Features; 3.1.10 Linear Transforms; 3.1.11 Kernels; 3.2 Feature Selection for Pattern Classification; 3.2.1 Review of Feature Selection Methods; 3.3 Feature Creation for Pattern Classification; 3.3.1 Categories of Feature Creation; 3.3.2 Review of Feature Creation Methods; 3.3.3 Future Trends; 3.4 Chapter Summary; References; 4 Pattern Classification Methods 4.1 Overview of Classification Methods4.2 Statistical Methods; 4.2.1 Bayes Decision Theory; 4.2.2 Parametric Methods; 4.2.3 Nonparametric Methods; 4.3 Artificial Neural Networks; 4.3.1 Single-Layer Neural Network; 4.3.2 Multilayer Perceptron; 4.3.3 Radial Basis Function Network; 4.3.4 Polynomial Network; 4.3.5 Unsupervised Learning; 4.3.6 Learning Vector Quantization; 4.4 Support Vector Machines; 4.4.1 Maximal Margin Classifier; 4.4.2 Soft Margin and Kernels; 4.4.3 Implementation Issues; 4.5 Structural Pattern Recognition; 4.5.1 Attributed String Matching; 4.5.2 Attributed Graph Matching 4.6 Combining Multiple Classifiers4.6.1 Problem Formulation; 4.6.2 Combining Discrete Outputs; 4.6.3 Combining Continuous Outputs; 4.6.4 Dynamic Classifier Selection; 4.6.5 Ensemble Generation; 4.7 A Concrete Example; 4.8 Chapter Summary; References; 5 Word and String Recognition; 5.1 Introduction; 5.2 Character Segmentation; 5.2.1 Overview of Dissection Techniques; 5.2.2 Segmentation of Handwritten Digits; 5.3 Classification-Based String Recognition; 5.3.1 String Classification Model; 5.3.2 Classifier Design for String Recognition; 5.3.3 Search Strategies 5.3.4 Strategies for Large Vocabulary |
| Record Nr. | UNINA-9910830367403321 |
| Hoboken, N.J., : Wiley-Interscience, c2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Character recognition systems [[electronic resource] ] : a guide for students and practioners / / Mohamed Cheriet ... [et al.]
| Character recognition systems [[electronic resource] ] : a guide for students and practioners / / Mohamed Cheriet ... [et al.] |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2007 |
| Descrizione fisica | 1 online resource (360 p.) |
| Disciplina |
006.4/24
006.424 |
| Altri autori (Persone) | CherietM (Mohamed) |
| Soggetto topico | Optical character recognition devices |
| ISBN |
1-281-13472-4
9786611134723 0-470-17653-9 0-470-17652-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
CHARACTER RECOGNITION SYSTEMS; CONTENTS; Preface; Acknowledgments; List of Figures; List of Tables; Acronyms; 1 Introduction: Character Recognition, Evolution, and Development; 1.1 Generation and Recognition of Characters; 1.2 History of OCR; 1.3 Development of New Techniques; 1.4 Recent Trends and Movements; 1.5 Organization of the Remaining Chapters; References; 2 Tools for Image Preprocessing; 2.1 Generic Form-Processing System; 2.2 A Stroke Model for Complex Background Elimination; 2.2.1 Global Gray Level Thresholding; 2.2.2 Local Gray Level Thresholding
2.2.3 Local Feature Thresholding-Stroke-Based Model2.2.4 Choosing the Most Efficient Character Extraction Method; 2.2.5 Cleaning Up Form Items Using Stroke-Based Model; 2.3 A Scale-Space Approach for Visual Data Extraction; 2.3.1 Image Regularization; 2.3.2 Data Extraction; 2.3.3 Concluding Remarks; 2.4 Data Preprocessing; 2.4.1 Smoothing and Noise Removal; 2.4.2 Skew Detection and Correction; 2.4.3 Slant Correction; 2.4.4 Character Normalization; 2.4.5 Contour Tracing/Analysis; 2.4.6 Thinning; 2.5 Chapter Summary; References; 3 Feature Extraction, Selection, and Creation 3.1 Feature Extraction3.1.1 Moments; 3.1.2 Histogram; 3.1.3 Direction Features; 3.1.4 Image Registration; 3.1.5 Hough Transform; 3.1.6 Line-Based Representation; 3.1.7 Fourier Descriptors; 3.1.8 Shape Approximation; 3.1.9 Topological Features; 3.1.10 Linear Transforms; 3.1.11 Kernels; 3.2 Feature Selection for Pattern Classification; 3.2.1 Review of Feature Selection Methods; 3.3 Feature Creation for Pattern Classification; 3.3.1 Categories of Feature Creation; 3.3.2 Review of Feature Creation Methods; 3.3.3 Future Trends; 3.4 Chapter Summary; References; 4 Pattern Classification Methods 4.1 Overview of Classification Methods4.2 Statistical Methods; 4.2.1 Bayes Decision Theory; 4.2.2 Parametric Methods; 4.2.3 Nonparametric Methods; 4.3 Artificial Neural Networks; 4.3.1 Single-Layer Neural Network; 4.3.2 Multilayer Perceptron; 4.3.3 Radial Basis Function Network; 4.3.4 Polynomial Network; 4.3.5 Unsupervised Learning; 4.3.6 Learning Vector Quantization; 4.4 Support Vector Machines; 4.4.1 Maximal Margin Classifier; 4.4.2 Soft Margin and Kernels; 4.4.3 Implementation Issues; 4.5 Structural Pattern Recognition; 4.5.1 Attributed String Matching; 4.5.2 Attributed Graph Matching 4.6 Combining Multiple Classifiers4.6.1 Problem Formulation; 4.6.2 Combining Discrete Outputs; 4.6.3 Combining Continuous Outputs; 4.6.4 Dynamic Classifier Selection; 4.6.5 Ensemble Generation; 4.7 A Concrete Example; 4.8 Chapter Summary; References; 5 Word and String Recognition; 5.1 Introduction; 5.2 Character Segmentation; 5.2.1 Overview of Dissection Techniques; 5.2.2 Segmentation of Handwritten Digits; 5.3 Classification-Based String Recognition; 5.3.1 String Classification Model; 5.3.2 Classifier Design for String Recognition; 5.3.3 Search Strategies 5.3.4 Strategies for Large Vocabulary |
| Record Nr. | UNINA-9910840511303321 |
| Hoboken, N.J., : Wiley-Interscience, c2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
HDP 2004 : proceedings of the First ACM Hardcopy Document Processing Workshop, November 12, 2004, Washington, DC, USA ; co-located with CIKM 2004
| HDP 2004 : proceedings of the First ACM Hardcopy Document Processing Workshop, November 12, 2004, Washington, DC, USA ; co-located with CIKM 2004 |
| Pubbl/distr/stampa | [Place of publication not identified], : Association for Comuting Machinery, 2004 |
| Descrizione fisica | 1 online resource (76 p.;) |
| Collana | ACM Conferences |
| Soggetto topico |
Text processing (Computer science)
Optical character recognition devices Database management Engineering & Applied Sciences Computer Science |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | HDP '04 |
| Record Nr. | UNINA-9910375913103321 |
| [Place of publication not identified], : Association for Comuting Machinery, 2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
International journal on document analysis and recognition : IJDAR
| International journal on document analysis and recognition : IJDAR |
| Pubbl/distr/stampa | Berlin, : Springer, ©1998- |
| Descrizione fisica | 1 online resource |
| Soggetto topico |
Optical character recognition devices
Document imaging systems Pattern recognition systems Image processing - Digital techniques Text processing (Computer science) Digital preservation Information storage and retrieval systems Gestion électronique de documents Reconnaissance optique des caractères - Dispositifs |
| Soggetto genere / forma | Periodicals. |
| Soggetto non controllato | Computing, mathematics and information systems |
| ISSN | 1433-2825 |
| Formato | Materiale a stampa |
| Livello bibliografico | Periodico |
| Lingua di pubblicazione | eng |
| Altri titoli varianti |
International journal of document analysis and recognition
Document analysis and recognition IDJAR |
| Record Nr. | UNINA-9910138871803321 |
| Berlin, : Springer, ©1998- | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
International journal on document analysis and recognition : IJDAR
| International journal on document analysis and recognition : IJDAR |
| Pubbl/distr/stampa | Berlin, : Springer, ©1998- |
| Descrizione fisica | 1 online resource |
| Soggetto topico |
Optical character recognition devices
Document imaging systems Pattern recognition systems Image processing - Digital techniques Text processing (Computer science) Digital preservation Information storage and retrieval systems Gestion électronique de documents Reconnaissance optique des caractères - Dispositifs |
| Soggetto genere / forma | Periodicals. |
| Soggetto non controllato | Computing, mathematics and information systems |
| ISSN | 1433-2825 |
| Formato | Materiale a stampa |
| Livello bibliografico | Periodico |
| Lingua di pubblicazione | eng |
| Altri titoli varianti |
International journal of document analysis and recognition
Document analysis and recognition IDJAR |
| Record Nr. | UNISA-996211810603316 |
| Berlin, : Springer, ©1998- | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Licensee event report (LER) format modification
| Licensee event report (LER) format modification |
| Pubbl/distr/stampa | Washington, DC : , : United States Nuclear Regulatory Commission, Office of Inspection and Enforcement, , 1986 |
| Descrizione fisica | 1 online resource |
| Collana | Information notice |
| Soggetto topico |
Nuclear power plants - Accidents - Reporting - United States
Optical character recognition devices |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Licensee event report |
| Record Nr. | UNINA-9910715021103321 |
| Washington, DC : , : United States Nuclear Regulatory Commission, Office of Inspection and Enforcement, , 1986 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Proceedings of the ... International Conference on Document Analysis and Recognition
| Proceedings of the ... International Conference on Document Analysis and Recognition |
| Pubbl/distr/stampa | [Los Alamitos, Calif.] : , : [IEEE Computer Society Press] |
| Disciplina | 006.42 |
| Soggetto topico |
Optical character recognition devices
Pattern recognition systems Document imaging systems |
| Soggetto genere / forma | Conference papers and proceedings. |
| ISSN | 2379-2140 |
| Formato | Materiale a stampa |
| Livello bibliografico | Periodico |
| Lingua di pubblicazione | eng |
| Altri titoli varianti |
ICDAR
International Conference on Document Analysis and Recognition proceedings |
| Record Nr. | UNISA-996281142503316 |
| [Los Alamitos, Calif.] : , : [IEEE Computer Society Press] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
