Website Search
Find information on spaces, staff, and services.
Catalog Search
Books
Advances in digital document processing and retrieval
- Author / Creator
- Available as
- Online
- Summary
-
From the participation of researchers in most important international conferences in the field, it is noted that activities in automatic document processing have been continuously growing. This boo...
From the participation of researchers in most important international conferences in the field, it is noted that activities in automatic document processing have been continuously growing. This book is an edited volume in Digital Document Processing where the chapters are written by several internationally renowned researchers in the domain. It will be useful for both students and researchers working on various aspects of document image analysis and recognition problems. It contains chapters on topics that are not covered by any textbook, but are more futuristic like ""Going beyond the Myth of
Details
- Creator
- editors, Bidyut Baran Chaudhuri, Swapan Kumar Parui, Indian Statistical Institute, India
- Format
- Books
- Language
- English
- Publication
-
- New Jersey : World Scientific, [2014]
- �2014
- Physical Details
-
- 1 online resource (x, 323 pages) : illustrations
- ISBNs
- 9789814368711, 9814368717, 9814368709, 1306396263
- OCLC
- ocn869811219
- Description based upon print version of record.
- Includes bibliographical references and index.
- English
- Foreword; Preface; Contents; 1. Document Image Analysis using Markovian Models: Application to Historical Documents; 1.1. Introduction; 1.2. Hidden Markov Random Field Models; 1.2.1. Theoretical foundations; 1.2.1.1. Simulated annealing; 1.2.1.2. Iterated Conditional Modes (ICM); 1.2.1.3. Highest Confidence First (HCF) algorithm; 1.2.1.4. 2D Dynamic Programming; 1.2.2. Application of MRF labelling to handwritten document segmentation; 1.2.2.1. Probability densities; 1.2.2.2. Clique potential functions; 1.2.2.3. Observations; 1.2.2.4. Decoding strategy; 1.2.3. Results; 1.2.3.1. Zone labelling
- 1.2.3.2. Text line labelling1.2.3.3. Conclusion; 1.3. Conditional Random Field Models; 1.3.1. Proposed model; 1.3.1.1. Feature functions; 1.3.1.2. Model inference; 1.3.1.3. Parameter learning; 1.3.2. A two level CRF model; 1.3.2.1. Observation features; 1.3.2.2. Label features; 1.3.2.3. Learning; 1.3.3. Integrating more contextual information; 1.3.3.1. Global feature function; 1.3.3.2. Combination of the information sources; 1.3.3.3. Linear combination of the information sources (impl.2); 1.3.3.4. Combination of the information sources using an MLP (impl.3); 1.3.4. Experiments and results
- 1.4. Conclusions and OutlookAcknowledgments; References; 2. Information Just-in-Time: Going Beyond the Myth of Paperlessness; 2.1. Introduction; 2.2. Information Just-in-Time; 2.2.1. Personal Information Environment; 2.2.2. Hot/Warm/Cold Documents; 2.2.3. Proposed Approach; 2.3. Digital Pen Solution; 2.3.1. Anoto Functionality; 2.3.2. Data Entry Applications; 2.4. iJIT Collaboration Platform; 2.4.1. On-Demand Printing; 2.4.2. Hybrid Document Management System; 2.4.3. Research Notebook Application - iJITNote; 2.4.4. Future Directions; 2.5. Conclusions; Acknowledgments; References
- 3. The Role of Document Image Analysis in Trustworthy Elections3.1. Introduction; 3.2. History; 3.3. Problems with Current Voting Technologies; 3.4. Experimental Approaches to Reliable Processing of Voting Records; 3.4.1. Statistical distribution of mark sense errors; 3.4.2. Unbiased context-free visual auditing based on ballot images; 3.4.3. Homogenous class display; 3.4.4. Unique identification of ballots; 3.4.5. Error characteristics of DRE with VVPAT; 3.4.6. Development of testing procedures for voting systems; 3.4.7. Affordances for voters with disabilities; 3.5. Some Related Efforts
- 3.6. Concluding RemarksReferences; 4. Information Retrieval from Document Image Databases; 4.1. Introduction; 4.2. Related Work; 4.3. Word Shape Coding; 4.3.1. Word Shape Coding by Character Stroke Categorization; 4.3.2. Word Shape Coding by Character Boundary Extrema; 4.3.3. Word Shape Coding by Character Holes and Reservoirs; 4.4. Document Image Retrieval; 4.4.1. Document Vector Construction; 4.4.2. Document Similarity Measurement; 4.5. Discussions; 4.5.1. Coding Ambiguity; 4.5.2. Coding Robustness; 4.5.3. Document Similarity Measurements; 4.5.4. Coding Scheme Selection; 4.6. Conclusion
- References