Download or read book Handbook of Document Image Processing and Recognition written by David Doermann and published by Springer. This book was released on 2014-05-21 with total page 1055 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Document Image Processing and Recognition is a comprehensive resource on the latest methods and techniques in document image processing and recognition. Each chapter provides a clear overview of the topic followed by the state of the art of techniques used – including elements of comparison between them – along with supporting references to archival publications, for those interested in delving deeper into topics addressed. Rather than favor a particular approach, the text enables the reader to make an informed decision for their specific problems.
Download or read book Handbook of Character Recognition and Document Image Analysis written by Horst Bunke and published by World Scientific. This book was released on 1997 with total page 868 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optical character recognition and document image analysis have become very important areas with a fast growing number of researchers in the field. This comprehensive handbook with contributions by eminent experts, presents both the theoretical and practical aspects at an introductory level wherever possible.
Download or read book Handbook of Document Image Processing and Recognition written by David Doermann and published by Springer. This book was released on 2014-05-22 with total page 1055 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Document Image Processing and Recognition is a comprehensive resource on the latest methods and techniques in document image processing and recognition. Each chapter provides a clear overview of the topic followed by the state of the art of techniques used – including elements of comparison between them – along with supporting references to archival publications, for those interested in delving deeper into topics addressed. Rather than favor a particular approach, the text enables the reader to make an informed decision for their specific problems.
Download or read book Handbook of Pattern Recognition and Computer Vision written by C. H. Chen and published by World Scientific. This book was released on 1999 with total page 1045 pages. Available in PDF, EPUB and Kindle. Book excerpt: The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference.
Download or read book Handbook of Character Recognition and Document Image Analysis written by Horst Bunke and published by . This book was released on 2000 with total page 833 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Character Recognition Systems written by Mohamed Cheriet and published by John Wiley & Sons. This book was released on 2007-11-27 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Much of pattern recognition theory and practice, including methods such as Support Vector Machines, has emerged in an attempt to solve the character recognition problem. This book is written by very well-known academics who have worked in the field for many years and have made significant and lasting contributions. The book will no doubt be of value to students and practitioners." -Sargur N. Srihari, SUNY Distinguished Professor, Department of Computer Science and Engineering, and Director, Center of Excellence for Document Analysis and Recognition (CEDAR), University at Buffalo, The State University of New York "The disciplines of optical character recognition and document image analysis have a history of more than forty years. In the last decade, the importance and popularity of these areas have grown enormously. Surprisingly, however, the field is not well covered by any textbook. This book has been written by prominent leaders in the field. It includes all important topics in optical character recognition and document analysis, and is written in a very coherent and comprehensive style. This book satisfies an urgent need. It is a volume the community has been awaiting for a long time, and I can enthusiastically recommend it to everybody working in the area." -Horst Bunke, Professor, Institute of Computer Science and Applied Mathematics (IAM), University of Bern, Switzerland In Character Recognition Systems, the authors provide practitioners and students with the fundamental principles and state-of-the-art computational methods of reading printed texts and handwritten materials. The information presented is analogous to the stages of a computer recognition system, helping readers master the theory and latest methodologies used in character recognition in a meaningful way. This book covers: * Perspectives on the history, applications, and evolution of Optical Character Recognition (OCR) * The most widely used pre-processing techniques, as well as methods for extracting character contours and skeletons * Evaluating extracted features, both structural and statistical * Modern classification methods that are successful in character recognition, including statistical methods, Artificial Neural Networks (ANN), Support Vector Machines (SVM), structural methods, and multi-classifier methods * An overview of word and string recognition methods and techniques * Case studies that illustrate practical applications, with descriptions of the methods and theories behind the experimental results Each chapter contains major steps and tricks to handle the tasks described at-hand. Researchers and graduate students in computer science and engineering will find this book useful for designing a concrete system in OCR technology, while practitioners will rely on it as a valuable resource for the latest advances and modern technologies that aren't covered elsewhere in a single book.
Download or read book Document Image Processing written by Ergina Kavallieratou and published by MDPI. This book was released on 2018-10-03 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Document Image Processing" that was published in J. Imaging
Download or read book Digital Document Processing written by Bidyut B. Chaudhuri and published by Springer Science & Business Media. This book was released on 2007-03-13 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings all the major and frontier topics in the field of document analysis together into a single volume, creating a unique reference source that will be invaluable to a large audience of researchers, lecturers and students working in this field. With chapters written by some of the most distinguished researchers active in this field, this book addresses recent advances in digital document processing research and development.
Download or read book Handbook of Digital Face Manipulation and Detection written by Christian Rathgeb and published by Springer Nature. This book was released on 2022-01-31 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book provides the first comprehensive collection of studies dealing with the hot topic of digital face manipulation such as DeepFakes, Face Morphing, or Reenactment. It combines the research fields of biometrics and media forensics including contributions from academia and industry. Appealing to a broad readership, introductory chapters provide a comprehensive overview of the topic, which address readers wishing to gain a brief overview of the state-of-the-art. Subsequent chapters, which delve deeper into various research challenges, are oriented towards advanced readers. Moreover, the book provides a good starting point for young researchers as well as a reference guide pointing at further literature. Hence, the primary readership is academic institutions and industry currently involved in digital face manipulation and detection. The book could easily be used as a recommended text for courses in image processing, machine learning, media forensics, biometrics, and the general security area.
Download or read book Document Processing Using Machine Learning written by Sk Md Obaidullah and published by CRC Press. This book was released on 2019-11-25 with total page 183 pages. Available in PDF, EPUB and Kindle. Book excerpt: Document Processing Using Machine Learning aims at presenting a handful of resources for students and researchers working in the document image analysis (DIA) domain using machine learning since it covers multiple document processing problems. Starting with an explanation of how Artificial Intelligence (AI) plays an important role in this domain, the book further discusses how different machine learning algorithms can be applied for classification/recognition and clustering problems regardless the type of input data: images or text. In brief, the book offers comprehensive coverage of the most essential topics, including: · The role of AI for document image analysis · Optical character recognition · Machine learning algorithms for document analysis · Extreme learning machines and their applications · Mathematical foundation for Web text document analysis · Social media data analysis · Modalities for document dataset generation This book serves both undergraduate and graduate scholars in Computer Science/Information Technology/Electrical and Computer Engineering. Further, it is a great fit for early career research scientists and industrialists in the domain.
Download or read book Handbook of Pattern Recognition and Computer Vision 5th Edition written by Chi-hau Chen and published by World Scientific. This book was released on 2015-12-15 with total page 582 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides an up-to-date and authoritative treatment of pattern recognition and computer vision, with chapters written by leaders in the field. On the basic methods in pattern recognition and computer vision, topics range from statistical pattern recognition to array grammars to projective geometry to skeletonization, and shape and texture measures. Recognition applications include character recognition and document analysis, detection of digital mammograms, remote sensing image fusion, and analysis of functional magnetic resonance imaging data, etc.
Download or read book Document Image Analysis written by Lawrence O'Gorman and published by Institute of Electrical & Electronics Engineers(IEEE). This book was released on 1995 with total page 542 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Document Image Analysis written by Horst Bunke and published by World Scientific. This book was released on 1994 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interest in the automatic processing and analysis of document images has been rapidly increasing during the past few years. This book addresses the different subfields of document image analysis, including preprocessing and segmentation, form processing, handwriting recognition, line drawing and map processing, and contextual processing.
Download or read book Document Image Analysis written by K.C. Santosh and published by Springer. This book was released on 2018-09-18 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book focuses on one of the key issues in document image processing – graphical symbol recognition, which is a sub-field of the larger research domain of pattern recognition. It covers several approaches: statistical, structural and syntactic, and discusses their merits and demerits considering the context. Through comprehensive experiments, it also explores whether these approaches can be combined. The book presents research problems, state-of-the-art methods that convey basic steps as well as prominent techniques, evaluation metrics and protocols, and research standpoints/directions that are associated with it. However, it is not limited to straightforward isolated graphics (visual patterns) recognition; it also addresses complex and composite graphical symbols recognition, which is motivated by real-world industrial problems.
Download or read book Machine Learning in Document Analysis and Recognition written by Simone Marinai and published by Springer Science & Business Media. This book was released on 2008-01-10 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of Document Analysis and Recognition (DAR) is to recognize the text and graphical components of a document and to extract information. This book is a collection of research papers and state-of-the-art reviews by leading researchers all over the world. It includes pointers to challenges and opportunities for future research directions. The main goal of the book is to identify good practices for the use of learning strategies in DAR.
Download or read book Handbook of Texture Analysis written by Majid Mirmehdi and published by World Scientific. This book was released on 2008 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Texture analysis is one of the fundamental aspects of human vision by which we discriminate between surfaces and objects. In a similar manner, computer vision can take advantage of the cues provided by surface texture to distinguish and recognize objects. In computer vision, texture analysis may be used alone or in combination with other sensed features (e.g. color, shape, or motion) to perform the task of recognition. Either way, it is a feature of paramount importance and boasts a tremendous body of work in terms of both research and applications.Currently, the main approaches to texture analysis must be sought out through a variety of research papers. This collection of chapters brings together in one handy volume the major topics of importance, and categorizes the various techniques into comprehensible concepts. The methods covered will not only be relevant to those working in computer vision, but will also be of benefit to the computer graphics, psychophysics, and pattern recognition communities, academic or industrial.
Download or read book Document Analysis And Text Recognition Benchmarking State of the art Systems written by Margner Volker and published by World Scientific. This book was released on 2018-02-23 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: The compendium presents the latest results of the most prominent competitions held in the field of Document Analysis and d104 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. Contents: Logical Structure and Segmentation: Logical Structure Extraction from Digitized Books (Antoine Doucet) Handwriting Segmentation (Nikolaos Stamatopoulos, Georgios Louloudis, and Basilis Gatos) Digits and Mathematical Expressions: Handwritten Digit and Digit String Recognition (Markus Diem, Stefan Fiel, and Florian Kleber) Handwritten Mathematical Expressions (Harold Mouchère, Christian Viard-Gaudin, Richard Zanibi, and Utpal Garain) Writer Identification and Signature Verification: Writer Identification (Georgios Louloudis, Nikolaos Stamatopoulos, and Basilis Gatos) Arabic Writer Identification Using AHTID/MW and KHATT Database (Fouad Slimane and Sameh Awaida) Signature Verification: Recent Developments and Perspectives (Muhammad Imran Malik, Sheraz Ahmed, Andreas Dengel, and Marcus Liwicki) d104 Recognition: Handwritten d104 Recognition Competitions With the tranScriptorium Dataset (Joan Andreu Sánchez, Verónica Romero, Alejandro H Toselli, and Enrique Vidal) Multifont and Multisize Low-resolution Arabic d104 Recognition Using APTI Database (Fouad Slimane and Christine Vanoirbeek) Readership: Researchers, academics, professionals and graduate students in pattern recognition/image analysis, neural networks, and innovation/technology. Keywords: Document Analysis;Digitisation;Character Recognition;Mathematical Expression Recognition;Digit Recognition;Arabic Documents;Handwriting Recognition;Performance Evaluation;Benchmarking;CompetitionsReview:0
