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This book has the primary goal of presenting and discussing some recent advances and ongoing developments in the Handwritten Text Recognition (HTR) field, resulting from works done on different HTR-related topics for the achievement of more accurate and efficient recognition systems. Nowadays, there is an enormous worldwide interest in HTR systems, which is mostly driven by the emergence of new portable devices incorporating handwriting recognition functions. Others interests are the biometric identification systems employing handwritten signatures, as well as the requirements from cultural heritage institutions like historical archives and libraries in order to preserve their large collections of historical (handwritten) documents. The book is organized into two sections: the first one is mainly devoted to describing the current state-of-the-art applications in HTR and the last advances in some of the steps involved in HTR workflow (that is, preprocessing, feature extraction, recognition engines, etc.), whereas the second focuses more on some relevant HTR-related applications.In more depth, the first part offers an overview of the current state-of-the-art applications of HTR technology and introduces the new challenges and research opportunities in the field. Besides, it provides a general discussion of currently ongoing approaches towards solving the underlying search problems on the basis of existing methods for HTR in terms of both accuracy and efficiency. In particular, there are chapters especially focused on image thresholding and enhancement, text image preprocessing techniques for historical handwritten documents and feature extraction methods for HTR. Likewise, in line with the breakout success of Deep Neural Networks (DNNs) in the field, a whole chapter is devoted to describing the designing of HTR systems based on DNNs. Finally, a chapter listing the most used benchmarking datasets for HTR is also included, providing detailed information about which types of HTR systems (on/offline) and features are commonly considered for each of them.In the second part, several systems -- also developed on the basis of the fundamental concepts and general approaches outlined in the first part -- are described for several HTR-related applications. Presented in the corresponding chapters, these applications cover a wide spectrum of scenarios: mathematical formulae recognition, scripting language recognition, multimodal handwriting-speech recognition, hardware design for online HTR, student performance evaluation through handwriting analysis, performance evaluation methods, keyword spotting, and handwritten signature verification systems.Last but not least, it is important to remark that to a large extent, this book is the result of works carried out by several researchers in the Handwritten Text Recognition field.Therefore, it owes credit to these researchers that have directly contributed to their ideas, discussions and technical collaborations, and in general who, in one manner or another, have made it possible.
Advances in Handwriting Recognition contains selected key papers from the 6th International Workshop on Frontiers in Handwriting Recognition (IWFHR '98), held in Taejon, Korea from 12 to 14, August 1998. Most of the papers have been expanded or extensively revised to include helpful discussions, suggestions or comments made during the workshop.
For many years researchers in the field of Handwriting Recognition were considered to be working in an area of minor importance in Pattern Recog nition. They had only the possibility to present the results of their research at general conferences such as the ICPR or publish their papers in journals such as some of the IEEE series or PR, together with many other papers generally oriented to the more promising areas of Pattern Recognition. The series of International Workshops on Frontiers in Handwriting Recog nition and International Conferences on Document Analysis and Recognition together with some special issues of several journals are now fulfilling the expectations of many researchers who have been attracted to this area and are involving many academic institutions and industrial companies. But in order to facilitate the introduction of young researchers into the field and give them both theoretically and practically powerful tools, it is now time that some high level teaching schools in handwriting recognition be held, also in order to unite the foundations of the field. Therefore it was my pleasure to organize the NATO Advanced Study Institute on Fundamentals in Handwriting Recognition that had its origin in many exchanges among the most important specialists in the field, during the International Workshops on Frontiers in Handwriting Recognition.
Over the last few decades, research on handwriting recognition has made impressive progress. The research and development on handwritten word recognition are to a large degree motivated by many application areas, such as automated postal address and code reading, data acquisition in banks, text-voice conversion, security, etc. As the prices of scanners, com puters and handwriting-input devices are falling steadily, we have seen an increased demand for handwriting recognition systems and software pack ages. Some commercial handwriting recognition systems are now available in the market. Current commercial systems have an impressive performance in recognizing machine-printed characters and neatly written texts. For in stance, High-Tech Solutions in Israel has developed several products for container ID recognition, car license plate recognition and package label recognition. Xerox in the U. S. has developed TextBridge for converting hardcopy documents into electronic document files. In spite of the impressive progress, there is still a significant perfor mance gap between the human and the machine in recognizing off-line unconstrained handwritten characters and words. The difficulties encoun tered in recognizing unconstrained handwritings are mainly caused by huge variations in writing styles and the overlapping and the interconnection of neighboring characters. Furthermore, many applications demand very high recognition accuracy and reliability. For example, in the banking sector, although automated teller machines (ATMs) and networked banking sys tems are now widely available, many transactions are still carried out in the form of cheques.
Frontiers in Handwriting Recognition contains selected key papers from the 6th International Workshop on Frontiers in Handwriting Recognition (IWFHR '98), held in Taejon, Korea from 12 to 14, August 1998. Most of the papers have been expanded or extensively revised to include helpful discussions, suggestions or comments made during the workshop.
Since their first inception, automatic reading systems have evolved substantially, yet the recognition of handwriting remains an open research problem due to its substantial variation in appearance. With the introduction of Markovian models to the field, a promising modeling and recognition paradigm was established for automatic handwriting recognition. However, no standard procedures for building Markov model-based recognizers have yet been established. This text provides a comprehensive overview of the application of Markov models in the field of handwriting recognition, covering both hidden Markov models and Markov-chain or n-gram models. First, the text introduces the typical architecture of a Markov model-based handwriting recognition system, and familiarizes the reader with the essential theoretical concepts behind Markovian models. Then, the text reviews proposed solutions in the literature for open problems in applying Markov model-based approaches to automatic handwriting recognition.
In the fall of 2006, the University of Maryland, along with various government and industrial sponsors, invited leading researchers from all over the world to a two-day Summit on Arabic and Chinese Handwriting Recognition (SACH 2006). The event acted as a complement to the biennial Symposium on Document Image Understanding Technology (SDIUT), providing a focused glimpse into the state of the art in Arabic and Chinese handwriting recognition. It offered a forum for interaction with prominent researchers at the forefront of the scientific community and provided an opportunity for participants to help explore possible directions of the field. This book is a result of the expansion, peer review, and revision of selected papers presented at this meeting. Handwriting recognition remains the Holy Grail of document analysis, and Arabic and Chinese scripts embrace many of the most significant challenges. We are pleased to have 16 scientific papers covering the original topics of handwritten Arabic and Chinese, as well as 2 papers covering other handwritten scripts. We asked each author to not only describe the techniques used in addressing the problem, but to attempt to identify the key research challenges and problems that the community faces. The result is an impressive collection of manuscripts that provide various detailed views of the state of research. In this book, six articles deal directly with Arabic handwriting. • Cheriet provides an overview of the problems of Arabic recognition and how systems can use natural language processing techniques to correct errors in lexicon-based systems.
Character and handwriting recognition by computers is attracting much attention particularly because of its potential for application in many areas such as office automation, bank check processing, recognition of postal addresses and ZIP Codes, signature verification, and document and text recognition.Over the past four decades, many methods have been proposed, developed and tested for computers to recognize characters, and they have been reported in a variety of publications. The present volume is a coherent and integrated publication containing papers which give new research results in this increasingly active field. It is a boon to researchers, scientists and engineers who need to keep abreast of new developments in character and handwriting methodologies and applications.
Handwriting Recognition has become a very important research area which is attracting more and more scientists. In fact, the extraordinary advances in the field of data acquisition technology and the promising results of the research, nowadays make possible the development of commercial systems for processing and recognition of handwritten documents.This book contains the results of the activity of the most important academic and industrial research groups working in this area. The new issues arising in the field are focused and involve both theoretical and practical aspects related to handwriting recognition and document processing systems. The contributions of eminent experts point out the more interesting challenges for the scientific community ranging from acquisition and preprocessing of handwritten documents, to recognition of handwritten digits and words, to the design of multi-expert systems and the exploitation of the contextual knowledge to improve system performance.
Handwriting recognition in general and online handwriting recognition in particular has been an active research area for several decades. Most of the research have been focused on English and recently on other scripts like Arabic and Chinese. There is a lack of research on recognition in Turkish text and this work primarily fills that gap with a state-of-the-art recognizer for the first time. It contains design and implementation details of a complete recognition system for recognition of Turkish isolated words. It considers the recognition of unconstrained handwriting with a limited vocabulary size first and then evolves to a large vocabulary system. Turkish script has many similarities with other Latin scripts, like English, which makes it possible to adapt strategies that work for them. However, there are some other issues which are particular to Turkish that should be taken into consideration separately. Two of the challenging issues in recognition of Turkish text are determined as delayed strokes and high Out-of-Vocabulary (OOV). This work examines these problems and alternative solutions at depth and proposes suitable solutions for Turkish script particularly.