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.
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.
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.
This book presents advances in character recognition, and it consists of 12 chapters that cover wide range of topics on different aspects of character recognition. Hopefully, this book will serve as a reference source for academic research, for professionals working in the character recognition field and for all interested in the subject.
This book focuses on the fundamental tools and ideas thatare generally usedin the handwriting recognition field.Though one of the oldest fields of computer patternrecognition, this topic is now attracting growing numbers ofresearchers in universities and development engineers inindustry.The volume is based on a NATO Advanced Study Institute thattook place in France in 1993. The most important algorithmsfor data acquisition, preprocessing, feature extraction, andclassification, andthe commonest database and devices foron-line and off-line recognition are presented. The role ofparallel machines and special networks in solving problemsin the field are also discussed.
The book is a collection of invited chapters by experts in Chinese document and text processing, and is part of a series on Language Processing, Pattern Recognition, and Intelligent Systems. The chapters introduce the latest advances and state-of-the-art methods for Chinese document image analysis and recognition, font design, text analysis and speaker recognition. Handwritten Chinese character recognition and text line recognition are at the core of document image analysis (DIA), and therefore, are addressed in four chapters for different scripts (online characters, offline characters, ancient characters, and text lines). Two chapters on character recognition pay much attention to deep convolutional neural networks (CNNs), which are widely used and performing superiorly in various pattern recognition problems. A chapter is contributed to describe a large handwriting database consisting both online and offline characters and text pages. Postal mail reading and writer identification, addressed in two chapters, are important applications of DIA. The collection can serve as reference for students and engineers in Chinese document and text processing and their applications.
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.
This book presents the results of the 5th International Conference on Computer Recognition Systems CORES’07 held 22-25 October 2007 in Hotel Tumski, Wroclaw, Poland. It brings together original research results in both methodological issues and different application areas of pattern recognition. The contributions cover all topics in pattern recognition including, for example, classification and interpretation of text, video, and voice.
Designing machines that can read handwriting like human beings has been an ambitious goal for more than half a century, driving talented researchers to explore diverse approaches. Obstacles have often been encountered that at first appeared insurmountable but were indeed overcome before long. Yet some open issues remain to be solved. As an indispensable branch, Chinese handwriting recognition has been termed as one of the most difficult Pattern Recognition tasks. Chinese handwriting recognition poses its own unique challenges, such as huge variations in strokes, diversity of writing styles, and a large set of confusable categories. With ever-increasing training data, researchers have pursued elaborate algorithms to discern characters from different categories and compensate for the sample variations within the same category. As a result, Chinese handwriting recognition has evolved substantially and amazing achievements can be seen. This book introduces integral algorithms used in Chinese handwriting recognition and the applications of Chinese handwriting recogniers. The first part of the book covers both widespread canonical algorithms to a reliable recognizer and newly developed scalable methods in Chinese handwriting recognition. The recognition of Chinese handwritten text is presented systematically, including instructive guidelines for collecting samples, novel recognition paradigms, distributed discriminative learning of appearance models and distributed estimation of contextual models for large categories, in addition to celebrated methods, e.g. Gradient features, MQDF and HMMs. In the second part of this book, endeavors are made to create a friendlier human-machine interface through application of Chinese handwriting recognition. Four scenarios are exemplified: grid-assisted input, shortest moving input, handwritten micro-blog, and instant handwriting messenger. All the while, the book moves from basic to more complex approaches, also providing a list for further reading with literature comments.
In the age of e-society, handwritten signature processing is an enabling technology in a multitude of fields in the “digital agenda” of many countries, ranging from e-health to e-commerce, from e-government to e-justice, from e-democracy to e-banking, and smart cities. Handwritten signatures are very complex signs; they are the result of an elaborate process that depends on the psychophysical state of the signer and the conditions under which the signature apposition process occurs. Notwithstanding, recent efforts from academies and industries now make possible the integration of signature-based technologies into other standard equipment to form complete solutions that are able to support the security requirements of today's society.Advances in Digital Handwritten Signature Processing primarily provides an update on the most fascinating and valuable researches in the multifaceted field of handwritten signature analysis and processing. The chapters within also introduce and discuss critical aspects and precious opportunities related to the use of this technology, as well as highlight fundamental theoretical and applicative aspects of the field. This book contains papers by well-recognized and active researchers and scientists, as well as by engineers and commercial managers working for large international companies in the field of signature-based systems for a wide range of applications and for the development of e-society.This publication is devoted to both researchers and experts active in the field of biometrics and handwriting forensics, as well as professionals involved in the development of signature-based solutions for advanced applications in medicine, finance, commerce, banking, public and private administrations, etc. Handwritten Signature Processing may also be used as an advanced textbook by graduate students.
