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.

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.

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.

This book includes reviewed papers by international scholars from the 2020 International Conference on Pattern Recognition and Artificial Intelligence (held online). The papers have been expanded to provide more details specifically for the book. It is geared to promote ongoing interest and understanding about pattern recognition and artificial intelligence. Like the previous book in the series, this book covers a range of topics and illustrates potential areas where pattern recognition and artificial intelligence can be applied. It highlights, for example, how pattern recognition and artificial intelligence can be used to classify, predict, detect and help promote further discoveries related to credit scores, criminal news, national elections, license plates, gender, personality characteristics, health, and more.Chapters include works centred on medical and financial applications as well as topics related to handwriting analysis and text processing, internet security, image analysis, database creation, neural networks and deep learning. While the book is geared to promote interest from the general public, it may also be of interest to graduate students and researchers in the field.

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.

This book comprises a selection of papers on new methods for analysis and design of hybrid intelligent systems using soft computing techniques from the IFSA 2007 World Congress, held in Cancun, Mexico, June 2007.

The nature of handwriting in our society has significantly altered over the ages due to the introduction of new technologies such as computers and the World Wide Web. With increases in the amount of signature verification needs, state of the art internet and paper-based automated recognition methods are necessary. ""Pattern Recognition Technologies and Applications: Recent Advances"" provides cutting-edge pattern recognition techniques and applications. Written by world-renowned experts in their field, this easy to understand book is a must have for those seeking explanation in topics such as on- and offline handwriting and speech recognition, signature verification, and gender classification.