Guide To Ocr For Arabic Scripts

This Guide to OCR for Arabic Scripts is the first book of its kind, specifically devoted to this emerging field. Topics and features: contains contributions from the leading researchers in the field; with a Foreword by Professor Bente Maegaard of the University of Copenhagen; presents a detailed overview of Arabic character recognition technology, covering a range of different aspects of pre-processing and feature extraction; reviews a broad selection of varying approaches, including HMM-based methods and a recognition system based on multidimensional recurrent neural networks; examines the evaluation of Arabic script recognition systems, discussing data collection and annotation, benchmarking strategies, and handwriting recognition competitions; describes numerous applications of Arabic script recognition technology, from historical Arabic manuscripts to online Arabic recognition.

This is the first comprehensive text on Optical Character Recognition for Indic scripts. It covers many topics and describes OCR systems for eight different scripts—Bangla, Devanagari, Gurmukhi, Gujarti, Kannada, Malayalam, Tamil and Urdu.

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.

This book offers a broad and structured overview of the state-of-the-art methods that could be applied for context-dependent languages like Arabic. It also provides guidelines on how to deal with Arabic scene data that appeared in an uncontrolled environment impacted by different font size, font styles, image resolution, and opacity of text. Being an intrinsic script, Arabic and Arabic-like languages attract attention from research community. There are a number of challenges associated with the detection and recognition of Arabic text from natural images. This book discusses these challenges and open problems and also provides insights into the complexities and issues that researchers encounter in the context of Arabic or Arabic-like text recognition in natural and document images. It sheds light on fundamental questions, such as a) How the complexity of Arabic as a cursive scripts can be demonstrated b) What the structure of Arabic text is and how to consider the features from a given text and c) What guidelines should be followed to address the context learning ability of classifiers existing in machine learning.

The two-volume set LNCS 9279 and 9280 constitutes the refereed proceedings of the 18th International Conference on Image Analysis and Processing, ICIAP 2015, held in Genoa, Italy, in September 2015. The 129 papers presented were carefully reviewed and selected from 231 submissions. The papers are organized in the following seven topical sections: video analysis and understanding, multiview geometry and 3D computer vision, pattern recognition and machine learning, image analysis, detection and recognition, shape analysis and modeling, multimedia, and biomedical applications.

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.

This Festschrift volume is published in Honor of Yaacov Choueka on the occasion of this 75th birthday. The present three-volumes liber amicorum, several years in gestation, honours this outstanding Israeli computer scientist and is dedicated to him and to his scientific endeavours. Yaacov's research has had a major impact not only within the walls of academia, but also in the daily life of lay users of such technology that originated from his research. An especially amazing aspect of the temporal span of his scholarly work is that half a century after his influential research from the early 1960s, a project in which he is currently involved is proving to be a sensation, as will become apparent from what follows. Yaacov Choueka began his research career in the theory of computer science, dealing with basic questions regarding the relation between mathematical logic and automata theory. From formal languages, Yaacov moved to natural languages. He was a founder of natural-language processing in Israel, developing numerous tools for Hebrew. He is best known for his primary role, together with Aviezri Fraenkel, in the development of the Responsa Project, one of the earliest fulltext retrieval systems in the world. More recently, he has headed the Friedberg Genizah Project, which is bringing the treasures of the Cairo Genizah into the Digital Age. This first part of the three-volume set covers a range of topics in computer science. The papers are grouped in topical sections on: the jubilaris: Yaacov and his oeuvre; theory of computation; science computing and tools for engineering; information retrieval.

The two volumes LNCS 9041 and 9042 constitute the proceedings of the 16th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2015, held in Cairo, Egypt, in April 2015. The total of 95 full papers presented was carefully reviewed and selected from 329 submissions. They were organized in topical sections on grammar formalisms and lexical resources; morphology and chunking; syntax and parsing; anaphora resolution and word sense disambiguation; semantics and dialogue; machine translation and multilingualism; sentiment analysis and emotion detection; opinion mining and social network analysis; natural language generation and text summarization; information retrieval, question answering, and information extraction; text classification; speech processing; and applications.