Liu Zhi-Qiang, Cai Jin-Hai, Buse Richard Handwriting Recognition / Soft Computing and Probabilistic Approaches 9783540401773

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Автор: Liu Zhi-Qiang, Cai Jin-Hai, Buse Richard
Название: Handwriting Recognition / Soft Computing and Probabilistic Approaches
Перевод названия: Компьютерное распознавание рукописного текста
ISBN: 9783540401773
Издательство: Springer
Классификация:

Преподавание отдельных предметов

Математика и естественные науки

Прикладная математика

Инженерное дело: Общие вопросы

Распознавание образов

ISBN-10: 3540401776
Обложка/Формат: Hardback
Страницы: 245
Вес: 0.53 кг.
Дата издания: 21.07.2003
Серия: Studies in Fuzziness and Soft Computing
Язык: English
Иллюстрации: Illustrations
Размер: 23.39 x 15.60 x 1.60
Читательская аудитория: General (us: trade)
Подзаголовок: Soft computing and probabilistic approaches
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Германии
Описание: This book takes a fresh look at the problem of unconstrained handwriting recognition and introduces the reader to new techniques for the recognition of written words and characters using statistical and soft computing approaches. The types of uncertainties and variations present in handwriting data are discussed in detail. The book presents several algorithms that use modified hidden Markov models and Markov random field models to simulate the handwriting data statistically and structurally in a single framework. The book explores methods that use fuzzy logic and fuzzy sets for handwriting recognition. The effectiveness of these techniques is demonstrated through extensive experimental results and real handwritten characters and words.
Дополнительное описание: Формат: 235x155
Круг читателей: Researchers, academics, graduate students, industry in the field of Soft Computing and Fuzziness
Ключевые слова: Handwriting Recognition
Soft Computing
Fuzzy Logic
Word Recognition
Markov Models
Markov Random Field Model
Язык: eng
Оглавление: Introduction.- Pre-processing and Feature Extraction.- Hidden Markov Model-Based Method for Recognizing Handwritten Digits.- Markov Models with Spectral Features for Handwritten Numeral Recognition.- Markov Random Field Model for Recognizing Handwritten Digits.- Markov Random Field Models for Recognizing Handwritten Words.- A Structural and Relational Approach to Handwritten Word Recognition.- Handwritten Word Recognition Using Fuzzy Logic.- Conclusion.

Handwriting Recognition / Soft Computing and Probabilistic Approaches, Liu Zhi-Qiang, Cai Jin-Hai, Buse Richard