Handwriting Recognition: Soft Computing and Probabilistic Approaches: 133 (Studies in Fuzziness and Soft Computing) - Tapa dura

Liu, Zhi-Qiang; Cai, Jin-Hai; Buse, Richard

 
9783540401773: Handwriting Recognition: Soft Computing and Probabilistic Approaches: 133 (Studies in Fuzziness and Soft Computing)
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ISBN 10: 3540401776 ISBN 13: 9783540401773
Editorial: Springer, 2003

Sinopsis

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.

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Reseña del editor

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.

Reseña del editor

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.

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Editorial
Springer
Año de publicación
2003
Idioma
Inglés
ISBN 10 
3540401776
ISBN 13 
9783540401773
Encuadernación
Tapa dura
Número de páginas
252
Contacto del fabricante
ROXIO
https://www.also.com/ec/cms5/en_6000/6000/index.jsp

Friedrich-Karl-Str. 9
Hamburg
22391
Alemania

Otras ediciones populares con el mismo título

9783642072802: Handwriting Recognition: Soft Computing and Probabilistic Approaches: 133 (Studies in Fuzziness and Soft Computing, 133)

Edición Destacada

ISBN 10:  3642072801 ISBN 13:  9783642072802
Editorial: Springer Berlin Heidelberg, 2010
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