Machine Learning and Script Recognition: Machine Vision - Tapa blanda

Saba, Tanzila; Rehman, Amjad

 
9783659111709: Machine Learning and Script Recognition: Machine Vision
Tapa blanda
ISBN 10: 3659111708 ISBN 13: 9783659111709
Editorial: LAP LAMBERT Academic Publishing, 2012

Sinopsis

Machine simulation to recognize handwriting has opened new horizons to improve human-computer interface and perform repetitive task of reading by machines. Despite nearly four decades of research, offline unconstrained cursive script segmentation and recognition remains an open problem. Currently, accuracy of offline cursive script recognition schemes is low particularly for touched script in data entry forms and computationally expensive for real world applications. This book presents latest machine learning techniques for script recognition from pre-processing to post-processing. Character segmentation is a focus of this book as poor segmentation significantly effects accuracy. Several interesting experiments are carried out and results are compared with existing pre-processing and post-processing techniques reported in the state of art using benchmark database such as NIST, IAM and CEDAR. Finally, latest techniques are integrated into a model script recognition system. Remaining problems are also highlighted along with suggestions and recommendations.

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Reseña del editor

Machine simulation to recognize handwriting has opened new horizons to improve human-computer interface and perform repetitive task of reading by machines. Despite nearly four decades of research, offline unconstrained cursive script segmentation and recognition remains an open problem. Currently, accuracy of offline cursive script recognition schemes is low particularly for touched script in data entry forms and computationally expensive for real world applications. This book presents latest machine learning techniques for script recognition from pre-processing to post-processing. Character segmentation is a focus of this book as poor segmentation significantly effects accuracy. Several interesting experiments are carried out and results are compared with existing pre-processing and post-processing techniques reported in the state of art using benchmark database such as NIST, IAM and CEDAR. Finally, latest techniques are integrated into a model script recognition system. Remaining problems are also highlighted along with suggestions and recommendations.

Biografía del autor

Dr. Tanzila Saba earned PhD in document information security from faculty of Computing Universiti Teknologi Malaysia. Her specialization is information management and business intelligence. Currently, she is serving as Assistant prof.in CIS P.S.University KSA. Her more than ten papers are ISI indexed & she is included in Marquis who is who 2012.

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Editorial
LAP LAMBERT Academic Publishing
Año de publicación
2012
Idioma
Inglés
ISBN 10 
3659111708
ISBN 13 
9783659111709
Encuadernación
Tapa blanda
Número de páginas
168
Contacto del fabricante
no disponible
Persona responsable
no disponible