Mobile Robot Digital Landmarks Recognition and Finger Writing Maneuver - Couverture souple

Shih, Ching-Long; Ku, Yu-Te

 
9783330347632: Mobile Robot Digital Landmarks Recognition and Finger Writing Maneuver
Couverture souple
ISBN 10 : 3330347635 ISBN 13 : 9783330347632
Editeur : LAP LAMBERT Academic Publishing, 2017

Synopsis

This book presents an image-based mobile robot guidance system in an indoor space with installed artificial ceiling landmarks and the robot is maneuver by a vision-based fingertip-writing character recognition system. The overall system, including an omni-directional mobile robot motion control, landmark image processing and image recognition, is implemented on a single FPGA chip with one CMOS image sensor. The proposed feature representation of the artificial ceiling land-marks is invariant with respect to rotation and translation. To enhance recognition accuracy, landmark classification is performed after the mobile robot is moved to a position such that the ceiling landmark is located in the upright-top corner position of the robot’s camera image. The accuracy of the proposed artificial ceiling landmark recognition system using nearest neighbor classification is 100% in our experiments and the proposed fingertip-writing recognition system provides an easy-to-use and accurate visual character input method.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

This book presents an image-based mobile robot guidance system in an indoor space with installed artificial ceiling landmarks and the robot is maneuver by a vision-based fingertip-writing character recognition system. The overall system, including an omni-directional mobile robot motion control, landmark image processing and image recognition, is implemented on a single FPGA chip with one CMOS image sensor. The proposed feature representation of the artificial ceiling land-marks is invariant with respect to rotation and translation. To enhance recognition accuracy, landmark classification is performed after the mobile robot is moved to a position such that the ceiling landmark is located in the upright-top corner position of the robot’s camera image. The accuracy of the proposed artificial ceiling landmark recognition system using nearest neighbor classification is 100% in our experiments and the proposed fingertip-writing recognition system provides an easy-to-use and accurate visual character input method.

Biographie de l'auteur

Ching-Long Shih received the BS and MS degrees form the National Chiao-Tung University, Hsinchu, Taiwan in 1980 and 1984, respectively, and the PhD degree in Electrical Engineering from the Ohio State University, Columbus, Ohio, USA in 1988.He is currently a Professor in the Department EE, National Taiwan University of Science and Technology.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2017
Langue
anglais
ISBN 10 
3330347635
ISBN 13 
9783330347632
Reliure
Broché
Nombre de pages
56
Coordonnées du fabricant
non disponible
Personne responsable
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