Isbn: 9783330347632 - mobile robot digital landmarks recognition and finger writing maneuver (5 Ergebnisse)

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  • Sprache: Englisch

    Verlag: LAP LAMBERT Academic Publishing, 2017

    3330347635 / 9783330347632

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    Paperback. Zustand: Brand New. 56 pages. 8.66x5.91x0.13 inches. In Stock.

  • Sprache: Englisch

    Verlag: LAP LAMBERT Academic Publishing Jul 2017, 2017

    3330347635 / 9783330347632

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    Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 56 pp. Englisch.…

  • Sprache: Englisch

    Verlag: LAP LAMBERT Academic Publishing, 2017

    3330347635 / 9783330347632

    • Softcover
    • Print-on-Demand

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    Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.…

  • Sprache: Englisch

    Verlag: LAP LAMBERT Academic Publishing, 2017

    3330347635 / 9783330347632

    • Softcover
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    Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Shih Ching-LongChing-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, Colum.…

  • Sprache: Englisch

    Verlag: LAP LAMBERT Academic Publishing Jul 2017, 2017

    3330347635 / 9783330347632

    • Softcover
    • Print-on-Demand

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    Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 56 pp. Englisch.…