Robust Hand Gesture Recognition for Robotic Hand Control
This book focuses on light invariant bare hand gesture recognition while there is no restriction on the types of gestures. Observations and results have confirmed that this research work can be used to remotely control a robotic hand using hand gestures.
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Robust Hand Gesture Recognition for Robotic Hand Control
Robust Hand Gesture Recognition for Robotic Hand Control
Ankit Chaudhary
Robust Hand Gesture Recognition for Robotic Hand Control
123
Ankit Chaudhary Department of Computer Science Northwest Missouri State University Maryville, MO USA
ISBN 978-981-10-4797-8 DOI 10.1007/978-981-10-4798-5
ISBN 978-981-10-4798-5
(eBook)
Library of Congress Control Number: 2017940231 © Springer Nature Singapore Pte Ltd. 2018 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore
“If we knew what it was we were doing, it would not be called research, would it?” —Albert Einstein
Preface
In the past few decades, hand gesture recognition has been considered to be an easy and natural technique for human–machine interaction. Many applications have been developed and enhanced based on hand gesture recognition. These applications range from mobile phones to advanced robotics and from gaming to medical science. In most of the existing commercial and research applications, recognition of hand gestures has been performed by employing sensor-based wired embedded gloves or by using vision-based techniques where colors, chemicals, or paperclips are used on the hand. However, it is desirable to have hand gesture recognition techniques that are applicable to a natural and bare hand, which is normally used for depicting gestures in verbal communication. Another important issue involved in vision-based techniques is their variance to light conditions. As the light conditions change, the threshold used for the segmentation also has to be changed. Bare hand gesture-based applications where no extern
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