000823049 000__ 04247cam\a2200457Ii\4500
000823049 001__ 823049
000823049 005__ 20230306143946.0
000823049 006__ m\\\\\o\\d\\\\\\\\
000823049 007__ cr\cn\nnnunnun
000823049 008__ 170608s2018\\\\si\a\\\\ob\\\\000\0\eng\d
000823049 019__ $$a1005135860$$a1011796738
000823049 020__ $$a9789811047985$$q(electronic book)
000823049 020__ $$a9811047987$$q(electronic book)
000823049 020__ $$z9789811047978
000823049 0247_ $$a10.1007/978-981-10-4798-5$$2doi
000823049 035__ $$aSP(OCoLC)ocn989513208
000823049 035__ $$aSP(OCoLC)989513208$$z(OCoLC)1005135860$$z(OCoLC)1011796738
000823049 040__ $$aN$T$$beng$$erda$$epn$$cN$T$$dGW5XE$$dN$T$$dYDX$$dCOO$$dAZU$$dUAB$$dU3W$$dCAUOI
000823049 049__ $$aISEA
000823049 050_4 $$aTJ211
000823049 08204 $$a629.8/933$$223
000823049 1001_ $$aChaudhary, Ankit,$$eauthor.
000823049 24510 $$aRobust hand gesture recognition for robotic hand control /$$cAnkit Chaudhary.
000823049 264_1 $$aSingapore :$$bSpringer,$$c[2018]
000823049 300__ $$a1 online resource (xxi, 96 pages) :$$billustrations.
000823049 336__ $$atext$$btxt$$2rdacontent
000823049 337__ $$acomputer$$bc$$2rdamedia
000823049 338__ $$aonline resource$$bcr$$2rdacarrier
000823049 347__ $$atext file$$bPDF$$2rda
000823049 504__ $$aIncludes bibliographical references.
000823049 5050_ $$aChapter 1: Introduction -- Chapter 2: Scientific Goals -- Chapter 3: State of the Art -- Chapter 4: Hand Image Segmentation -- Chapter 5: Light Invariant Hand Gesture Recognition -- Chapter 6: Fingertips Detection -- Chapter 7: Bent Finger?s Angles Calculation -- Chapter 8: Both Hands? Angles Calculation -- Chapter 9: Conclusions.
000823049 506__ $$aAccess limited to authorized users.
000823049 520__ $$aThis 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. The system developed here is also able to recognize hand gestures in different lighting conditions. The pre-processing is performed by developing an image-cropping algorithm that ensures only the area of interest is included in the segmented image. The segmented image is compared with a predefined gesture set which must be installed in the recognition system. These images are stored and feature vectors are extracted from them. These feature vectors are subsequently presented using an orientation histogram, which provides a view of the edges in the form of frequency. Thereby, if the same gesture is shown twice in different lighting intensities, both repetitions will map to the same gesture in the stored data. The mapping of the segmented image's orientation histogram is firstly done using the Euclidian distance method. Secondly, the supervised neural network is trained for the same, producing better recognition results. An approach to controlling electro-mechanical robotic hands using dynamic hand gestures is also presented using a robot simulator. Such robotic hands have applications in commercial, military or emergency operations where human life cannot be risked. For such applications, an artificial robotic hand is required to perform real-time operations. This robotic hand should be able to move its fingers in the same manner as a human hand. For this purpose, hand geometry parameters are obtained using a webcam and also using KINECT. The parameter detection is direction invariant in both methods. Once the hand parameters are obtained, the fingers? angle information is obtained by performing a geometrical analysis. An artificial neural network is also implemented to calculate the angles. These two methods can be used with only one hand, either right or left. A separate method that is applicable to both hands simultaneously is also developed and fingers angles are calculated. The contents of this book will be useful for researchers and professional engineers working on robotic arm/hand systems.
000823049 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed June 8, 2017).
000823049 650_0 $$aRobot hands$$xControl.
000823049 650_0 $$aRobust control.
000823049 77608 $$iPrint version: $$z9789811047978
000823049 852__ $$bebk
000823049 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-981-10-4798-5$$zOnline Access$$91397441.1
000823049 909CO $$ooai:library.usi.edu:823049$$pGLOBAL_SET
000823049 980__ $$aEBOOK
000823049 980__ $$aBIB
000823049 982__ $$aEbook
000823049 983__ $$aOnline
000823049 994__ $$a92$$bISE