Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorReddy, Dandu Amarnatha-
dc.contributor.authorSahoo, Jaya Prakash-
dc.contributor.authorAri, Samit-
dc.identifier.citation2nd International Conference on Trends in Electronics and Informatics (ICOEI 2018), Tamil Nadu, India, 11 - 12 May, 2018en_US
dc.descriptionCopyright of this document belongs to proceedings publisher.en_US
dc.description.abstractHand gesture recognition system is widely used in the development of human-computer interaction. The vision based hand gesture recognition is achieved by the following steps: preprocessing, feature extraction and classification. The aim of preprocessing stage is to localize the hand region from the image frame. The Laplacian of Gaussian filtering technique along with zero crossing detector is applied on hand gesture images to detect the edges of hand region. This paper proposes a novel feature extraction technique, which is based on local histogram feature descriptor (LHFD). The proposed feature is extracted by finding the local histogram of the gray scale gesture image. This technique uses the whole region of the hand to extract the features. The proposed method is invariant to the scaling and illumination. Two standard datasets viz. Massey University gesture dataset (MUGD) and Jochen Triesch static hand posture database are used to evaluate the recognition performance of the proposed technique. The gesture recognition performance of the proposed technique is 99.5% and 95% on Massey University gesture dataset and Triesch dataset respectively, using multi-class support vector machine (SVM) classifier.en_US
dc.subjectFeature extractionen_US
dc.subjectHand gesture recognitionen_US
dc.subjectHuman computer interactionen_US
dc.subjectLocal histogramen_US
dc.subjectSupport Vector Machineen_US
dc.titleHand Gesture Recognition Using Local Histogram Feature Descriptoren_US
Appears in Collections:Conference Papers

Files in This Item:
File Description SizeFormat 
2018_ICOEI_DAReddy_Hand gesture.pdfConference Paper916.56 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.