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Content Provider | IET Digital Library |
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Author | Rokade, Rajeshree S. Doye, Dharmpal D. |
Abstract | In this study, the authors present a new system for sign language hand gesture recognition. Using video input, the system can recognise any spelled word or alphabetic sequence signed in American Sign Language. The three main steps in the recognition process include detection of the region of interest (the hands), detection of key frames and recognition of gestures from these key frames. The proposed segmentation algorithm distinguishes regions of interest from both uniform and non-uniform backgrounds with an efficiency of 95%. The proposed key frame detection algorithm achieves an efficiency of 96.50%. A rotation-invariant algorithm for feature extraction is additionally proposed, which provides an overall gesture recognition efficiency of 84.2%. |
Starting Page | 381 |
Ending Page | 388 |
Page Count | 8 |
ISSN | 17519659 |
Volume Number | 9 |
e-ISSN | 17519667 |
Issue Number | Issue 5, May (2015) |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-ipr/9/5 |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2012.0691 |
Journal | IET Image Processing |
Publisher Date | 2014-11-04 |
Access Restriction | Open |
Rights Holder | © The Institution of Engineering and Technology |
Subject Keyword | Alphabetic Sequence American Sign Language Computer Vision And Image Processing Technique Feature Extraction Gesture Recognition Image Recognition Key Frame Detection Algorithm Natural Language Processing Rotation Invariant Algorithm Segmentation Algorithm Sign Language Hand Gesture Recognition Spelled Sign Word Recognition Video Input |
Content Type | Text |
Resource Type | Article |
Subject | Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software |
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