DocumentCode
238025
Title
Real time Sign Language Recognition using PCA
Author
Sawant, Shreyashi Narayan ; Kumbhar, M.S.
Author_Institution
Dept. of Electron. & Telecommun., Rajarambapu Inst. of Technol., Islampur, India
fYear
2014
fDate
8-10 May 2014
Firstpage
1412
Lastpage
1415
Abstract
The Sign Language is a method of communication for deaf-dumb people. This paper presents the Sign Language Recognition system capable of recognizing 26 gestures from the Indian Sign Language by using MATLAB. The proposed system having four modules such as: pre-processing and hand segmentation, feature extraction, sign recognition and sign to text and voice conversion. Segmentation is done by using image processing. Different features are extracted such as Eigen values and Eigen vectors which are used in recognition. The Principle Component Analysis (PCA) algorithm was used for gesture recognition and recognized gesture is converted into text and voice format. The proposed system helps to minimize communication barrier between deaf-dumb people and normal people.
Keywords
feature extraction; handicapped aids; image segmentation; mathematics computing; principal component analysis; real-time systems; sign language recognition; Indian sign language; Matlab; PCA; deaf-dumb people; feature extraction; gesture recognition; hand segmentation; principle component analysis; real time sign language recognition; Artificial neural networks; Feature extraction; Image resolution; Image segmentation; Speech recognition; Training; Vectors; Feature Extraction; PCA; Sign Language; Sign Recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Communication Control and Computing Technologies (ICACCCT), 2014 International Conference on
Conference_Location
Ramanathapuram
Print_ISBN
978-1-4799-3913-8
Type
conf
DOI
10.1109/ICACCCT.2014.7019333
Filename
7019333
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