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
Link To Document :
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