Review of Finger Spelling Sign Language Recognition
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International Journal of Engineering Trends and Technology (IJETT) | 
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| © 2015 by IJETT Journal | ||
| Volume-22 Number-9 |
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| Year of Publication : 2015 | ||
| Authors : Dr. P.M. Mahajan, Jagruti S. Chaudhari | ||
| DOI : 10.14445/22315381/IJETT-V22P282 |
Citation
Dr. P.M. Mahajan, Jagruti S. Chaudhari"Review of Finger Spelling Sign Language Recognition", International Journal of Engineering Trends and Technology (IJETT), V22(9),400-404 April 2015. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
Abstract
Sign language is a mean of communication among
the deaf people. Indian sign language is used by deaf for
communication purpose in India. Here in this paper, we have
proposed a system using Euclidean distance as a classification
technique for recognition of various Signs of Indian sign
Language. The system comprises of four parts: Image
Acquisition, Pre Processing, Feature Extraction and
Classification. 31 signs including A to Z alphabets & one to five
numbers were considered.
Gesture recognition enables humans to communicate with the
machine and interact naturally without any mechanical devices.
Gesture recognition can be seen as a way for computers to begin
to understand human body language, thus building a richer
bridge between machines and humans than primitive text user
interface or even GUIs (graphical user interfaces), which still
limit the majority of input to keyboard and mouse. Gesture
recognition pertains to recognizing meaningful expressions of
motion by human, involving the hands, arms, face, head, and/or
body. Hand gesture is a method of non-verbal communication for
human beings for its freer expressions much more other than
body parts. Hand gesture recognition has greater importance in
designing an efficient human computer interaction system.
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Keywords
Principle Component Analysis(PCA), Hidden
Markov Model(HMM), Neural Network(NN).