Sign Language Research Paper

SIGN LANGUAGE RECOGNITION

S. Gausalya, V.C. Geethaa, C. Hemalatha, G. Manjula

Department of Electronics and Communication Engineering

Avinashilingam University, Coimbatore, India.

ABSTRACT Sign language is the mode of communication for the deaf and dumb people with normal person. But the normal person finds difficulty in understanding the sign language. Our paper mainly focuses on the deaf and dumb people who are bedridden. This paper reduces the difficulty faced by the normal people to understand the sign language, by using flex sensor based on hand glove. Flex sensor detects the hand motions depending on the degree of bend. The flex sensor output which indicates the gesture is processed using microcontroller. The identified sign

The development in embedded system changes our lifestyle in smart way. Sign language is a natural way for communication between normal and deaf and dumb people. In sign language gestures are the physical actions performed by the hearing and speech impaired people to share their thoughts or to convey some information. Sign language is not universal but varies for various countries. The physical sign language communication consists of hand gestures, facial expression, body language, etc. The use of camera is an early developed technology to sense gestures. Due to some challenging problems such as variation of lightning conditions and background, it is difficult to identify the gesture accurately. The intension of sign language recognition is to translate sign language to speech, text as well as message to mobile phone using GSM modem. Ref[1] encloses the digital gloves to reduce the difficulty faced between mute and public. It also presents glove system technology used in biomedical science. Ref[2] recognises Indian sign language based on sensor movement converted to text as well as voice messages. Ref[3] discusses an automatic Arabic sign language recognition system depends on Hidden Markov model. Ref[4] discusses the Human computer interaction with emphasis on software development. Ref[5] presents the gesture recognition for Human robot interaction and Human robot

VI. ACKNOWLEDGEMENT

We would like to express our gratitude for our guide Assistant professor S. Anitha for her continuous support. REFERENCES [1] Praveen Kumar, S. Havalgi, Shruthi Urf Niveditha, “The amazing digital gloves that give voice to the voiceless” IJAET, ISSN: 2231-1963, March 2013. [2] Sachin Bhat, Amruthesh, Ashik, Chidanand Das, Sujith, “Translating Indian sign language to text and voice messages using flex sensors” International Journal of Advanced Research in computer and communication Engineering, Vol.4, issue 5, ISSN 2278-1021, May 2015. [3] Aliaa, A.A.Youssif, Amal Elsayed Aboutabl, Heba Hamdy Ali, “Arabic Sign Language (ArSL) Recognition system using HMM” IJACSA, Vol. 2, No.11, 2011. [4] Beifang Yi, Xusheng Wang, Frederick C. Harris, Jr, Sergiu M. Dascalu, “A Prototype for a sign language interfacing system” IEEE Transactions on Human Machine systems, Vol. 44, No.4, Aug 2014. [5] Seong-Whan Lee, “Automatic Gesture Recognition for Intelligent Human Robot Interaction” proceeding the 7th International Conference on Automatic face Gesture Recognition (FGR’06) ISBN#