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Reseach Article

Indian Sign Language Recognition System in Marathi Language Text

by Prajakta Rokade, Archana Kadam, Dipti Shinde, Shalini Yadav, Neha Sali
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 182 - Number 30
Year of Publication: 2018
Authors: Prajakta Rokade, Archana Kadam, Dipti Shinde, Shalini Yadav, Neha Sali
10.5120/ijca2018918202

Prajakta Rokade, Archana Kadam, Dipti Shinde, Shalini Yadav, Neha Sali . Indian Sign Language Recognition System in Marathi Language Text. International Journal of Computer Applications. 182, 30 ( Dec 2018), 19-22. DOI=10.5120/ijca2018918202

@article{ 10.5120/ijca2018918202,
author = { Prajakta Rokade, Archana Kadam, Dipti Shinde, Shalini Yadav, Neha Sali },
title = { Indian Sign Language Recognition System in Marathi Language Text },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2018 },
volume = { 182 },
number = { 30 },
month = { Dec },
year = { 2018 },
issn = { 0975-8887 },
pages = { 19-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume182/number30/30218-2018918202/ },
doi = { 10.5120/ijca2018918202 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:12:54.392354+05:30
%A Prajakta Rokade
%A Archana Kadam
%A Dipti Shinde
%A Shalini Yadav
%A Neha Sali
%T Indian Sign Language Recognition System in Marathi Language Text
%J International Journal of Computer Applications
%@ 0975-8887
%V 182
%N 30
%P 19-22
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Sign languages are natural language that used to communicate with deaf and mute people.It is a significant way of communication between normal and deaf and dumb people,which does not require an interpreter. The main objective of this project is to develop a system that helps hearing and speech impaired people to convey their messages to ordinary people. There is much different sign language in the world. But the main focused of system is on Indian Sign Language (ISL) which is on the way of standardization in that the system will concentrated on hand gestures only. Hand gesture is very important part of the body for exchange ideas, messages, thoughts among deaf and dumb people. The proposed system will recognize the Indian hand sign language of words and sentences and translate the signs into Marathi text with images which have been extracted from the input videos. The process will be divided into three parts i.e. preprocessing, feature extraction, classification]. It will initially identify the gestures from Indian Sign language. Finally, the system processes that gesture to recognize character with the help of classification.

References
  1. Umme Santa, Farzana Tazreen and Shayhan Ameen Chowdhury "Bangladeshi Hand Sign Language Recognition from Video" ,2017 20th International Conference of Computer and Information Technology (ICCIT)22-24 December, 2017
  2. Miss. Juhi Ekbote and Mrs. Mahasweta Joshi “Indian Sign Language Recognition Using ANN And SVM Classifier”,2017 International Conference on Innovations in information Embedded and Communication Systems (ICIIECS)
  3. P. Subha Rajam and Dr. G. Balakrishnan “Real Time Indian Sign Language Recognition System to aid Deaf-dumb People”.
  4. Geethu G Nath and Anu.V.S “Embedded Sign Language Interpreter System For Deaf and Dumb People” , 2017 International Conference on Innovations in information Embedded and Communication Systems (ICIIECS).
  5. Dr. Dharaskar Rajiv, Dr. Mr.Futane Pravin, “Hand Gesture Recognition System for numbers uses Thresholding”, 2011.
  6. Priyal SP, Bora PK (2010). “A study on static hand gesture recognition using moments”. In: Proceedings of international conference on signal processing and communications (SPCOM),
  7. Dong-Luong Dinh , Sung young Lee ,Tae Seong K , “Hand Number Gesture Recognition Using the Recognized Hand Parts in Depth Images”, Springer Science Business Media New York 2014.
  8. Akanksha Singh, Saloni Arora Indian Sign Language Gesture Classification as Single or Double Handed Gesture Third International Conference on Image Intonation Processing, 2015.
  9. Anup Kumar, Mevin M. Domini, Sign Language Recognition 3rd In CI Condon Recent Advances in Information Technology I RAIT-2016.
  10. Wu CH, Lin CH (2013), “Depth-based hand gesture recognition for home appliance control”. In: Proceedings of IEEE 17th international symposium on consumer electronics, pp 279–280
  11. Liu X, Fujimura K (2004). “Hand gesture recognition using depth data”. In: Proceedings of IEEE international conference on automatic face and gesture recognition, pp 529–534
  12. Priyal SP, Bora PK (2010). “A study on static hand gesture recognition using moments”. In: Proceedings of international conference on signal processing and communications (SPCOM), pp 1–5
  13. Ren Z, Yuan J, Meng J, Zhang Z (2013). “Robust part-based hand gesture recognition using Kinect sensor”. IEEE Trans. Trans Multimedia 15(5):1110–1120
  14. Barkocy A, Charkari NM (2011) Static hand gesture recognition of Persian sign numbers using thinning method. In: Proceedings of international conference on multimedia technology (ICMT), pp 6548–6551
Index Terms

Computer Science
Information Sciences

Keywords

Computer and information processing Feature extraction Gesture recognition SVM thinning algorithm