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Indian Sign Language Recognition System in Marathi Language Text

Prajakta Rokade1 , Neha Sali2 , Dipti Shinde3 , Shalini Yadav4

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-5 , Page no. 881-885, May-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i5.881885

Online published on May 31, 2019

Copyright © Prajakta Rokade, Neha Sali, Dipti Shinde, Shalini Yadav . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Prajakta Rokade, Neha Sali, Dipti Shinde, Shalini Yadav, “Indian Sign Language Recognition System in Marathi Language Text,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.5, pp.881-885, 2019.

MLA Style Citation: Prajakta Rokade, Neha Sali, Dipti Shinde, Shalini Yadav "Indian Sign Language Recognition System in Marathi Language Text." International Journal of Computer Sciences and Engineering 7.5 (2019): 881-885.

APA Style Citation: Prajakta Rokade, Neha Sali, Dipti Shinde, Shalini Yadav, (2019). Indian Sign Language Recognition System in Marathi Language Text. International Journal of Computer Sciences and Engineering, 7(5), 881-885.

BibTex Style Citation:
@article{Rokade_2019,
author = {Prajakta Rokade, Neha Sali, Dipti Shinde, Shalini Yadav},
title = {Indian Sign Language Recognition System in Marathi Language Text},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2019},
volume = {7},
Issue = {5},
month = {5},
year = {2019},
issn = {2347-2693},
pages = {881-885},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4331},
doi = {https://doi.org/10.26438/ijcse/v7i5.881885}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i5.881885}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4331
TI - Indian Sign Language Recognition System in Marathi Language Text
T2 - International Journal of Computer Sciences and Engineering
AU - Prajakta Rokade, Neha Sali, Dipti Shinde, Shalini Yadav
PY - 2019
DA - 2019/05/31
PB - IJCSE, Indore, INDIA
SP - 881-885
IS - 5
VL - 7
SN - 2347-2693
ER -

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Abstract

Sign language is a natural language that is 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 are different sign languages in the world. But the main focus of system is on Indian Sign Language (ISL) which is on the way of standardization. This system will concentrate on hand gestures only. Hand gesture is very important part of the body for exchanging 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 is divided into three parts i.e. preprocessing, feature extraction, classification. It will initially identify the gestures from Indian Sign language. Finally, the system processes the gesture to recognize character with the help of classification.

Key-Words / Index Term

Image processing, Feature extraction, Gesture recognition, SVM, thinning algorithm

References

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[2] Miss. Juhi Ekbote and Mrs. Mahasweta Joshi “Indian Sign Language Recognition Using ANN And SVM Classifier”, International Conference on Innovations in information Embedded and Communication Systems (ICIIECS), 2017.
[3] P. Subha Rajam and Dr. G. Balakrishnan “Real Time Indian Sign Language Recognition System to aid Deaf-dumb People”.
[4] Dr. Dharaskar Rajiv, Dr. Mr.Futane Pravin, “Hand Gesture Recognition System for numbers uses Thresholding”, 2011.
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[6] Akanksha Singh, Saloni Arora.“ Indian Sign Language Gesture Classification as Single or Double Handed Gesture” In: Third International Conference on Image Intonation Processing, 2015.
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