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Hand Gesture Recognition based on Real-time Indian Sign Language

Rakesh.B.S 1 , Tamilarasan.S 2 , Avinash N3

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-7 , Page no. 181-185, Jul-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i7.181185

Online published on Jul 31, 2019

Copyright © Rakesh.B.S, Tamilarasan.S, Avinash N . 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: Rakesh.B.S, Tamilarasan.S, Avinash N, “Hand Gesture Recognition based on Real-time Indian Sign Language,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.7, pp.181-185, 2019.

MLA Style Citation: Rakesh.B.S, Tamilarasan.S, Avinash N "Hand Gesture Recognition based on Real-time Indian Sign Language." International Journal of Computer Sciences and Engineering 7.7 (2019): 181-185.

APA Style Citation: Rakesh.B.S, Tamilarasan.S, Avinash N, (2019). Hand Gesture Recognition based on Real-time Indian Sign Language. International Journal of Computer Sciences and Engineering, 7(7), 181-185.

BibTex Style Citation:
@article{N_2019,
author = {Rakesh.B.S, Tamilarasan.S, Avinash N},
title = {Hand Gesture Recognition based on Real-time Indian Sign Language},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {7 2019},
volume = {7},
Issue = {7},
month = {7},
year = {2019},
issn = {2347-2693},
pages = {181-185},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4741},
doi = {https://doi.org/10.26438/ijcse/v7i7.181185}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i7.181185}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4741
TI - Hand Gesture Recognition based on Real-time Indian Sign Language
T2 - International Journal of Computer Sciences and Engineering
AU - Rakesh.B.S, Tamilarasan.S, Avinash N
PY - 2019
DA - 2019/07/31
PB - IJCSE, Indore, INDIA
SP - 181-185
IS - 7
VL - 7
SN - 2347-2693
ER -

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Abstract

Indian sign language (ISL) could be a language which is used to employ by hearing and speech impaired individuals to speak with other individuals. In this paper we present system which might recognise hand poses and gestures from the Indian sign language (ISL) in real-time mistreatment grid-based options. Here, we are introducing hand gesture recognition system to recognize the gestures and convert them to a natural language. Gesture recognition can be used to communicate merely through gestures without any physical link with the actual machine. Gesture is converted to text which helps deaf-dumb people to communicate with normal people. The system can be programmed in such a way that it can translate gesture to text. The proposed system involves taking the input through the in-built camera. One of the advantage of the system is that the individual can add new sentences based on their comfort and understanding. The output text is displayed on the screen based on the gesture showed to the camera.

Key-Words / Index Term

Hand guesture recognition, unicode, image processing, webcam

References

[1] Joyeeta Singha, Karen Das “Recognition of Indian Sign Language in Live Video”, IJCA Transaction, Vol.70,Issue.19,pp.17-22,2013.
[2] Sakshi Lahoti, Shaily Kayal, Sakshi Kumbhare, Ishani Suradkar, Vikul Pawar1 S. Willium, “Android based American Sign LanguageRecognition System with Skin Segmentation and SVM”, IEEE Transaction, IEEE Transaction,pp.1-6, 2018.
[3] Nico Zengeler, Thomas Kopinski, Uwe Handmann “Hand Gesture Recognition in Automotive Human–Machine Interaction Using Depth Cameras”, MDPI Transaction, pp.1-28, 2012.
[4] Anant Agarwal, Manish K Thakur “Sign Langauage Transaction using Microsoft Kinect “, IEEE Transaction, pp.181-185.
[5] Zaher Hamid Al-Tairi, Rahmita Wirza Rahmat, M. Iqbal Saripan, Puteri Suhaiza Sulaiman, “Skin Segmentation Using YUV and
RGB Color Spaces”,KIPS Tranaction,pp.283-299.
[6] Houssem Lahiani, Mohamed Elleuch, Monji Kherallah, “Real Time Hand Gesture Recognition System forAndroid Devices”, IEEE Transaction,pp.591-596.
[7] Prajwal Paudyal, Ayan Banerjee, and Sandeep K.S. Gupta, “SCEPTRE: a Pervasive, Non-Invasive, and Programmable Gesture Recognition Technology”,Impact Transaction,pp.1-12.
[8] Dipali Rojasara, Nehal Chitaliya, “Real Time Visual Recognition of Indian Sign Language using Wavelet Transform and Principle Component Analysis”,IJSCE Transaction,Vol.4,Issue.3,pp.17-20.
[9] Pooja Kiranalli, Dr. S. R. Gengaje, “Real time Indian Sign Language Number Recognition System”,IJRTER Transaction,Vol.2, Issue.6;pp.200-205.
[10] Kumud Tripathi, Neha Baranwal and G. C. Nandi, “Continuous Indian Sign Language Gesture Recognition and Sentence Formation”,IMCIP Transaction, pp.523-529.
[11] Kartik Shenoy, Tejas Dastane, Varun Rao, Devendra Vyavaharkar, “Real-time Indian Sign Language (ISL) Recognition”, IEEE Transaction,2018
[12] Kartik Shenoy, Tejas Dastane, Varun Rao, Devendra Vyavaharkar, “Real-time Indian Sign Language (ISL) Recognition”,IEEE Transaction,2018,pp.1-9