Wearable Based Sign Language Recognition

Authors

  • B N Meghana Department of Electrical and Electronic Engineering, Sai Vidya Institute of Technology, Bangalore
  • Priyanka R Vidur Department of Electrical and Electronic Engineering, Sai Vidya Institute of Technology, Bangalore
  • Meghana K Jambagi Department of Electrical and Electronic Engineering, Sai Vidya Institute of Technology, Bangalore
  • Basavanagowda N Department of Electrical and Electronic Engineering, Sai Vidya Institute of Technology, Bangalore
  • T G Manjunath Department of Electrical and Electronic Engineering, Sai Vidya Institute of Technology, Bangalore

DOI:

https://doi.org/10.5281/zenodo.4737714

Keywords:

Sign Language, ATM, Hand Gestures, Survey, Otsu, Gloves, Wearables

Abstract

Money is one of the most required components on one’s life. Be it a normal person or a physically challenged individual, finance is required to lead life ahead. Usually ATMs are utilised for withdrawing money from a bank account, but the visually impaired might have a tough time accessing these machines. Simple sign languages can be used by the blind to withdraw the money from the ATMs thus making their lives easy. Here are a few papers that have worked on sign language recognition.

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References

Sasirekha, K. & Nivetha, M. & Indumathi, A. & Renukadevi, D.. (2016). Atm machine for blind people. 14. 911-916.

Singanamalla, Sudheesh & Potluri, Venkatesh & Scott, Colin & Medhi-Thies, Indrani. (2019). PocketATM: understanding and improving ATM accessibility in India. 1-11. 10.1145/3287098.3287106.

B. G. Lee and S. M. Lee, "Smart Wearable Hand Device for Sign Language Interpretation System With Sensors Fusion," in IEEE Sensors Journal, vol. 18, no. 3, pp. 1224-1232, 1 Feb.1, 2018.

A. Arif, S. T. H. Rizvi, I. Jawaid, M. A. Waleed and M. R. Shakeel, "Techno-talk: An American Sign Language (ASL) Translator," 2016 International Conference on Control, Decision and Information Technologies (CoDIT), St. Julian's, 2016, pp. 665-670.

P. Maragos and R. Schafer, "Applications of morphological filtering to image analysis and processing," ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing, Tokyo, Japan, 1986, pp. 2067-2070.

N. Otsu, "A Threshold Selection Method from Gray-Level Histograms," in IEEE Transactions on Systems, Man, and Cybernetics, vol. 9, no. 1, pp. 62-66, Jan. 1979.

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Published

2021-04-05

How to Cite

[1]
B. N. Meghana, P. R. Vidur, M. K. Jambagi, B. N, and T. G. Manjunath, “Wearable Based Sign Language Recognition”, pices, vol. 4, no. 12, pp. 295-297, Apr. 2021.

Issue

Vol. 4 No. 12 (2021): Issue 12 - March 2021

Section

Articles

URN

http://nbn-resolving.de/urn:nbn:de:101:1-2021050420325480506121

License

Copyright (c) 2021 Perspectives in Communication, Embedded-systems and Signal-processing - PiCES/ WorldServe Online

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.