Communication System for Incapacitated using Eye Blink

Authors

  • Usha Rani R Department of Computer Science and Engineering, Dr. Ambedkar Institute of Technology, Bengaluru – 560056, Karnataka, India
  • Vaishali B Department of Computer Science and Engineering, Dr. Ambedkar Institute of Technology, Bengaluru – 560056, Karnataka, India
  • Vandana A S Department of Computer Science and Engineering, Dr. Ambedkar Institute of Technology, Bengaluru – 560056, Karnataka, India
  • Wamiq Yousuf Department of Computer Science and Engineering, Dr. Ambedkar Institute of Technology, Bengaluru – 560056, Karnataka, India
  • Jayalakshmi K Department of Computer Science and Engineering, Dr. Ambedkar Institute of Technology, Bengaluru – 560056, Karnataka, India

Keywords:

MATLAB, Simulink, Biometrics, Erosion, Dilation

Abstract

We describe a real-time technique for eye blink recognition that is based on various video and image processing algorithms. The necessity to disable those who are unable to communicate with humans is the driving force behind this research. The position of the identified face is used to propose an effective eye tracking technique. For managing Android mobile phones, an eye blinking detection based on eyelid status (closed or open) is used. The procedure is applied both with and without a smoothing filter to demonstrate how the accuracy of detection has improved. This project's primary goal is to create a real-time interactive system that can help the paralysed operate household items like lights and fans or play pre-recorded audio messages with a certain amount of eye blinks.

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References

Dunya Goz Hastanesi. Research on “Blink Detection and Eye Tracking for Eye Localization Information”. Wuhan University of Technology, 2018.

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Ahmad Hammoud, Daniel Bourget, etc. “Algorithm of Moving Object Tracking Based on Video Images Sequence”. Journal of Jilin University, 2017.

Veena N. Hegde, Ramya S. Ullagaddimath, Comparison of eye tracking, electrooculography and an auditory brain computer interface for binary communication: a case study with a participant in the locked-in state, (2015).

Ioana Bacivarov, Research on “Eye Monitored Device for disable People”. Master's degree thesis of Zhengzhou University, 2015

Oualla, M., Sadiq, A. and Mbarki, S. 2015. “Comarative study of the methods using Haarlike feature”. International Journal of Engineering Sciences & Research Technology.

Vibodha Yasas Sri Bandara, Prof. Asiri Nanayakkara, et al.” High-Speed Tracking with Kernelized Correlation Filters”. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2014.

Asfand Ateem and T. Bock, “Statistical Models of Appearance for Eye Tracking and EyeBlink Detection and Measurement”, Proceeding of 31st International Sysposium on Automation and Robotics in Construction and Mining (ISARC), Sydney, Australia, (2014).

Nayel Al-Zubi, Z. Murtaza and Ali Shah," Differentiation of signals generated by eye blinks and mouth clenching in a portable brain computer interface system”, Robotic and Emerging Allied Technology in Engineering (2014).

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Published

2022-06-28

How to Cite

[1]
U. Rani R, V. B, V. A S, W. Yousuf, and J. K, “Communication System for Incapacitated using Eye Blink”, pices, pp. 52-54, Jun. 2022.

Issue

2022: PiCES - Special Issue

Section

Articles

License

Copyright (c) 2022 Perspectives in Communication, Embedded-systems and Signal-processing - PiCES

Creative Commons License

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