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Real Time Eye Blink Detection Method for Android Device Controlling

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Computer Vision in Control Systems-4

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 136))

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Abstract

Designing systems to detect the human gestures and movements is an important area in computer vision. In this chapter, a method to detect human eye blink patterns is proposed. Our system detects the user’s eye blink patterns in real time and responds with an action on a mobile device, such as the phone call, text message, and/or an alarm. In this chapter, several image processing techniques are used for detecting human eye blinks. To examine the state of the eyelid, whether it’s opened or closed, the eye state value is used by computing the minimum threshold. The system is able to track the blinking of the eyes efficiently and accurately from the video using the proposed method. This system is user-friendly and easy to operate. The experiment was performed under different conditions by changing the distance from the camera and light in the room. The experimental results showed that the overall detection rate for eye blink is 98%. The proposed method takes only 8 ms as the average execution time for each frame, which makes it work more efficiently in real time applications.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Arkansas at Little Rock, 2801 S. University Avenue, Little Rock, AR, 72204, USA

    Suzan Anwar & Mariofanna Milanova

  2. Department of Biology, University of Arkansas at Little Rock, 2801 S. University Avenue, Little Rock, AR, 72204, USA

    Daniah Al-Nadawi

Authors
  1. Suzan Anwar
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  2. Mariofanna Milanova
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  3. Daniah Al-Nadawi
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Corresponding author

Correspondence to Mariofanna Milanova .

Editor information

Editors and Affiliations

  1. Institute of Informatics and Telecommunications, Reshetnev Siberian State University of Science and Technology, Krasnoyarsk, Russia

    Margarita N. Favorskaya

  2. Faculty of Education, Science, Technology and Mathematics, University of Canberra, Canberra, Aust Capital Terr, Australia

    Lakhmi C. Jain

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Anwar, S., Milanova, M., Al-Nadawi, D. (2018). Real Time Eye Blink Detection Method for Android Device Controlling. In: Favorskaya, M., Jain, L. (eds) Computer Vision in Control Systems-4. Intelligent Systems Reference Library, vol 136. Springer, Cham. https://doi.org/10.1007/978-3-319-67994-5_8

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  • DOI: https://doi.org/10.1007/978-3-319-67994-5_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67993-8

  • Online ISBN: 978-3-319-67994-5

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