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International Conference on Intelligent Systems Design and Applications

ISDA 2017: Intelligent Systems Design and Applications pp 180–190Cite as

Hand Gesture Recognition System Based on Local Binary Pattern Approach for Mobile Devices

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 736))

Abstract

Since the appearance of mobile devices, gesture recognition is being a challenging task in the field of computer vision. In this paper, a simple and fast algorithm for static hand gesture recognition for mobile device is described. The hand pose is recognized by using gentle AdaBoost learning algorithm and Local Binary Pattern features. The system is developed on an Android OS platform. The method used consists of two steps: a real-time gesture captured by a smartphone’s camera and the recognition of the hand gestures. It presents a system based on a real-time hand posture recognition algorithm for mobile devices. The aim of this work is to allow the mobile device interpreting the sign made by the user without the need to touch the screen. In this system, the device is able to perform all necessary steps to recognize hand posture without the need to connect to any distant device.

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Author information

Authors and Affiliations

  1. National School of Electronics and Telecommunications, University of Sfax, Sfax, Tunisia

    Houssem Lahiani

  2. Faculty of Sciences, University of Sfax, Sfax, Tunisia

    Monji Kherallah

  3. Faculty of Economics and Management, University of Sfax, Sfax, Tunisia

    Houssem Lahiani & Mahmoud Neji

  4. Multimedia Information Systems and Advanced Computing Laboratory, Sfax, Tunisia

    Houssem Lahiani & Mahmoud Neji

Authors
  1. Houssem Lahiani
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  2. Monji Kherallah
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  3. Mahmoud Neji
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Corresponding author

Correspondence to Houssem Lahiani .

Editor information

Editors and Affiliations

  1. Machine Intelligence Research Labs , Auburn, Washington, USA

    Ajith Abraham

  2. Department of Computer Science, South Asian University, Chanakyapuri, Delhi, India

    Pranab Kr. Muhuri

  3. Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka , Durian Tunggal, Melaka, Malaysia

    Azah Kamilah Muda

  4. Machine Intelligence Research Labs , Auburn, Washington, USA

    Niketa Gandhi

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Lahiani, H., Kherallah, M., Neji, M. (2018). Hand Gesture Recognition System Based on Local Binary Pattern Approach for Mobile Devices. In: Abraham, A., Muhuri, P., Muda, A., Gandhi, N. (eds) Intelligent Systems Design and Applications. ISDA 2017. Advances in Intelligent Systems and Computing, vol 736. Springer, Cham. https://doi.org/10.1007/978-3-319-76348-4_18

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  • DOI: https://doi.org/10.1007/978-3-319-76348-4_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-76347-7

  • Online ISBN: 978-3-319-76348-4

  • eBook Packages: EngineeringEngineering (R0)

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