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Real Time Hand Gesture Recognition for Differently-Abled Using Deep Learning

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Recent Trends in Image Processing and Pattern Recognition (RTIP2R 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1035))

Abstract

In the field of Computer science, Gesture recognition is an alternative user interface for providing real-time data to a computer. This paper focuses on a system which provides the communication between the vocally impaired people and the normal people of the society by translating Sign Language system into Text and Speech in English. The system can recognize one handed sign representation of the standard alphabets (A–Z) and numeric values (0–9). In this paper we used OpenCV for gesture capture through web camera and deep learning algorithms to train and recognize the gesture. The system is very efficient and consistent with respect to output.

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References

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Authors and Affiliations

  1. BMS Institute of Technology and Management, Bengaluru, India

    C. N. Gireesh Babu, K. T. Chandrashekhara & T. N. Manjunath

  2. University of Horticultural Sciences, Bagalkot, India

    M. Thungamani

Authors
  1. C. N. Gireesh Babu
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  2. M. Thungamani
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  3. K. T. Chandrashekhara
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  4. T. N. Manjunath
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Corresponding author

Correspondence to C. N. Gireesh Babu .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of South Dakota, Vermillion, SD, USA

    K. C. Santosh

  2. Solapur University, Solapur, India

    Ravindra S. Hegadi

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Cite this paper

Gireesh Babu, C.N., Thungamani, M., Chandrashekhara, K.T., Manjunath, T.N. (2019). Real Time Hand Gesture Recognition for Differently-Abled Using Deep Learning. In: Santosh, K., Hegadi, R. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2018. Communications in Computer and Information Science, vol 1035. Springer, Singapore. https://doi.org/10.1007/978-981-13-9181-1_29

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  • DOI: https://doi.org/10.1007/978-981-13-9181-1_29

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9180-4

  • Online ISBN: 978-981-13-9181-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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