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Indian Sign Language Recognition Using Framework of Skin Color Detection, Viola- Jones Algorithm, Correlation-Coefficient Technique and Distance Based Neuro-Fuzzy Classification Approach

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Emerging Technology Trends in Electronics, Communication and Networking (ET2ECN 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1214))

Abstract

Sign language recognition is exceptionally a vast in the research field where one can utilize a few procedures like glove based method, image based method, sensors and so on, to acquire the signs. In this paper we have undertaken an image based technique to recognize sign language. In this paper we have proposed a framework which is comprised of 4 phases: in first phase we have applied various image processing techniques to smooth the image. Further we have used skin color detection and Viola-Jones algorithm, which are used to segment a face part and hand part from the image. Second phase consist of a distance count method and Correlation-Coefficient method to extract distance and similarity index features respectively. These features continue to 3rd phase to classify and identify the sign using Neuro-Fuzzy classification algorithm. Finally in the 4th phase we have used Natural Language Processing (NLP) to display the final word. Presented framework has been implemented on MATLAB. We have tested 20 videos (total 100 images) of different family relation signs and our experimental result is 95% accuracy.

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Authors and Affiliations

  1. Sardar Patel University, Vallabh Vidyanagar, India

    Hemina Bhavsar & Jeegar Trivedi

Authors
  1. Hemina Bhavsar
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  2. Jeegar Trivedi
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Correspondence to Hemina Bhavsar .

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Editors and Affiliations

  1. Sardar Vallabhbhai National Institute of Technology, Surat, India

    Shilpi Gupta

  2. Sardar Vallabhbhai National Institute of Technology, Surat, India

    Jignesh N. Sarvaiya

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Bhavsar, H., Trivedi, J. (2020). Indian Sign Language Recognition Using Framework of Skin Color Detection, Viola- Jones Algorithm, Correlation-Coefficient Technique and Distance Based Neuro-Fuzzy Classification Approach. In: Gupta, S., Sarvaiya, J. (eds) Emerging Technology Trends in Electronics, Communication and Networking. ET2ECN 2020. Communications in Computer and Information Science, vol 1214. Springer, Singapore. https://doi.org/10.1007/978-981-15-7219-7_20

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  • DOI: https://doi.org/10.1007/978-981-15-7219-7_20

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-7218-0

  • Online ISBN: 978-981-15-7219-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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