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A Real Time Dactylology Based Feature Extractrion for Selective Image Encryption and Artificial Neural Network

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Book cover Image Feature Detectors and Descriptors

Part of the book series: Studies in Computational Intelligence ((SCI,volume 630))

Abstract

Dactylology or Finger Spelling is popularly known as sign speech, is a kind of gesture based language used by the deaf and dumb people to communicate with themselves or with other people in and around them. In many ways FingerSpelling provides a connection between the sign and oral language. Dactylology can also be used for secret communication or can be used by the security personnel to communicate secretly with their counterpart. In the proposed work a two phase encryption technique has been proposed wherein the first phase a ‘Gesture Key’, generated from Indian Sign Language in real time has been used for encrypting the Region of Interests (ROIs) and in the second phase a session key has been used to encrypt the partially encrypted image further. The experimental results show that the scheme provides significant security improvement without compromising the image quality. The speed of encryption and decryption process is quite good. The Performance of the proposed scheme is compared with the few other popular encryption methods to establish the relevance of the work.

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Author information

Authors and Affiliations

  1. Department of CSE, Hooghly Engineering & Technology College, Hooghly, India

    Sirshendu Hore

  2. Department of IT, Techno India, Saltlake, India

    Tanmay Bhattacharya

  3. Department of Information Technology, Techno India College of Technology, Kolkata, India

    Nilanjan Dey

  4. Cairo University, Scientific Research Group, Giza, Egypt

    Aboul Ella Hassanien

  5. Department of ETC, Indian Institute of Engineering Science and Technology, Shibpur, India

    Ayan Banerjee & S. R. Bhadra Chaudhuri

Authors
  1. Sirshendu Hore
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  2. Tanmay Bhattacharya
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  3. Nilanjan Dey
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  4. Aboul Ella Hassanien
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  5. Ayan Banerjee
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  6. S. R. Bhadra Chaudhuri
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Correspondence to Sirshendu Hore .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Luleå University of Technology, Luleå, Sweden

    Ali Ismail Awad

  2. Image and Video Processing Lab, Faculty, South Valley University, Qena, Egypt

    Mahmoud Hassaballah

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© 2016 Springer International Publishing Switzerland

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Hore, S., Bhattacharya, T., Dey, N., Hassanien, A.E., Banerjee, A., Bhadra Chaudhuri, S.R. (2016). A Real Time Dactylology Based Feature Extractrion for Selective Image Encryption and Artificial Neural Network. In: Awad, A., Hassaballah, M. (eds) Image Feature Detectors and Descriptors . Studies in Computational Intelligence, vol 630. Springer, Cham. https://doi.org/10.1007/978-3-319-28854-3_8

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  • DOI: https://doi.org/10.1007/978-3-319-28854-3_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28852-9

  • Online ISBN: 978-3-319-28854-3

  • eBook Packages: EngineeringEngineering (R0)

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