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Erschienen in:
Detection and Description of Image Features: An Introduction Kapitel lesen Erstes Kapitel lesen

2016 | OriginalPaper | Buchkapitel

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

verfasst von : Sirshendu Hore, Tanmay Bhattacharya, Nilanjan Dey, Aboul Ella Hassanien, Ayan Banerjee, S. R. Bhadra Chaudhuri

Erschienen in: Image Feature Detectors and Descriptors

Verlag: Springer International Publishing

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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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Vorheriges Kapitel Redundancy Elimination in Video Summarization
Nächstes Kapitel Spectral Reflectance Images and Applications
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Metadaten
Titel
A Real Time Dactylology Based Feature Extractrion for Selective Image Encryption and Artificial Neural Network
verfasst von
Sirshendu Hore
Tanmay Bhattacharya
Nilanjan Dey
Aboul Ella Hassanien
Ayan Banerjee
S. R. Bhadra Chaudhuri
Copyright-Jahr
2016
Buch
Image Feature Detectors and Descriptors

Print ISBN: 978-3-319-28852-9

Electronic ISBN: 978-3-319-28854-3

Copyright-Jahr: 2016

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

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