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

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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