[PDF][PDF] Computational intelligence based lossless regeneration (CILR) of blocked gingivitis intraoral image transportation

A Bhowmik, J Dey, A Sarkar, S Karforma - IAES International Journal …, 2019 - academia.edu
IAES International Journal of Artificial Intelligence (IJ-AI), 2019academia.edu
The proposed technique dealt with the generation of n number of partial shares by creating
a unique frame structure by the dentist/physician. Additional feature has been proposed on
the computational lossless transportation. The existing techniques cause a high
computational complexity. The proposed technique ensured the lossless regeneration
property while blocked gingivitis image sharing. Filling of bits have been incorporated to
ensure the static sized homogeneous blocks of intraoral gingivitis image. A graphical …
The proposed technique dealt with the generation of n number of partial shares by creating a unique frame structure by the dentist/physician. Additional feature has been proposed on the computational lossless transportation. The existing techniques cause a high computational complexity. The proposed technique ensured the lossless regeneration property while blocked gingivitis image sharing. Filling of bits have been incorporated to ensure the static sized homogeneous blocks of intraoral gingivitis image. A graphical masking method had been deployed, followed by successive decryption procedure on minimum threshold shares that ensure lossless data regeneration. This can guide the dental treatment with enhanced accuracy. Different types of statistical testing like entropy analysis and histogram analysis confirms the exhibition of authenticity, confidentiality, and integrity of our proposed technique.
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