PhD Seminar by Kris Manohar
TITLE:A Centroid Based Vector Quantization Reversible Data Hiding Technique
DATE: Wednesday 29th May, 2019
TIME: 1:00 p.m.
VENUE:Department Seminar Room, Dept. of Computing and Information Technology, 2nd floor, Natural Sciences Building
ABSTRACT: Security of digital communication is a major concern in today’s digital world. Although cryptographic algorithms can convert sensitive data into cypher texts, attackers have been known to detect, intercept and in some cases break these cypher texts. Steganography addresses this concern by hiding the act of transmitting cypher texts. This is achieved by embedding secret messages into digital objects (e.g., images, texts, audios etc.) without significantly distorting it. Recently, many researchers have proposed algorithms to embed secret information into the output code stream of compression algorithms. This seminar presents a reversible data hiding scheme that exploits the centroid formula. Specifically, this formula is used to define a centroid boundary vector and a centroid state codebook CSCB. Initially, these centroid boundary vectors and CSCBs are the same as the side match vector quantization (SMVQ) algorithm’s boundary vectors and state codebooks SCBs. However as each VQ index is processed the centroid formula is exploited to update the centroid boundary vector and the corresponding CSCB. This coupled with a heuristic to select the best state codebook (i.e., either SCB or CSCB) for each VQ index, generates a highly compressible distribution of index values. The experimental results confirm that the proposed scheme improves recent VQ and SMVQ based reversible data hiding schemes.
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