Nowadays the role of data hiding has become more eminent. The data safety on the Internet is known to be a challenge due to frequent hacker attacks and data tampering during transmission. In addition to encryption schemes, data hiding has an important role in secret message transmission, authentication, and copyright protection.
This thesis presents in-depth state-of-the-art data hiding schemes evaluation, and based on the conducted analysis describes the proposed method, which seek the maximum improvement. We utilize a causal predictor and a local activity indicator with two embedding possibilities based on difference expansion and histogram shifting. Moreover, the secret data from Galois field GF(q),q ≤ 2 in order to embed more than one bit per pixel in a single run of the algorithm is considered. We extend our data hiding technique to the transform domain complaint with JPEG coding. In the experimental part, the proposed method is compared with state-of-the-art reversible data hiding schemes on a vast set of test images, where our approach produces better embedding capacity versus image quality performance. We conclude that proposed scheme achieves efficiency in terms of redundancy, which is decreased due to the derived conditions for location map free data embedding, invariability to the choice of predictor, and high payload capacity of more than 1 bit per pixel in a single run of the algorithm
