Data hiding in video using efficient quantization scale and low distortion transform

This paper proposes two data hiding approaches using compressed MPEG video. The first approach hides message bits by modulating the quantization scale of a constant bit rate video. A payload of one message bit per macro block is achieved. A second order multivariate regression is used to find an association between macro block-level feature variables and the values of a hidden message bit. The regression model is then used by the decoder to predict the values of the hidden message bits with very high prediction accuracy. The second approach uses the flexible macro block ordering feature of H. 264/AVC to hide message bits. Macro blocks are assigned to arbitrary slice groups according to the content of the message bits to be hidden. A maximum pay load of three message bits per macro block is achieved. In Recent environment Distortion is a major problem and also multi embedding is a problem. In the proposed system, a distortion less technique with the help of prediction based filter is used. In normal prediction based filter has less security problem and retrieval problem due to no change in prediction context to overcome this embedding is done not only into the current pixel but also into its prediction context. Comparisons with previous work reveal that the proposed solutions are superior in terms of message payload while causing less distortion and compression overhead.