Poulami Das

Feature analysis for the blind-watermarked electroencephalogram signal in wireless telemonitoring using Alattar's method

The present medical era has seen quite a considerable amount of work been done in tele-monitoring that involves transmission of biomedical signals through wireless media. Exchange of information amongst various hospital systems and medical centers require high level of reliability and security. Signal integrity can be verified, authenticity and achieved control over the copy process can be proved by adding watermark in the original information as multimedia content. Electroencephalography (EEG) is a medical test that records the electrical activity originating from the brain. In this present work, Alattars Method is used for watermark insertion and extraction in an EEG signal without devalorizing its diagnostic parameters. In the second part of the paper, different features in the time domain and the spatial domain are obtained from the original EEG signal, watermarked EEG signal, and the recovered EEG signal.

Feature analysis for the reversible watermarked electrooculography signal using Low distortion Prediction-error Expansion

At present, most of the hospitals and diagnostic centers globally, have started using wireless media for exchange of biomedical information (Electronic Patient Report or hospital logo) for mutual availability of therapeutic case studies. Exchange of information amongst various hospital and medical centers require high level of reliability and security. Signal integrity can be verified, authenticity and achieved control over the copy process can be proved by adding watermark in the original information as multimedia content. Electrooculography (EOG) is a medical test that records the movements and position of the eyes. In this present work, Low distortion Prediction-error Expansion technique is used for watermark insertion and extraction in an EOG signal without devalorizing its diagnostic parameters. It can be seen that in this approach the correlation value of the original watermark and the extracted watermark is quite high. The Signal-to-Noise ratio (SNR) between the original EOG signal and the recovered EOG signal markedly improves which claims the robustness of the method. In the second part of the present work different features of the original EOG signal, watermarked EOG signal and recovered EOG signal are analysed.

A novel Block Matching Algorithmic Approach with smaller block size for motion vector estimation in video compression

The most computationally expensive operation in entire video compression process is Motion Estimation. The challenge is to reduce the computational complexity and time of Exhaustive Search Algorithm without losing too much quality at the output. The proposed work is to implement a novel block matching algorithm for Motion Vector Estimation which performs better than other conventional Block Matching Algorithms such as Three Step Search (TSS), New Three Step Search (NTSS), and Four Step Search (FSS) etc.