Wavelet packet decomposition

hospital servers . In this paper, a one new technique has been introduced which is the hybrid of encryption and wavelet-based ECG steganography technique . Encryption allows privacy and ECG steganography allows to hide one sensitive data into other insensitive host thus guaranteeing the integration between ECG and the rest. Keywords:-ECG ,encryption ,steganography, authentication,wavelet I .INTRODUCTION Population increase has increased number of patients that are

important that patient privacy is protected while data are being transmitted over the public network as well as when they are stored in hospital servers . In this paper, a one new technique has been introduced which is the hybrid of encryption and wavelet-based ECG steganography technique . Encryption allows privacy and ECG steganography allows to hide one sensitive data into other insensitive host thus guaranteeing the integration between ECG and the rest. Keywords:-ECG ,encryption

extracted with minimum error. In terms of PSNR, the visual quality of the watermarked image is exceptional. The proposed algorithm is robust to many image attacks and suitable for copyright protection applications. KEYWORDS: Watermarking, Discrete wavelet transform, Discrete Cosine Transform, PSNR, MSE. I. INTRODUCTION DIGITAL image watermarking has become a necessity in many applications such as data authentication, broadcast

mother wavelet, their coefficients representing 320 ms and 640 ms of the EEG data. According to the paper, due to a variable window size, WT exhibited excellent compression and detection capabilities despite the abstruse nature of artifacts like EMG. The result was obtained as an eight scale multi-resolution display, from which a total of 16 coefficients were taken from levels 2 and 3. It was further processed

Discrete Wavelet Transform for Compressing and Decompressing the Speech Signal Bhavana Pujari1, Prof. S.S.Gundal2 Abstract: The original digital speech signal contains tremendous measure of memory, the main concept for the speech compression algorithm is presented here, in which bit rate of the speech signal is reduced with maintaining signal quality for storage, memory saving or transmission over the long distance. The concentration of this project is to compact the digital speech signal using

CHAPTER 1 INTRODUCTION 1.1 BACKGROUND Research related to medical imaging has produced several techniques for diagnosis purpose like CT, MRI and ultrasound. Each one has its own advantages and disadvantages. Medical imaging is the procedure of creating visual representations of the interior body for medical diagnosis. It helps in revealing internal structures which are hidden inside skin and bones, as well as to treat diseases and for diagnosis purpose. It identifies abnormality through

good for synchronisation and robust for watermarking. Ali Al-Haj [2] in his paper proposed solution for shortcomings of spread spectrum method is overcome by combining it with singular value decomposition for high rate of robustness. To make it more robust the watermark bits are inserted diagonally into wavelet transformed input audio signals and a controlling gain parameter is introduced. This method also

CONTENTS CHAPTER TOPIC PAGE NO. Candidate’s Declaration I Acknowledgements ii Contents 1 Abstract 4 List of Figures 5 List of abbreviations 6 1. INTRODUCTION 1.1. Overview 1.2. Background 1.2.1 The human hand 1.2.1.1 Palm 1.2.1.2 Fingers Bones 1.2.1.3 Wrist and Hand 1.2.1.4 Muscles 1.2.2 Structure of hand 1.2.3 Movements 1.2.4 Grasps

this method is its high immunity to synchronization attack. This algorithm adds an echo on continuous blocks of the cover medium to embed a secret bit. Noise addition aects the echo hiding receiver when the resulting SNR gets below 50dB. Regarding packet loss the BER starts increasing when more than 10on the echo hiding receiver, hence giving a high BER. Time spread echo hiding (TS) is a strong approach compared to conventional echo hiding systems. This system uses the many echoes spreading in time

Abstract: In medical field the disease diagnosis is often made based on the knowledge and experience of the medical practitioner. Due to this there are chances of errors, unwanted biases and also takes longer time in accurate diagnosis of disease. In case of heart disease, its diagnosis is most difficult task. It depends on the careful analysis of different clinical and pathological data of the patient by medical experts, which is complicated process. Due to advancement in