1,182 research outputs found

    Security of Electronic Patient Record using Imperceptible DCT-SVD based Audio Watermarking Technique

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    Abstract—A robust and highly imperceptible audio watermarkingtechnique is presented to secure the electronic patientrecord of Parkinson’s Disease (PD) affected patient. The proposedDCT-SVD based watermarking technique introduces minimalchanges in speech such that the accuracy in classification of PDaffected person’s speech and healthy person’s speech is retained.To achieve high imperceptibility the voiced part of the speech isconsidered for embedding the watermark. It is shown that theproposed watermarking technique is robust to common signalprocessing attacks. The practicability of the proposed technique istested: by creating an android application to record & watermarkthe speech signal. The classification of PD affected speech is doneusing Support Vector Machine (SVM) classifier in cloud server

    Data Aggregation and Privacy Preserving Using Computational Intelligence

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    An Invisible Logo Watermarking Using Arnold Transform

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    AbstractDigital watermarking is the process of hiding information into the digital content. The method of embedding a smaller logo image into the host image is called logo watermarking. The system proposes an invisible and secure watermarking. The key entered initially determine the location of embedding and thus classified the host image to white and black textured regions. The logo image is then transformed using Arnold transform. Discrete Wavelet Transform (DWT) technique is employed for embedding the transformed logo into the white textured regions. Watermark extraction is done by entering the same key which was already entered during embedding. The system is secure and the logo is imperceptible within the host image. Finally for analysis, PSNR value has been used as a metric for determining the quality of the recovered image

    Blind audio watermarking technique based on two dimensional cellular automata

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    In this paper we propose a new method of digital audio watermarking based on two dimensional cellular automata; the method increases the dimension of the audio and uses cellular automata in generating the key of watermark embedding. The watermarking method is blind, and does not require the original host audio or any of its features to extract the watermark; the watermark can be easily extracted using the right key. The experimental results show that the watermarks are imperceptible; and show a high similarity between the original and the watermarked audio. Cosine similarity and peak signal-to-noise ratio were used to measure the similarity between the original audio and the watermarked audio
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