Sonika C. Rathi

Bio: Sonika C. Rathi is an academic researcher. The author has contributed to research in topics: Authentication (law) & Digital watermarking. The author has an hindex of 1, co-authored 1 publications receiving 31 citations.

Medical Image Authentication through Watermarking Preserving ROI

Abstract: Telemedicine is a well-known application where enormous amount of medical data need to be securely transferred over the public network and manipulate effectively. Medical image watermarking is an appropriate method used for enhancing security and authentication of medical data, which is crucial and used for further diagnosis and reference. This project focuses on the study of medical image watermarking methods for protecting and authenticating medical data. Additionally, it covers algorithm for application of water marking technique on Region of Non Interest (RONI) of the medical image preserving Region of Interest (ROI). The medical images can be transferred securely by embedding watermarks in RONI allowing verification of the legitimate changes at the receiving end without affecting ROI. Segmentation plays an important role in medical image processing for separating the ROI from medical image. The proposed system separate the ROI from medical image by GUI based approach, which works for all types of medical images. The experimental results show the satisfactory performance of the system to authenticate the medical images preserving ROI.

Wavelet based watermarking approach of hiding patient information in medical image for medical image authentication

Abstract: Watermarking scheme is required to secure data to protect digital contents from unauthorized modifications. Image watermarking scheme can effectively be used in medical image processing to authenticate or investigate the integrity on medical images. In this paper, discrete wavelet transform (DWT) domain and chaotic system based medical image watermarking scheme has been proposed for hiding patient information in medical image to authenticate, in other words, to trace the origin of the image. The patient information has been embedded into the medical images as watermark, without affecting the image quality. DWT has been applied to the host medical image to decompose the image into four sub-bands of low and high frequency components. Chaotic system shows complex behavior and improves the security level of watermarking scheme by providing secret keys. In this paper, logistic map has been used through which chaotic watermark has been obtained, which has been embedded into the low frequency sub-band of medical image. The low frequency sub-band has been divided into 3×3 non overlapping blocks. The chaotic watermark has been embedded into each block by observing neighbor pixels conditions and modifying one of neighbor pixels. Experimental results of the proposed method have been compared with other existing medical image watermarking scheme. From the experimental results, it can be seen that the proposed watermarking scheme outperforms the existing methods. The proposed method achieves high values of peak signal to noise ratio (PSNR) of watermarked image and high values of normalized correlation (NC) of the extracted watermark.

SVM based robust watermarking for enhanced medical image security

Abstract: Medical images are more typical than any other ordinary images, since it stores patient’s information for diagnosis purpose. Such images need more security and confidentiality as total diagnosis depends on it. In telemedicine applications, transmission of medical image via open channel, demands strong security and copyright protection. In our proposed robust watermarking model, a double layer security is introduced to ensure the robustness of embedded data. The embedded data is scrambled using a unique key and then a transform domain based hybrid watermarking technique is used to embed the scrambled data into the transform coefficients of the host image. The data embedding in medical images involves more attention, so that the diagnosis part must not be affected by any modification. Therefore, Support Vector Machine (SVM) is used as a classifier, which classify a medical image into two regions i.e. Non Region of Interest (NROI) and Region of Interest (ROI) to embed watermark data into the NROI part of the medical image, using the proposed embedding algorithm. The objective of the proposed model is to avoid any quality degradation to the medical image. The simulation is performed to measure the Peak Signal to Noise Ratio (PSNR) for imperceptibility and Structural Similarity Index (SSIM) to test the robustness. The experimented result shows, robustness and imperceptibility with SSIM of more than 0.50 and PSNR of more than 35 dB for proposed watermarking model.