Medical Image Watermarking for Tamper Detection in ROI Using LWT and Hashing

Abstract

Security is one of the important characteristics while transmitting the data particularly medical images and patient information over cyberspace without any loss of information. In the proposed method LWT, DCT and SHA-256 hashing techniques are used to provide security to the patient data and to detect tampers in ROI of the medical images. In this paper, medical image is segmented into three regions, region of interest (ROI), region of non interest (RONI) and BORDER regions. ROI is an area that has an important impact on diagnosis, whereas RONI has less or no significance in diagnosis. This paper proposed ROI based tamper detection that embeds hash value of ROI into RONI for authentication and also embed the patient information into RONI for providing security. The experimental results of the proposed method on various medical image databases proved to identify the tampers in medical images. Compared with the existing technique, the proposed method offered high Peak Signal to Noise Ratio (PSNR) approximately 59db for watermarked medical images.