Copyright © 2018 K. Chaitanya, K. Gangadhara Rao. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. International Journal of Engineering & Technology, 7 (4) (2018) 2137-2148 International Journal of Engineering & Technology Website: www.sciencepubco.com/index.php/IJET doi: 10.14419/ijet.v7i4.128554 Research paper A novel approach to medical image watermarking for tamper detection and recovery of region of interest using block compression and checksum K. Chaitanya 1 *, K. Gangadhara Rao 2 1 Assistant Professor, Dept. of CSE, ANU College of Engineering and Technology, Acharya Nagarjuna University, Andhra Pradesh, India 2 Professor, Dept. of CSE, ANU College of Sciences, Acharya Nagarjuna University, Andhra Pradesh, India *Corresponding author E-mail: anu.konda.chaitanya@gmail.com Abstract Effective use of telecommunication and information technology in telemedicine increases the medical services to the patients who are from far away locations. The doctors provide these services by evaluating the patient details & scans like CT Scan, MRI and Ultra Sound. The patient information is exchanged between doctors and patients on a public network which is not safe. In medical image, specific regions are very important to diagnosis known as Region of Interest (ROI) and the rest of the regions are not of much importance known as Region of Non-Interest (RONI). Providing security to the ROI is an important issue hence medical image watermarking is used to transmit the medical images by embedding the ROI into RONI. At the destination, if tampering is found in ROI then recovery of ROI is possible by extracting the ROI from RONI. In the proposed method, the medical image is divided into three parts: BORDER, ROI and RONI. Further the ROI and RONI are divided into blocks and each ROI block is mapped to RONI block by applying division hash function. Lossless block compression technique is applied to each ROI block and embedded the compressed ROI block into mapped RONI block. To provide authenticity to ROI, checksum is calculated for ROI and embed this checksum in BORDER. Again checksum is calculated for each ROI block and placed in mapped RONI blocks. Whether ROI is tampered or not, is to be identified by extracting the checksum from BORDER and if it is tampered then recover the ROI by mapped RONI. The efficiency of the proposed algorithm is estimated by the performance measures mainly Peak Signal to Noise Ratio (PSNR). The proposed method gives good results on average 55 dB of PSNR compared to the previous methods [21] by efficiently compressing the ROI and by checking the authenticity. Keywords: Region of Interest; Region of Non-Interest; Division Hash Function; Lossless Block Compression; Checksum. 1. Introduction In recent days, diagnosing the patients from the far away locations is an important task performed by the doctors through transmission of patient information like patient details and patient scanned reports like CT Scan, MRI and Ultra Sound through internet. This is the main objective of telemedicine applications like teleconsulting and telediagnosis etc. During the transmission of patient details through public network there is a chance of tampering the data in the medical images by the unauthorized persons. Hence, the three security services must be implemented in telemedicine: authenticity, confidentiality and integrity. Therefore, transmission of medical images safely to the destination is an important task needed to perform for diagnosing the patient correctly [1], [2]. For the safe transmission of medical images, medical image watermarking is used [3]. Digital image watermarking is the process of embedding of the relevant information as watermark into the digital image for providing copyright protection, checking authenticity, detection of tampers in the image and recovery of tampered images [4]. Based on the perception of human, watermarking can be divided into visible and invisible watermarking. The watermark that is embedded into the image is visible, that is called as visible watermarking [5], [6]. Visible watermarking is useful for providing copyright protection to the owner. The watermark which is not visible even after embedding into the image is called invisible watermarking [7].Invisible watermarking is useful for copyright protection and authentication. Further invisible watermarking can be divided into fragile, semi-fragile, robust watermarking methods. In fragile watermarking, the watermark that is embedded into the image is sensitive on applying general operations like compression, adding noise, etc. This is suitable for checking the authenticity of ROI. In semi-fragile watermark, the watermark is survived for general operations and it is sensitive to the geometrical attacks. This method is suitable for content authentication [8]. In robust watermarking, the watermark is not removed from cover images after applying the general operations as well as geometrical attacks like scaling, re-sizing etc. It is used for ownership protection [9]. Digital watermarking is implemented by frequency domain techniques and spatial domain techniques. In frequency domain techniques, the watermark is embedded into the image after applying transformation techniques. Some of the transformation techniques are Discrete Fourier Transform, Discrete Wavelet Transform and Discrete Cosine Transform [10]. The main advantage of frequency domain techniques is the robustness of the watermark during the occurrence of attacks. The disadvantage is difficult to implement as it also needed transformation techniques [11], [12]. In spatial domain watermarking, the watermark is embedded directly into the image without conversion. The main