International Journal of Computer Applications (0975 – 8887) Volume 104 – No 11, October 2014 8 A Semi-Fragile Blind Digital Watermarking Technique for Medical Image File Authentication using Stationary Wavelet Transformation Tanmay Bhattacharya Assoc. Professor Dept. of IT, Techno India, Salt Lake, Kolkata, West Bengal, India Sirshendu Hore Asst. Professor Dept. of CSE, Hooghly Engineering & Technology College, Hooghly, Hooghly, West Bengal, India S. R. Bhadra Chaudhuri Professor, Dept of ETC, Indian Institute of Engineering Science and Technology, Shibpur, West Bengal, India ABSTRACT Electronically stored health information enhances resource sharing, help us to reduce the number of errors, speed up clinical communication and assist doctors in diagnosis and treatment. Medical image watermarking is a special type of watermarking technique where the watermarked medical images should not differ perceptually from the original images, because the diagnosis must not be affected due to the presence of watermark. This paper presents a new blind watermarking technique for medical image using Stationary Wavelet Transformation (SWT). In the proposed method multiple watermarks containing patient’s information are embedded and original image is not needed for the extraction of those watermarks. General Terms Watermarking, Medical Image, SWT Keywords SWT, Pseudo Random Noise, SNR, ISWT. 1. INTRODUCTION Medical image watermarking [3, 5, 6, 8 and 9] is used to authenticate, investigate the integrity of medical images. The biggest challenge in medical image watermarking is that, the image may not undergo any major degradation that will affect the quality of images with visible alteration to their original form. Medical image watermarking systems can be broken into three broad categories: robust, fragile, and semi-fragile. Robust watermarks are robust under most image processing methods and can be extracted from heavily attacked watermarked image. Fragile watermarks are destroyed by random image processing methods. The change in watermark is easy to be detected, thus can provide information for image completeness. Semi-fragile watermarks combine the properties of both robust and fragile watermarks like robust methods; they can tolerate some degree of change to the watermarked image. There are different watermarking technologies both in spatial [4, 7 and 14] and frequency-domain [13]. Compared to spatial-domain watermarking, frequency domain watermarking are more popular because of robustness and imperceptibility. Embedding watermarks within DCT coefficients [10, 13 and 15] or DWT coefficient [10, 11, and 17] is a common approach. Multiple watermark embedding [8, 16 and 18] has also been used by a number of researchers. Multiple watermarking systems have the advantages that different watermarks can be applied for different purposes. In the blind [12] watermarking technique original image is not needed for the extraction of the watermarks. 1.1 Discrete Stationary Wavelet Transform Discrete Stationary wavelet transform or SWT [1, 2, 11 and 19] provides efficient numerical solutions in the signal processing applications. It was independently developed by several researchers and under different names, such as undecimated wavelet transform, the shift invariant wavelet transform and the redundant wavelet transform.SWT performs a multilevel stationary wavelet decomposition using either a specific orthogonal wavelet or specific orthogonal Wavelet decomposition filters. SWT is almost similar to the Discrete Wavelet Transform (DWT) where the high-pass and low-pass filters are applied to the input signal at each level (3 and 6). However, in the SWT, the output signal is never down sampled (not decimated). Instead, at each level the filters are up sampled. Figure 1 illustrated the block diagram of SWT decomposition. Fig 1: Block Diagram of SWT Decomposition The second section gives the proposed algorithm and the third section explains the algorithm in detail. Fourth section shows the experimental results and the fifth section discussed about the proposed method. 2. PROPOSED ALGORITHM 2.1 Watermark Embedding Process Step 1: Color medical image is decomposed into RGB color components. Step 2: Two-Dimensional SWT is applied on individual color components (R, G, & B). Step 3: Three binary images, one containing patient’s name in short form; second containing patient’s blood group and third