Digital watermarking in medical images

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 05/12/2005.This thesis addresses authenticity and integrity of medical images using watermarking. Hospital Information Systems (HIS), Radiology Information Systems (RIS) and Picture Archiving and Communication Systems (P ACS) now form the information infrastructure for today's healthcare as these provide new ways to store, access and distribute medical data that also involve some security risk. Watermarking can be seen as an additional tool for security measures. As the medical tradition is very strict with the quality of biomedical images, the watermarking method must be reversible or if not, region of Interest (ROI) needs to be defined and left intact. Watermarking should also serve as an integrity control and should be able to authenticate the medical image. Three watermarking techniques were proposed. First, Strict Authentication Watermarking (SAW) embeds the digital signature of the image in the ROI and the image can be reverted back to its original value bit by bit if required. Second, Strict Authentication Watermarking with JPEG Compression (SAW-JPEG) uses the same principal as SAW, but is able to survive some degree of JPEG compression. Third, Authentication Watermarking with Tamper Detection and Recovery (AW-TDR) is able to localise tampering, whilst simultaneously reconstructing the original image

Robust watermarking for magnetic resonance images with automatic region of interest detection

Medical image watermarking requires special considerations compared to ordinary watermarking methods. The first issue is the detection of an important area of the image called the Region of Interest (ROI) prior to starting the watermarking process. Most existing ROI detection procedures use manual-based methods, while in automated methods the robustness against intentional or unintentional attacks has not been considered extensively. The second issue is the robustness of the embedded watermark against different attacks. A common drawback of existing watermarking methods is their weakness against salt and pepper noise. The research carried out in this thesis addresses these issues of having automatic ROI detection for magnetic resonance images that are robust against attacks particularly the salt and pepper noise and designing a new watermarking method that can withstand high density salt and pepper noise. In the ROI detection part, combinations of several algorithms such as morphological reconstruction, adaptive thresholding and labelling are utilized. The noise-filtering algorithm and window size correction block are then introduced for further enhancement. The performance of the proposed ROI detection is evaluated by computing the Comparative Accuracy (CA). In the watermarking part, a combination of spatial method, channel coding and noise filtering schemes are used to increase the robustness against salt and pepper noise. The quality of watermarked image is evaluated using Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM), and the accuracy of the extracted watermark is assessed in terms of Bit Error Rate (BER). Based on experiments, the CA under eight different attacks (speckle noise, average filter, median filter, Wiener filter, Gaussian filter, sharpening filter, motion, and salt and pepper noise) is between 97.8% and 100%. The CA under different densities of salt and pepper noise (10%-90%) is in the range of 75.13% to 98.99%. In the watermarking part, the performance of the proposed method under different densities of salt and pepper noise measured by total PSNR, ROI PSNR, total SSIM and ROI SSIM has improved in the ranges of 3.48-23.03 (dB), 3.5-23.05 (dB), 0-0.4620 and 0-0.5335 to 21.75-42.08 (dB), 20.55-40.83 (dB), 0.5775-0.8874 and 0.4104-0.9742 respectively. In addition, the BER is reduced to the range of 0.02% to 41.7%. To conclude, the proposed method has managed to significantly improve the performance of existing medical image watermarking methods

Preserving data integrity of encoded medical images: the LAR compression framework

International audienceThrough the development of medical imaging systems and their integration into a complete information system, the need for advanced joint coding and network services becomes predominant. PACS (Picture Archiving and Communication System) aims to acquire, store and compress, retrieve, present and distribute medical images. These systems have to be accessible via the Internet or wireless channels. Thus protection processes against transmission errors have to be added to get a powerful joint source-channel coding tool. Moreover, these sensitive data require confidentiality and privacy for both archiving and transmission purposes, leading to use cryptography and data embedding solutions. This chapter introduces data integrity protection and developed dedicated tools of content protection and secure bitstream transmission for medical encoded image purposes. In particular, the LAR image coding method is defined together with advanced securization services

Nested Quantization Index Modulation for Reversible Watermarking and Its Application to Healthcare Information Management Systems

Digital watermarking has attracted lots of researches to healthcare information management systems for access control, patients' data protection, and information retrieval. The well-known quantization index modulation-(QIM-) based watermarking has its limitations as the host image will be destroyed; however, the recovery of medical images is essential to avoid misdiagnosis. In this paper, we propose the nested QIM-based watermarking, which is preferable to the QIM-based watermarking for the medical image applications. As the host image can be exactly reconstructed by the nested QIM-based watermarking. The capacity of the embedded watermark can be increased by taking advantage of the proposed nest structure. The algorithm and mathematical model of the nested QIM-based watermarking including forward and inverse model is presented. Due to algorithms and architectures of forward and inverse nested QIM, the concurrent programs and special processors for the nested QIM-based watermarking are easily implemented

Optimization of medical image steganography using n-decomposition genetic algorithm

Protecting patients' confidential information is a critical concern in medical image steganography. The Least Significant Bits (LSB) technique has been widely used for secure communication. However, it is susceptible to imperceptibility and security risks due to the direct manipulation of pixels, and ASCII patterns present limitations. Consequently, sensitive medical information is subject to loss or alteration. Despite attempts to optimize LSB, these issues persist due to (1) the formulation of the optimization suffering from non-valid implicit constraints, causing inflexibility in reaching optimal embedding, (2) lacking convergence in the searching process, where the message length significantly affects the size of the solution space, and (3) issues of application customizability where different data require more flexibility in controlling the embedding process. To overcome these limitations, this study proposes a technique known as an n-decomposition genetic algorithm. This algorithm uses a variable-length search to identify the best location to embed the secret message by incorporating constraints to avoid local minimum traps. The methodology consists of five main phases: (1) initial investigation, (2) formulating an embedding scheme, (3) constructing a decomposition scheme, (4) integrating the schemes' design into the proposed technique, and (5) evaluating the proposed technique's performance based on parameters using medical datasets from kaggle.com. The proposed technique showed resistance to statistical analysis evaluated using Reversible Statistical (RS) analysis and histogram. It also demonstrated its superiority in imperceptibility and security measured by MSE and PSNR to Chest and Retina datasets (0.0557, 0.0550) and (60.6696, 60.7287), respectively. Still, compared to the results obtained by the proposed technique, the benchmark outperforms the Brain dataset due to the homogeneous nature of the images and the extensive black background. This research has contributed to genetic-based decomposition in medical image steganography and provides a technique that offers improved security without compromising efficiency and convergence. However, further validation is required to determine its effectiveness in real-world applications

A review and open issues of diverse text watermarking techniques in spatial domain

Nowadays, information hiding is becoming a helpful technique and fetches more attention due to the fast growth of using the internet; it is applied for sending secret information by using different techniques. Watermarking is one of major important technique in information hiding. Watermarking is of hiding secret data into a carrier media to provide the privacy and integrity of information so that no one can recognize and detect it's accepted the sender and receiver. In watermarking, many various carrier formats can be used such as an image, video, audio, and text. The text is most popular used as a carrier files due to its frequency on the internet. There are many techniques variables for the text watermarking; each one has its own robust and susceptible points. In this study, we conducted a review of text watermarking in the spatial domain to explore the term text watermarking by reviewing, collecting, synthesizing and analyze the challenges of different studies which related to this area published from 2013 to 2018. The aims of this paper are to provide an overview of text watermarking and comparison between approved studies as discussed according to the Arabic text characters, payload capacity, Imperceptibility, authentication, and embedding technique to open important research issues in the future work to obtain a robust method

A Survey on Recent Reversible Watermarking Techniques

Watermarking is a technique to protect the copyright of digital media such as image, text, music and movie. Reversible watermarking is a technique in which watermark can be removed to completely restore the original image. Reversible watermarking of digital content allows full extraction of the watermark along with the complete restoration of the original image. For the last few years, reversible watermarking techniques are gaining popularity due to its applications in important and sensitive areas like military communication, healthcare, and law-enforcement. Due to the rapid evolution of reversible watermarking techniques, a latest review of recent research in this field is highly desirable. In this survey, the performances of different latest reversible watermarking techniques are discussed on the basis of various characteristics of watermarking

Data hiding techniques in steganography using fibonacci sequence and knight tour algorithm

The foremost priority in the information and communication technology era, is achieving an efficient and accurate steganography system for hiding information. The developed system of hiding the secret message must capable of not giving any clue to the adversaries about the hidden data. In this regard, enhancing the security and capacity by maintaining the Peak Signal-to-Noise Ratio (PSNR) of the steganography system is the main issue to be addressed. This study proposed an improved for embedding secret message into an image. This newly developed method is demonstrated to increase the security and capacity to resolve the existing problems. A binary text image is used to represent the secret message instead of normal text. Three stages implementations are used to select the pixel before random embedding to select block of (64 × 64) pixels, follows by the Knight Tour algorithm to select sub-block of (8 × 8) pixels, and finally by the random pixels selection. For secret embedding, Fibonacci sequence is implemented to decomposition pixel from 8 bitplane to 12 bitplane. The proposed method is distributed over the entire image to maintain high level of security against any kind of attack. Gray images from the standard dataset (USC-SIPI) including Lena, Peppers, Baboon, and Cameraman are implemented for benchmarking. The results show good PSNR value with high capacity and these findings verified the worthiness of the proposed method. High complexities of pixels distribution and replacement of bits will ensure better security and robust imperceptibility compared to the existing systems in the literature