Osamah M. Al-Qershi

Authentication and Data Hiding Using a Hybrid ROI-Based Watermarking Scheme for DICOM Images

Authenticating medical images using watermarking techniques has become a very popular area of research, and some works in this area have been reported worldwide recently. Besides authentication, many data-hiding techniques have been proposed to conceal patient’s data into medical images aiming to reduce the cost needed to store data and the time needed to transmit data when required. In this paper, we present a new hybrid watermarking scheme for DICOM images. In our scheme, two well-known techniques are combined to gain the advantages of both and fulfill the requirements of authentication and data hiding. The scheme divides the images into two parts, the region of interest (ROI) and the region of non-interest (RONI). Patient’s data are embedded into ROI using a reversible technique based on difference expansion, while tamper detection and recovery data are embedded into RONI using a robust technique based on discrete wavelet transform. The experimental results show the ability of hiding patient’s data with a very good visual quality, while ROI, the most important area for diagnosis, is retrieved exactly at the receiver side. The scheme also shows some robustness against certain levels of salt and pepper and cropping noise.

Passive detection of copy-move forgery in digital images: state-of-the-art.

Currently, digital images and videos have high importance because they have become the main carriers of information. However, the relative ease of tampering with images and videos makes their authenticity untrustful. Digital image forensics addresses the problem of the authentication of images or their origins. One main branch of image forensics is passive image forgery detection. Images could be forged using different techniques, and the most common forgery is the copy-move, in which a region of an image is duplicated and placed elsewhere in the same image. Active techniques, such as watermarking, have been proposed to solve the image authenticity problem, but those techniques have limitations because they require human intervention or specially equipped cameras. To overcome these limitations, several passive authentication methods have been proposed. In contrast to active methods, passive methods do not require any previous information about the image, and they take advantage of specific detectable changes that forgeries can bring into the image. In this paper, we describe the current state-of-the-art of passive copy-move forgery detection methods. The key current issues in developing a robust copy-move forgery detector are then identified, and the trends of tackling those issues are addressed.

High capacity data hiding schemes for medical images based on difference expansion

Since the difference expansion (DE) technique was proposed, many researchers tried to, improve its performance in terms of hiding capacity and visual quality. In this paper, a new scheme, based on DE is proposed in order to increase the hiding capacity for medical images. One of the characteristics of medical images, among the other types of images, is the large smooth regions. Taking advantage of this characteristic, our scheme divides the image into two regions; smooth region and non-smooth region. For the smooth region, a high embedding capacity scheme is applied, while the original DE method is applied to the non-smooth region. Sixteen DICOM images of different modalities were used for testing the proposed schemes. The results showed that the proposed scheme has higher hiding capacity compared to the original schemes.

Two-dimensional difference expansion (2D-DE) scheme with a characteristics-based threshold

Fragile watermarking is commonly used for content authentication and tamper detection in digital multimedia. For some critical applications, such as medical systems, the fragile watermarking system should be based on a reversible data hiding scheme. The Difference Expansion (DE) technique is a popular reversible data hiding method. In this paper, we adopt a two-dimensional difference expansion technique (2D-DE) to increase the hiding capacity. The proposed scheme is a fragile block-based scheme where the image is divided into blocks of 4x4 pixels, and these expandable blocks are embedded with 16 bits of payload. In addition to increasing the achieved capacity, we study the effect of selecting the blocks to be embedded according to characteristics such as standard deviation, smoothness, and uniformity. These characteristics can be used as selection criteria to enhance the visual quality. The experimental results demonstrate a very high embedding capacity equals to approximately 1 bit per pixel (bpp). Moreover, a threshold based on the standard deviation can be used to control the hiding capacity and predict the reduction in hiding capacity that will enhance the visual quality.

ROI-based tamper detection and recovery for medical images using reversible watermarking technique

Digital image watermarking is proposed to overcome the problems of security, capacity and cost in health care management systems. Medical images, unlike most of images, require extreme care when embedding additional data within them because the additional information must not affect the image quality and readability. In order to overcome any misdiagnose caused by embedding data into medical images, lossless data hiding techniques have been developed. This paper presents a lossless watermarking technique for Ultrasound (US) images. The proposed technique adopts a high-capacity reversible data hiding scheme based on difference expansion (DE). It can be used to hide patients data hiding and protecting the region of interest (ROI) with tamper detection and recovery capability. The experimental results show that the original image can be exactly extracted from the watermarked one in case of no tampering. In case of tampered ROI, tampered area can be localized and recovered losslessly.

Characteristic region based image steganography using Speeded-Up Robust Features technique

Steganography is the art and science of invisible communication. It is employed in different useful applications, like, safe circulation of secret data and Medical Imaging Systems. For most of the current steganography techniques, information hiding modifies almost all the cover components, which may negatively affect the visual quality of the image and increase the possibility of losing data after the possible attacks. This paper presents a new region based steganography technique, which hides data in the robust regions of the image. First, the Speeded-Up Robust Features (SURF) is used to find the most robust regions in the image. Then, the data embedding is achieved in a content-based manner by modifying the wavelet transform coefficients of those robust regions. Experimental results show the proposed algorithm allows hiding data invisibly with an accurate retrieval in the presence of lossy compression or noise. Moreover, the visual quality of the embedded image is high.

Reversible Watermarking Scheme Based on Two-Dimensional Difference Expansion (2D-DE)

The main advantage of reversible image watermarking is the ability to recover the host image without any loses. Many reversible watermarking schemes were proposed for digital images during the last few years. One of those schemes is difference expansion (DE) which introduced by Jun Tian. In this paper, we adopt a two-dimensional difference expansion technique (2D-DE) in order to increase the hiding capacity by minimizing the size of embedding map while keeping a good visual quality of the watermarked image. The experimental results show higher embedding capacity compared to Alattars scheme with better visual quality using two different metrics.

Enhanced Matching Method for Copy-Move Forgery Detection by Means of Zernike Moments

Copy-move is one of the most popular and efficient operations to create image forgery. Many passive detection techniques have been proposed to detect such a forgery in digital images. The performance of the detection algorithms depends mainly on the features used for matching image blocks or keypoints and the matching method as well. Among the existing detection algorithms, those which employ Zernike moments as features provide remarkable detection accuracy. The robustness of Zernike moments comes from the fact that they are invariant to rotation and scaling. However, Zernike moments-based algorithms can be improved further by adopting more efficient matching methods. In this paper, we propose a new matching method in order to enhance the detection accuracy. Compared to the lexicographical sorting-based matching method, the proposed method improved the detection accuracy by 40 %.

A Comparison between Block-Based and Non Block-Based Watermarking Schemes Based on DWT

In recent years, invisible digital watermarks have been proposed as a method for protecting copyrighted materials such as digital images. Due to its characteristics, one of the problems in digital image watermarking is to decide which technique should be used to hide in an image as many bits of information as possible while ensuring that the embedded watermark can be correctly extracted at the detecting stage, even after various attacks. In this paper we study the effect of dividing the image into blocks and applying a watermarking scheme to each block as an individual image (block-based), and compare it with applying the same watermark to the entire image (non-block-based). Digital wavelet transform (DWT) combined with a proper quantization method is used in this paper and normalized correlation (NC) is used to compare between the two cases after applying number of standard attacks. The results show that block-based watermarking has slightly better performance than non-block-based watermarking.

Copy-Move Forgery Detection Using on Locality Sensitive Hashing and k-means Clustering

Digital images are a main source of information in our modern digital era. However, the easiness of manipulating digital images using simple user-friendly software makes the credibility of images questionable. Copy-Move is one of the most common image forgery types, where a region of an image is copied and pasted into another location of the same image. Such a forgery is simple to achieve but hard to be detected as the pasted region shares the same characteristics with the image. Although plenty of algorithms have been proposed to tackle the copy-move detection problem, a fast and reliable copy-move detection algorithm is not achieved yet. In this paper, a new matching method is proposed which can reduce the detection time and enhance the accuracy of detection as well. Such enhancement is done by clustering image blocks into clusters, and searching for identical blocks within each cluster instead of all image blocks. For that purpose, k-means clustering is used to cluster the image blocks then Locality Sensitive Hashing (LSH) method is used to match the blocks based on Zernike moments. The experimental results shows that the processing time has been reduced to 10% and the detection accuracy has been enhanced as well.