Verification of image content integrity by using dual watermarking on wavelets domain

일반적인 워터마킹 기술들은 영상의 특성을 고려하지 않은 채 신체 책인 영상에 워터마크를 삽입하는 경우가 많다 본 논문에서는 워터마킹 알고리즘을 웨이브렛을 기반으로 구현을 하였으며, 견고한 워터마크 삽입을 위해 Multi-Threshold Watermark Coding(MTWC)의 원리에 기초하여 Region of Interest(ROI)라고 불리우는 영상의 영역에 큰 계수를 찾아 워터마크를 삽입하게 된다. 이때 Human Visual System(HVS)을 이용하여 견고성과 비가시성의 향상을 도모하였다. 워터마크 삽입대역은 중주파 대역에 삽입을 하게 되는데 중주파 대역에 삽입한 워터마크는 어떠한 영상 처리과정 후에도 높은 비율의 추출을 보였으며, 워터마크가 삽입된 영상의 왜곡정도도 다른 대역보다 상대적으로 적게 나타나므로 중주파 대역에 워터마크를 삽입하였다. 워터마크는 의사 랜덤 시퀀스(Pseudo Random Sequence)로 구성되어 있고 워터마크의 검출은 Cox의 유사도 측정식을 이용하여 워터마크의 삽입여부를 판단한다 General watermarking techniques tend not to consider intrinsic characteristics of image, so that watermarks are embeded to entire images. In this paper, we present a watermarking algorithm based on wavelet domain, and the watermark is embedded into large coefficients in region of interest(ROI) being based on principle of multi-threshold watermark coding(MTWC) for robust watermark insertion. We try to accomplish both image duality and robustness using human visual system(HVS). The watermarks are embedded in middle frequency bands because the distortion degree of watermarked images appears to be less than lower frequency bands, and the embedded watermarks in the middle bands showed high extraction ratios after some distortion. The watermarks are consisted of pseudo random sequences and detected using Cox's similarity mesurement.

This paper presents a new technique for copyright protection and content authentication of satellite images. The novelty in the presented approach consists in designing a hybrid Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT) and hash function based digital image watermarking. In this study, two watermarks are embedded in the cover image called robust copyright watermark and fragile authentication watermark. The robust watermark is embedded in hybrid frequency and wavelet domain by applying DWT and DCT respectively. Such two steps embedding allows the proposed approach to provide better imperceptibility in harmony with the human visual system and offers higher robustness against signal processing attacks. Subsequently, the fragile watermark is embedded in a spatial domain using the hash function approach. The proposed hybrid watermarking technique has been tested on DubaiSat-2 images with 1 meter resolution. The experimental results show that the proposed method is robust against JPEG compression, rotation and resizing attacks. In addition, the multi-watermarked image has a good transparency and the fragile watermark is sensitive to any tampering.

Fragile watermarking is a technology for detecting manipulations in an image, such as the digital signature in cryptography. However, the classification of attacks is not fixed in the security evaluation of existing fragile watermarking schemes, although many schemes have been proposed. In this paper, typical fragile watermarking schemes using a public key cryptosystem are evaluated from the viewpoint of a practical watermarking service. In this evaluation, nine attacks on watermarked images are defined and are classified as: watermarked image attacks, similar to cipher text attacks in cryptography; known original image attacks, similar to known plain text attacks; chosen original image attacks, similar to chosen plain text attacks. We show that the existing schemes are not secure against all attacks and propose a new scheme that is secure against such. attacks and useful for a practical watermarking service.

This paper presents an objective MPEG-2 video quality measurement method based on fragile digital image watermarking. Based on the DWT-based watermarking scheme, this paper presents a fragile digital video watermarking scheme that can work as an automatic quality monitoring system. We embed watermark in the DWT domain of the I-frames of an original video, and the DWT coefficients for embedding are carefully selected so that the degradation of the watermark can reflect the degradation of the video quality. This scheme can track the change of the PSNR value and the Watson JND value. The Watson perceptual model is taken into account to weight the quality measurement according to the human visual system. The evaluations demonstrate the effectiveness of the proposed scheme against MPEG-2 compression and noise pollution

Digital CT Scan images are exchanged among the medical practitioners for consultative purposes or discussing diagnostic and therapeutic measures. This exchange of medical images imposes two main constraints for medical information: (i) the Content Authentication and (ii) Copyright protection. To address these two issues, we have proposed a technique of watermarking for medical images which embeds two watermarks in the CT scan image. The binary pattern is embedded in region of interest (ROI) for content authentication and the composite watermark is embedded in the region of non interest (RONI) for copyright protection. Initially CT Scan image is divided in ROI and RONI by segmentation process. The segmented ROI contains some holes which are first filled. The image morphology is then used and closing operation is applied on the resultant image which eliminates small holes and fills gaps in the contour. Thus binary mask is obtained which is used to separate ROI from RONI. Before embedding the binary pattern in ROI for data authentication purpose, the Least Significant Bit (LSB) information of ROI is extracted first and is saved in separate store. Also, before embedding the composite watermark, pixels in RONI are scrambled for providing the further security. The payload in both ROI and RONI is embedded with simple LSB substitution technique. The extraction procedure is the reverse of embedding process. However few steps of extraction procedure are same as embedding procedure. We have used CT scan image database obtained from Radiology Department, Ackron University Ohio USA. The experimental results show that the proposed algorithm provides better security of medical information during transmission by addressing both issues of data authentication and copyright protection.KeywordsMedical image watermarkingLeast significant bit techniqueImage morphologyImage segmentationData authenticationCopyright protectionRegion of interest (ROI)Region of non interest (RONI)

A reinforcement-learning-based non-uniform compressed sensing (NCS) framework for time-varying signals is introduced. The proposed scheme, referred to as RL-NCS, aims to boost the performance of signal recovery through an optimal and adaptive distribution of sensing energy among two groups of coefficients of the signal, referred to as region of interest (ROI) coefficients and non-ROI coefficients. The coefficients in ROI usually have greater importance and need to be reconstructed with higher accuracy compared to non-ROI coefficients. In order to accomplish this task, the ROI is predicted at each time-step using two specific approaches. One of these approaches incorporates a long short-term memory (LSTM) network for the prediction. The other approach employs the previous ROI information for predicting the next step ROI. Using the exploration-exploitation technique, a Q-network learns to choose the best approach for designing the measurement matrix. Furthermore, a joint loss function is introduced for the efficient training of the Q-network as well as the LSTM network. The result indicates a significant performance gain for our proposed method, even for rapidly varying signals and reduced number of measurements.

For solving the problems of storage and transmission existing in the high-resolution photogrammetric image, an efficient photogrammetric image encoding method based on Region of Interest (ROI) is proposed according to the application characters of photogrammetric image. The ROIs of the photogrammetric image are automatically detected and extracted using the binarization segmentation and the image dilation algorithm. The description of ROI mask is achieved by combining the coefficient similarity in the same level wavelet sub-bands with specific wavelet filter at an extremely low bit rate. All ROI coefficients are compressed using the lossless method to completely reserve the image information necessary for higher measurement precision. According to the energy concentration features of wavelet transform, only the BG (Back Ground) coefficients belonging to the lowest frequency sub-band are encoded in order to improve total compression ratio. Experimental results show that the ROI mask and the main context information could be described at less than 0.03bit/pixel. Furthermore, the proposed method has improved its compression ratio by more than 6%, and reduced the encoding time above 30% as compared with those of the MaxShift method based on JPGE2000. Thus, the proposed method realizes a high efficiency encoding of photogrammetric image and lays a good foundation for the storage and transmission of the high-resolution photogrammetric image.

To guarantee copyright protection and integrity authentication simultaneously, this paper proposed a dual digital watermarking scheme: Transform the image by a two-stage wavelet transform, embed a robust watermark in the low frequency sub image and embed a fragile watermark in the high frequency sub images. A logistic chaos algorithm and a Arnold transform were used to add to the difficulty of breaking, leading to the failure of fragile watermark extraction from tampered image. The algorithm can extract a robust watermark, even though the stego image is badly damaged. It can prove a very feeble modification to the image by a fragile watermark. Theoretical analysis and experimental results show that this technique is an integrated and secure scheme for multimedia production protection.

Abstract. At present, medical equipment provides often 3D models of scanning organs instead of ordinary 2D images. This concept is supported by Digital Imaging and COmmunications in Medicine (DICOM) standard available for telemedicine. This means that the confidential information under transmission ought to be protected by special techniques, particularly digital watermarking scheme instead of textual informative files represented, for example, on CD disks. We propose a multilevel protection, for which a fragile watermark is the first level of protection. The Region Of Interest (ROI) watermark and textual watermarks with information about patient and study (the last ones can be combines as a single textual watermark) form the second level of protection. Encryption of the ROI and textual watermarks using Arnold’s transform is the third level of protection. In the case of 3D models, we find the ROI in each of 2D sliced images, apply the digital wavelet transform or digital shearlet transform (depending on the volume of watermarks) for the ROI and textual watermarks embedding, and embed a fragile watermark using digital Hadamard transform. The main task is to find the relevant regions for embedding. To this and, we develop the original algorithm for selecting relevant regions. The obtained results confirm the robustness of our approach for rotation, scaling, translation, and JPEG attacks.

Background: DCE‐MRI has great potential to provide routine assessment of cancer treatment response. The contrast agent preferentially accumulates in tumors due to increased tumor vascular permeability. The MR based parameters that can be used for treatment assessment (permeability and leakage space) can be averaged over the whole tumor or over a maximum enhancement ROI. The optimal method of analysis is controversial. Material and Methods: DCE‐MR images of selective head and neck, breast and extremity sarcoma patients were acquired on a 1.5T GE Signa Exite scanner before and after different therapy regimens (concurrent chemoradiation for head and neck, neoadjuvant and hyperthermia for breast, and radiation and hyperthermia for extremity sarcomas). The images were analyzed using an fTP pharmacokinetic analysis implemented by CAD Sciences® (White Plains, NY) that determines the tumor's permeability (PERM) and extracellular volume fraction (EVF). ROIs were defined over the entire extent of the tumor (Tumor ROI) and over areas that show maximum enhancement (MaxEnhROI). For head and neck cases, MaxEnhROI were carefully selected not to include fast enhancing arteries which can bias the averaging. Results: For all three tumor types, the trends of PERM and EVF change are the same, but the absolute changes are not. Larger differences are seen in tumors that have peripheral enhancement and large necrotic areas (found often in head and neck and extremity sarcomas). As expected, for homogeneous enhancing tumors (rarely encountered), the differences are not significant. Conclusions: Preliminary results show that ROI selection is important in MR parameter averaging, particularly if the quantitative analysis is used for therapy assessment. This statement is true for all the three sites considered. Although DCE‐MRI has great potential to provide routine assessment of cancer treatment response, its widespread application should be standardized for clinical use. Supported in part by grant NCI CA42745.

The wide use of digital speech recorders becomes a serious matter when they are involved in assisting with court rulings. How to distinguish if a recorded content is valid or not becomes a life-or-death question. In light of this concern, least significant bits (LSB) of excitation signals would be used as fragile watermarks in the hybrid speech vocoder. In addition, a location-variable content-dependent watermark generating mechanism is proposed. Such location-variable content-based watermark would allow users to detect where in the recording the content is being replaced, inserted, or deleted. Lastly, an attempt is done to store partial reconstruction data in the LSBs of excitation signals in the G.723.1 speech codec, so that the original speech content may be reconstructed after counterfeited. The proposed system is demonstrated to be a reliable system, with test results showing that a recording with watermarks has a perceptual evaluation of speech quality (PESQ) value down 0.2, while the accuracy in detecting faked regions can be up to 97.45%.

The embedded multi-resolution coding in JPEG2000 make the ROI(Region Of Interesting) coding very successful. But it is processed in the wavelet domain, resulting in having to decompose some mature JPEG2000 baseline system coder and decoder to implement the ROI function. So a low computational complexity upscaling method in space domain, deduced from the relation of the original image and the image after wavelet transform, is proposed in this paper without modifying the baseline system. By the method, we should right shift the data outside the region of interesting, then use the normal JPEG2000 system to encode and decode the image, and subsequently we can get the image by left shift that data in the space domain after decoding. The method can get high performance quality in ROI in very low bit rate. And it has low computational complexity, needn't deduce the ROI mask in the wavelet domain. As Maxshift method in the wavelet domain, the Maxshift in space domain can be deduced and it decodes the compressed image without ROI mask. That is the ROI mask transmission is not need. The cost of the simpleness is that it will produce distinct tiring edge around the ROI. The method can implement the ROI function through simple extends with the JPEG2000 baseline hardware without the ROI function and it is significative in practice.

To compare the influence of two different regions of interest (ROIs) on diffusion tensor metrics in dystrophic thigh muscles using acustom-made (whole muscle) ROI including and aselective ROI excluding areas of fatty replacement. Diffusion tensor imaging (DTI) and chemical-shift-encoded water-fat magnetic resonance imaging (MRI) of the thigh was conducted on a3-Tesla system in 15cases with muscular dystrophy and controls. The ROIs were chosen according to patterns of fatty replacement on co-registered axial DTI and gradient echo sequence (GRE) images. Fractional anisotropy (FA), apparent diffusion coefficient (ADC), fiber track length (FTL), and muscle fat fractions (MFF) were compared between both ROI segmentations. These comparisons, muscle-specific correlation coefficients, and the influence of ROI localization on tensor metrics were derived based on linear mixed effects regression models. In the cases ahigh correlation was observed for ADC and FA with MFF using acustom ROI. The correlation was weaker but still significant with aselective ROI method. Using the custom ROI, FTL correlated significantly with MFF in 3 out of 4muscles (r ≤ -0.51). Acorrelation was not found for the selective ROI method. Interaction analysis revealed that the association of ADC and FA with MFF was not significantly influenced by the ROI localization. For FTL the ROI localization significantly reduced the negative association with MFF. The DTI metrics and FTL of custom ROI segmentation are significantly influenced by MFF. Contrary to ADC and FA, the effect of MFF on FTL is significantly reduced when applying selective ROI segmentation, which could therefore be abetter option for MR tractography.

Deep learning models based on resting-state functional magnetic resonance imaging (rs-fMRI) have been widely used to diagnose brain diseases, particularly autism spectrum disorder (ASD). Existing studies have leveraged the functional connectivity (FC) of rs-fMRI, achieving notable classification performance. However, they have significant limitations, including the lack of adequate information while using linear low-order FC as inputs to the model, not considering individual characteristics (i.e., different symptoms or varying stages of severity) among patients with ASD, and the non-explainability of the decision process. To cover these limitations, we propose a novel explainability-guided region of interest (ROI) selection (EAG-RS) framework that identifies non-linear high-order functional associations among brain regions by leveraging an explainable artificial intelligence technique and selects class-discriminative regions for brain disease identification. The proposed framework includes three steps: (i) inter-regional relation learning to estimate non-linear relations through random seed-based network masking, (ii) explainable connection-wise relevance score estimation to explore high-order relations between functional connections, and (iii) non-linear high-order FC-based diagnosis-informative ROI selection and classifier learning to identify ASD. We validated the effectiveness of our proposed method by conducting experiments using the Autism Brain Imaging Database Exchange (ABIDE) dataset, demonstrating that the proposed method outperforms other comparative methods in terms of various evaluation metrics. Furthermore, we qualitatively analyzed the selected ROIs and identified ASD subtypes linked to previous neuroscientific studies.

In this paper, a new fragile watermarking method based on statistical analysis in the wavelet domain is developed for image authentication. A two component Gaussian mixture model is developed to describe the statistical characteristics of images in the wavelet domain. Each wavelet subspace of the original image is divided into a watermarking block and a reference block. A Gaussian mixture model is then applied to both blocks to obtain their respective model parameters by an EM (expectation-maximization) algorithm. By slightly changing the wavelet coefficients (adding watermark) in the watermark block, we can adjust its model parameter to the same value as that of the reference block for authentication purposes, which constitutes the fragile watermark. Any change in the fragile-watermarked image will break the relationship of the statistical models between the watermarking block and reference block. The authentication procedure needs only a simple comparison between the model parameters of the two blocks in the watermarked image and no information about the original image. The preliminary experimental results indicate that the new watermarking scheme conforms with human perception characteristics and provides a perceptually invisible fragile watermark with fewer image data modified, compared with some other conventional fragile watermarking methods.