No / A robust watermarking technique is implemented for copyright protection. The proposed method is based on 2-level discrete wavelet transform (DWT). The embedded watermarking information is a mobile phone number including the international code. The first level of the DWT transformation is applied on 16×16 blocks of the host image. All the coefficients of the 8×8 low-low (LL1) first level sub-band are grouped into one matrix. The second level of the DWT is then applied to the grouped matrix from the first level transformation. The highest coefficient from the LL2 sub-band (4×4) is used for embedding the watermark information. The extracting process is blind since it does not require the original image at the receiver side. The distortion in the host image due to the watermarking process is minimal and the PSNR is greater than 60 dB. The proposed algorithm showed robustness against several attacks such as scaling, filtering, cropping, additive noise and JPEG compression.

Reversible watermarking techniques extract the watermark and recover the original image losslessly from the watermarked image. They have been applied to those sensitive fields, such as the medicine and the military. Since an embedding pixel value may exceed the limitation of pixel value during the embedding process, most of the reversible watermarking methods require a location-map to record those pixels for recovering cover images. Although the location-map can be compressed by a lossless compression algorithm, and then embed into the watermarked image, this lowers embedding capacity and increases the complexity of watermarking during the procedures of embedding and extraction. In this thesis, we propose a reversible location-map free of watermarking algorithm. This algorithm first exploits the sorting and the correlation of neighboring pixels to increase the embedding capacity. Next we find thresholds from the predicted values. If the predicted value of an embedding pixel is within the thresholds, we can ensure that the pixel has no underflow or overflow problem during embedding process. Therefore, we can recover the cover image without any distortion. The experimental results reveal that the performance of our proposed method outperforms that proposed by FUJIYOSHI et al. For example, the embedding capacity obtained by the proposed method is higher than that obtained by FUJIYOSHI et al. about 60%, and the PSNR of our scheme is higher than FUJIYOSHI et al. about 5 dB.

The rapid development of Internet introduces a new set of challenging problem regarding security. To prevent unauthorized copying of digital production from distributing is one of the significant problems. Digital watermarking is a potential method for protecting the ownership rights on digital audio, image and video data. An attack succeeds in defeating a watermarked article if it impairs the watermarking information beyond acceptable limits while maintaining the perceptual quality of the attacked article. Namely, attacks on digital watermarked article must consider both watermarking information survival and the distortion of the attacked stego-media. Current attack benchmarks do not exploit as much knowledge of the watermarked image as possible, also they do not consider the distortion of the attacked stego-media. In this paper, various attacks on digital watermarking have been investigated, and a categorization of different attacks was roughly given; Besides, an Eigen-image-based (ED-based) attack is proposed to deliberately impair the watermarking information without excessively distorting the attacked stego-media, that is not currently included in those benchmark tools.

Many existing researches on image watermarking for copyright protection need to use original image in retrieving watermark. Though it is more robust, it would cause some problems about the authorization of original image. In this thesis, we propose a method based on DCT domain without using original image. Using the property of concentrating energy in DCT transform, the energies of blocks are used for further processing. In the embedding algorithm, the DC coefficients of blocks are first collected. Then they are divided by some number to get remainders. The values of embedded data are embedded in the relationship between corresponding location of embedded data and other locations by adjusting the remainders in all locations. Some typical watermarking attacks and noise are used to evaluate the robustness of our method. Compared with other competing algorithms, it shows that the survival rate of watermark in our method can be almost the same or even better then those methods which need original image. The error rate of the lowest quality JPEG compression can be adjusted less then 1%, when the length of embedding data is 512 bits. Our proposed method can be further improved by adjusting the values of remainders and the block size. These provide flexibility to satisfy different requirements.

In this dissertation, I investigated some fundamental issues related to medical image segmentation, registration, and watermarking. I used color retinal fundus images to perform my study because of the rich representation of different objects (blood vessels, microaneurysms, hemorrhages, exudates, etc.) that are pathologically important and have close resemblance in shapes and colors. To attack this complex subject, I developed a divide-and-conquer strategy to address related issues step-by-step and to optimize the parameters of different algorithm steps. Most, if not all, objects in our discussion are related. The algorithms for detection, registration, and protection of different objects need to consider how to differentiate the foreground from the background and be able to correctly characterize the features of the image objects and their geometric properties. To address these problems, I characterized the shapes of blood vessels in retinal images and proposed the algorithms to extract the features of blood vessels. A tracing algorithm was developed for the detection of blood vessels along the vascular network. Due to the noise interference and various image qualities, the robust segmentation techniques were used for the accurate characterization of the objects’ shapes and verification. Based on the segmentation results, a registration algorithm was developed, which uses the bifurcation and cross-over points of blood vessels to establish the correspondence between the images and derive the transformation that aligns the images. A Region-of-Interest (ROI) based watermarking scheme was proposed for image authenticity. It uses linear segments extracted from the image as reference locations for embedding and detecting watermark. Global and locally-randomized synchronization schemes were proposed for bit-sequence synchronization of a watermark. The scheme is robust against common image processing and geometric distortions (rotation and scaling), and it can detect alternations such as moving or removing of the image content.

Thesis (Ph. D.)--State University of New York at Binghamton, Watson School of Engineering and Applied Science (Systems Science), 2005. / Includes bibliographical references.

Η ψηφιακή υδατοσήμανση προτείνεται για την προστασία των πνευματικών δικαιωμάτων και του copyright των αρχείων ψηφιακού βίντεο. Το πρόβλημα συνήθως αντιμετωπίζεται με αλγορίθμους υδατοσήμανσης ψηφιακής εικόνας, οι οποίοι εφαρμόζονται σε κάθε πλαίσιο (frame) ενός αρχείου ψηφιακού βίντεο. Τα αόρατα υδατογραφήματα κυρίως στοχεύουν στην ανίχνευση και απόδειξη της παραβίασης του copyright για τα αρχεία ψηφιακού βίντεο που διακινούνται μέσω των δικτύων και του Διαδικτύου. Κατά την ανίχνευση της ύπαρξης του υδατογραφήματος, σε οποιοδήποτε πλαίσιο του αρχείου ψηφιακού βίντεο, αποδεικνύεται και η ταυτότητα του κατόχου του αρχείου και οι νομικοί περιορισμοί χρήσης του. / Digital watermarking is proposed for the protection of intellectual rights and copyright the files of digital video. The problem is usually faced with watermarked algorithms of digital picture, which are applied in each frame of a digital video file . Invisible watermarks mainly aim in the detection and proof of copyright violation for the files of digital video that are trafficked in via the networks and the Internet. At the detection of existence of watermarking, in any frame of digital video file, is proved also the identity of holder of file and its legal restrictions of use.

Image and video quality evaluation is very important. In applications involving signal transmission, the Reduced- or No-Reference quality metrics are generally more practical than the Full-Reference metrics. Digital watermarking based quality evaluation emerges as a potential Reduced- or No-Reference quality metric, which estimates signal quality by assessing the degradation of the embedded watermark. Since the watermark contains a small amount of information compared to the cover signal, performing accurate signal quality evaluation is a challenging task. Meanwhile, the watermarking process causes signal quality loss. To address these problems, in this thesis, a framework for image and video quality evaluation is proposed based on semi-fragile and adaptive watermarking. In this framework, adaptive watermark embedding strength is assigned by examining the signal quality degradation characteristics. The "Ideal Mapping Curve" is experimentally generated to relate watermark degradation to signal degradation so that the watermark degradation can be used to estimate the quality of distorted signals. With the proposed framework, a quantization based scheme is first implemented in DWT domain. In this scheme, the adaptive watermark embedding strengths are optimized by iteratively testing the image degradation characteristics under JPEG compression. This iterative process provides high accuracy for quality evaluation. However, it results in relatively high computational complexity. As an improvement, a tree structure based scheme is proposed to assign adaptive watermark embedding strengths by pre-estimating the signal degradation characteristics, which greatly improves the computational efficiency. The SPIHT tree structure and HVS masking are used to guide the watermark embedding, which greatly reduces the signal quality loss caused by watermark embedding. Experimental results show that the tree structure based scheme can evaluate image and video quality with high accuracy in terms of PSNR, wPSNR, JND, SSIM and VIF under JPEG compression, JPEG2000 compression, Gaussian low-pass filtering, Gaussian noise distortion, H.264 compression and packet loss related distortion.

Image and video quality evaluation is very important. In applications involving signal transmission, the Reduced- or No-Reference quality metrics are generally more practical than the Full-Reference metrics. Digital watermarking based quality evaluation emerges as a potential Reduced- or No-Reference quality metric, which estimates signal quality by assessing the degradation of the embedded watermark. Since the watermark contains a small amount of information compared to the cover signal, performing accurate signal quality evaluation is a challenging task. Meanwhile, the watermarking process causes signal quality loss. To address these problems, in this thesis, a framework for image and video quality evaluation is proposed based on semi-fragile and adaptive watermarking. In this framework, adaptive watermark embedding strength is assigned by examining the signal quality degradation characteristics. The "Ideal Mapping Curve" is experimentally generated to relate watermark degradation to signal degradation so that the watermark degradation can be used to estimate the quality of distorted signals. With the proposed framework, a quantization based scheme is first implemented in DWT domain. In this scheme, the adaptive watermark embedding strengths are optimized by iteratively testing the image degradation characteristics under JPEG compression. This iterative process provides high accuracy for quality evaluation. However, it results in relatively high computational complexity. As an improvement, a tree structure based scheme is proposed to assign adaptive watermark embedding strengths by pre-estimating the signal degradation characteristics, which greatly improves the computational efficiency. The SPIHT tree structure and HVS masking are used to guide the watermark embedding, which greatly reduces the signal quality loss caused by watermark embedding. Experimental results show that the tree structure based scheme can evaluate image and video quality with high accuracy in terms of PSNR, wPSNR, JND, SSIM and VIF under JPEG compression, JPEG2000 compression, Gaussian low-pass filtering, Gaussian noise distortion, H.264 compression and packet loss related distortion.

Image and video quality evaluation is very important. In applications involving signal transmission, the Reduced- or No-Reference quality metrics are generally more practical than the Full-Reference metrics. Digital watermarking based quality evaluation emerges as a potential Reduced- or No-Reference quality metric, which estimates signal quality by assessing the degradation of the embedded watermark. Since the watermark contains a small amount of information compared to the cover signal, performing accurate signal quality evaluation is a challenging task. Meanwhile, the watermarking process causes signal quality loss. To address these problems, in this thesis, a framework for image and video quality evaluation is proposed based on semi-fragile and adaptive watermarking. In this framework, adaptive watermark embedding strength is assigned by examining the signal quality degradation characteristics. The "Ideal Mapping Curve" is experimentally generated to relate watermark degradation to signal degradation so that the watermark degradation can be used to estimate the quality of distorted signals. With the proposed framework, a quantization based scheme is first implemented in DWT domain. In this scheme, the adaptive watermark embedding strengths are optimized by iteratively testing the image degradation characteristics under JPEG compression. This iterative process provides high accuracy for quality evaluation. However, it results in relatively high computational complexity. As an improvement, a tree structure based scheme is proposed to assign adaptive watermark embedding strengths by pre-estimating the signal degradation characteristics, which greatly improves the computational efficiency. The SPIHT tree structure and HVS masking are used to guide the watermark embedding, which greatly reduces the signal quality loss caused by watermark embedding. Experimental results show that the tree structure based scheme can evaluate image and video quality with high accuracy in terms of PSNR, wPSNR, JND, SSIM and VIF under JPEG compression, JPEG2000 compression, Gaussian low-pass filtering, Gaussian noise distortion, H.264 compression and packet loss related distortion.