The main focus of this thesis is the problem of geometric distortion in image and video watermarking. In this thesis we discuss the two aspects of the geometric distortion problem, namely the watermark desynchronization aspect and the perceptual quality assessment aspect. Furthermore, this thesis also discusses the challenges of watermarking data compressed in low bit-rates. The main contributions of this thesis are: A watermarking algorithm suitable for low bit-rate video has been proposed. Two different approaches has been proposed to deal with the watermark desynchronization problem. A novel approach has been proposed to quantify the perceptual quality impact of geometric distortion.

Optimizing the performance of digital imaging systems with respect to the capture, display, storage and transmission of visual information represents one of the biggest challenges in the field of image and video processing. Taking into account the way humans perceive visual information can be greatly beneficial for this task. To achieve this, it is necessary to understand and model the human visual system, which is also the principal goal of this thesis. Computational models for different aspects of the visual system are developed, which can be used in a wide variety of image and video processing applications. The proposed models and metrics are shown to be consistent with human perception. The focus of this work is visual quality assessment. A perceptual distortion metric (PDM) for the evaluation of video quality is presented. It is based on a model of the ...

In scalable image/video coding, high resolution content is encoded to the highest visual quality and the bit-streams are adapted to cater various communication channels, display devices and usage requirements. These content adaptations, which include quality, resolution and frame rate scaling may also affect the content protection data, such as, watermarks and are considered as a potential watermark attack. In this thesis, research on robust watermarking techniques for scalable coded image and video, are proposed and the improvements in robustness against various content adaptation attacks, such as, JPEG 2000 for image and Motion JPEG 2000, MC-EZBC and H.264/SVC for video, are reported. The spread spectrum domain, particularly wavelet-based image watermarking schemes often provides better robustness to compression attacks due to its multi-resolution decomposition and hence chosen for this work. A comprehensive and comparative analysis of the available wavelet-based watermarking schemes,is performed ...

In this thesis, a number of novel watermarking techniques for different 3D representations are presented. A novel watermarking method is proposed for the mono-view video, which might be interpreted as the basic implicit representation of 3D scenes. The proposed method solves the common flickering problem in the existing video watermarking schemes by means of adjusting the watermark strength with respect to temporal contrast thresholds of human visual system (HVS), which define the maximum invisible distortions in the temporal direction. The experimental results indicate that the proposed method gives better results in both objective and subjective measures, compared to some recognized methods in the literature. The watermarking techniques for the geometry and image based representations of 3D scenes, denoted as 3D watermarking, are examined and classified into three groups, as 3D-3D, 3D-2D and 2D-2D watermarking, in which the pair of symbols ...

People of all generations are making more and more use of digital imaging systems in their daily lives. The image content rendered by these digital imaging systems largely differs in perceived quality depending on the system and its applications. To be able to optimize the experience of viewers of this content understanding and modeling perceived image quality is essential. Research on modeling image quality in a full-reference framework --- where the original content can be used as a reference --- is well established in literature. In many current applications, however, the perceived image quality needs to be modeled in a no-reference framework at real-time. As a consequence, the model needs to quantitatively predict perceived quality of a degraded image without being able to compare it to its original version, and has to achieve this with limited computational complexity in order ...

Nowadays, richer 3D visual representation formats are emerging, notably light fields and point clouds. These formats enable new applications in many usage domains, notably virtual and augmented reality, geographical information systems, immersive communications, and cultural heritage. Recently, following major improvements in 3D visual data acquisition, there is an increasing interest in point-based visual representation, which models real-world objects as a cloud of sampled points on their surfaces. Point cloud is a 3D representation model where the real visual world is represented by a set of 3D coordinates (the geometry) over the objects with some additional attributes such as color and normals. With the advances in 3D acquisition systems, it is now possible to capture a realistic point cloud to represent a visual scene with a very high resolution. These point clouds may have up to billions of points and, thus, ...

Image and video quality assessment has become an increasingly important subject in digital video coding and transmission scenarios, such as digital television. In this context, a special interest has been put on no-reference objective quality assessment metrics, since they are suitable for real-time quality monitoring once the video delivery system is settled. This Thesis proposes new no-reference quality assessment metrics for images and video. The main goal of the proposed techniques is to estimate the quality of lossy DCT-based encoded video. The proposed metrics share the same key idea: based on elements extracted from the bitstream of the encoded images or video arriving at the point where quality assessment has to be performed, an estimate of the quantization error associated to each DCT coefficient is obtained. Those estimates are perceptually weighted and combined in order to obtain a quality score ...

This thesis has two main parts. The first part deals with security and privacy analysis of biometric hashing. The second part introduces a method for fixed-length feature vector extraction and hash generation from fingerprint minutiae. The upsurge of interest in biometric systems has led to development of biometric template protection methods in order to overcome security and privacy problems. Biometric hashing produces a secure binary template by combining a personal secret key and the biometric of a person, which leads to a two factor authentication method. This dissertation analyzes biometric hashing both from a theoretical point of view and in regards to its practical application. For theoretical evaluation of biohashes, a systematic approach which uses estimated entropy based on degree of freedom of a binomial distribution is outlined. In addition, novel practical security and privacy attacks against face image hashing ...

We propose a technique for the problem of detecting the very presence of hidden messages in an audio object. The detector is based on the characteristics of the denoised residuals of the audio file. Our proposition is established upon the presupposition that the hidden message in a cover object leaves statistical evidence that can be detected with the use of some audio distortion measures. The distortions caused by hidden message are measured in terms of objective and perceptual quality metrics. The detector discriminates between cover and stego files using a selected subset of features and an SVM classifier. We have evaluated the detection performance of the proposed steganalysis technique with the well-known watermarking and steganographic methods. We present novel and robust audio fingerprinting techniques based on the summarization of the time-frequency spectral characteristics of an audio object. The perceptual hash ...

This thesis deals with the coding of images with multiple coding schemes and their dynamic selection. In our society of information highways, electronic communication is taking everyday a bigger place in our lives. The number of transmitted images is also increasing everyday. Therefore, research on image compression is still an active area. However, the current trend is to add several functionalities to the compression scheme such as progressiveness for more comfortable browsing of web-sites or databases. Classical image coding schemes have a rigid structure. They usually process an image as a whole and treat the pixels as a simple signal with no particular characteristics. Second generation schemes use the concept of objects in an image, and introduce a model of the human visual system in the design of the coding scheme. Dynamic coding schemes, as their name tells us, make ...

Ten years after its infancy, digital watermarking is still considered as a young technology. Despite the fact that it has been introduced for security-related applications such as copyright protection, almost no study has been conducted to assert the survival of embedded watermarks in a hostile environment. In this thesis, it will be shown that this lack of evaluation has led to critical security pitfalls against statistical analysis, also referred to as collusion attacks. Such attacks typically consider several watermarked documents and combine them to produce unwatermarked content. This threat is all the more relevant when digital video is considered since each individual video frame can be regarded as a single watermarked document by itself. Next, several countermeasures are introduced to combat the highlighted weaknesses. In particular, motion compensated watermarking and signal coherent watermarking will be investigated to produce watermarks which ...

This thesis presents a framework of test methodology to assess spatial domain compression artefacts produced by image and intra-frame coded video codecs. Few researchers have studied this broad range of artefacts. A taxonomy of image and video compression artefacts is proposed. This is based on the point of origin of the artefact in the image communication model. This thesis presents objective evaluation of distortions known as artefacts due to image and intra-frame coded video compression made using synthetic test patterns. The American National Standard Institute document ANSI T1 801 qualitatively defines blockiness, blur and ringing artefacts. These definitions have been augmented with quantitative definitions in conjunction with test patterns proposed. A test and measurement environment is proposed in which the codec under test is exercised using a portfolio of test patterns. The test patterns are designed to highlight the artefact ...

Automatic face recognition has attracted a lot of attention not only because of the large number of practical applications where human identification is needed but also due to the technical challenges involved in this problem: large variability in facial appearance, non-linearity of face manifolds and high dimensionality are some the most critical handicaps. In order to deal with the above mentioned challenges, there are two possible strategies: the first is to construct a “good” feature space in which the manifolds become simpler (more linear and more convex). This scheme usually comprises two levels of processing: (1) normalize images geometrically and photometrically and (2) extract features that are stable with respect to these variations (such as those based on Gabor filters). The second strategy is to use classification structures that are able to deal with non-linearities and to generalize properly. To ...

This thesis investigates the design and evaluation of an embedded optimization framework for the perceptual enhancement of audio signals which are degraded by linear and/or nonlinear distortion. In general, audio signal enhancement has the goal to improve the perceived audio quality, speech intelligibility, or another desired perceptual attribute of the distorted audio signal by applying a real-time digital signal processing algorithm. In the designed embedded optimization framework, the audio signal enhancement problem under consideration is formulated and solved as a per-frame numerical optimization problem, allowing to compute the enhanced audio signal frame that is optimal according to a desired perceptual attribute. The first stage of the embedded optimization framework consists in the formulation of the per-frame optimization problem aimed at maximally enhancing the desired perceptual attribute, by explicitly incorporating a suitable model of human sound perception. The second stage of ...

This thesis treats efficient estimation algorithms for the epipolar geometry, the model underlying two views of the same scene or object. The epipolar geometry is computed from image correspondences that are found by local feature matching. These correspondences are used to calculate the fundamental matrix, which is the mathematical representation of the epipolar geometry. Since there are outliers among the correspondences, the fundamental matrix is usually calculated by the robust RANSAC (RANdom SAmple Consensus) algorithm which is very well suited for this purpose. A disadvantage of the algorithm, however, is that it shows a considerable complexity for higher outlier ratios. This hampers its application in vision algorithms dealing with many views. In this thesis we investigate techniques for faster fundamental matrix estimation using RANSAC. The first approach that is taken is the computation of inlier probabilities for the correspondences, that ...