The use of watermarks in the protection of digital multimediaproducts

The watermarking of digital images, audio, video, and multimedia products in general has been proposed for resolving copyright ownership and verifying originality of content. This paper studies the contribution of watermarking for developing protection schemes. A general watermarking framework (GWF) is studied and the fundamental demands are listed. The watermarking algorithms, namely watermark generation, embedding, and detection, are analyzed and necessary conditions for a reliable and efficient protection are stated. Although the GWF satisfies the majority of requirements for copyright protection and content verification, there are unsolved problems inside a pure watermarking framework. Particular solutions, based on product registration and related network services, are suggested to overcome such problems     

Asymptotically optimal detection for additive watermarking in the DCT and DWT domains

Most of the watermarking schemes that have been proposed until now employ a correlation detector (matched filter). The current paper proposes a new detector scheme that can be applied in the case of additive watermarking in the DCT (discrete cosine transform) or DWT (discrete wavelet transform) domain. Certain properties of the probability density function of the coefficients in these domains are exploited. Thus, an asymptotically optimal detector is constructed based on well known results of the detection theory. Experimental results prove the superiority of the proposed detector over the correlation detector.     

Multichannel L filters based on marginal data ordering

The extension of single-channel nonlinear filters whose output is a linear combination of the order statistics of the input samples to the multichannel case is presented in the paper. The subordering principle of marginal ordering (M-ordering) is used for multivariate data ordering. Assuming a multichannel signal corrupted by additive white multivariate noise whose components are generally correlated, the coefficients of the multichannel L filter based on marginal ordering are chosen to minimize the output mean-squared-error (MSE) either subject to the constraints of unbiased or location-invariant estimation or without imposing any constraint. Both the case of a constant multichannel signal corrupted by additive white multivariate noise as well as the case of a nonconstant signal is considered. In order to test the performance of the designed multichannel marginal L filters, long-tailed multivariate distributions are required. The derivation and design of such a distribution, namely, the Laplacian (biexponential) distribution that belongs to Morgenstern's family in the 2D case is discussed. It is shown by simulation that the proposed multichannel L filters perform better than other multichannel nonlinear filters such as the vector median, the marginal α-trimmed mean, the marginal-median, the multichannel modified trimmed mean, the multichannel double-window trimmed mean, and the multivariate ranked-order estimator R_E proposed elsewhere as well as their single-channel counterparts     

Blind robust watermarking schemes for copyright protection of 3D mesh objects

In this paper, two novel methods suitable for blind 3D mesh object watermarking applications are proposed. The first method is robust against 3D rotation, translation, and uniform scaling. The second one is robust against both geometric and mesh simplification attacks. A pseudorandom watermarking signal is cast in the 3D mesh object by deforming its vertices geometrically, without altering the vertex topology. Prior to watermark embedding and detection, the object is rotated and translated so that its center of mass and its principal component coincide with the origin and the z-axis of the Cartesian coordinate system. This geometrical transformation ensures watermark robustness to translation and rotation. Robustness to uniform scaling is achieved by restricting the vertex deformations to occur only along the r coordinate of the corresponding (r, /spl theta/, /spl phi/) spherical coordinate system. In the first method, a set of vertices that correspond to specific angles /spl theta/ is used for watermark embedding. In the second method, the samples of the watermark sequence are embedded in a set of vertices that correspond to a range of angles in the /spl theta/ domain in order to achieve robustness against mesh simplifications. Experimental results indicate the ability of the proposed method to deal with the aforementioned attacks.     

Δ15, 18-tetracosadienoic acid content of sphingolipids from platel and erythrocytes of animals fed diets high in saturated or polyunsaturated fats

The effect of diets high (15%) in saturated (beef tallow) or polyunsaturated (corn or cottonseed oil) fatty acids on the fatty acid composition of sphingomyelin from canine erythrocytes and platelets and sphingomyelin and neutral glycosphingolipids of swine erythrocytes was determined. Sphingolipids of platelets and erythrocytes from animals fed high levels of corn or cottonseed oil exhibited a dramatic alteration in their fatty acid composition, most notable of which was a 50% reduction in nervonic acid (24∶1ω9) as compared to levels observed in control or tallow fed animals. This decrease was compensated for by a quantitatively similar increase in a C₂₄ dienoic acid. The long chain dienoic acid was isolated by silver nitrate thin layer chromatography and determined by analysis of its oxidation products to be Δ15, 18-tetracosadienoic acid (24∶2ω6). When the animals were fed the diets high in polyunsaturates, the 24∶2ω6 represented 13, 20, and 9% of the sphingomyelin fatty acids from canine erythrocytes, platelets, and swine erythrocytes, respectively, and 5% of the neutral glycosphingolipid fatty acids of swine erythrocytes. In contrast, the 24∶2ω6 represented less than 4% of the total cellular sphingolipid fatty acids in animals fed the control or high beef tallow diets. The 24∶1ω9 in the sphingolipids of the animals fed the polyunsaturated diet was roughly equal to that of 24∶2ω6, whereas in the sphingolipids of animals fed the control or saturated fat (beef tallow) diet, the 24∶1ω9 was twice these values. Since sphingomyelin is a membrane component, the increase in unsaturation (24∶2ω6) in its fatty acid moiety induced by dietary polyunsaturates may affect membrane fluidity and may alter membrane properties. Dr. Nelson’s current affiliation is with the Lipid Metabolism Branch, Division of Heart and Vascular Diseases, National Heart, Lung, and Blood Institute.     

Comparison of ICA approaches for facial expression recognition

Independent component analysis (ICA) and Gabor wavelets extract the most discriminating features for facial action unit classification by employing either a cosine similarity measure (CSM) classifier or support vector machines (SVMs). So far, only the ICA approach, which is based on the InfoMax principle, has been tested for facial expression recognition. In this paper, in addition to the InfoMax approach, another five ICA approaches extract features from two facial expression databases. In particular, the Extended InfoMax ICA, the undercomplete ICA, and the nonlinear kernel-ICA approaches are exploited for facial expression representation for the first time. When applied to images, ICA treats the images as being mixtures of independent sources and decomposes them into an independent basis and the corresponding mixture coefficients. Two architectures for representing the images can be employed yielding either independent and sparse basis images or independent and sparse distributions of image representation coefficients. After feature extraction, facial expression classification is performed with the help of either a CSM classifier or an SVM classifier. A detailed comparative study is made with respect to the accuracy offered by each classifier. The correlation between the accuracy and the mutual information of independent components or the kurtosis is evaluated. Statistically significant correlations between the aforementioned quantities are identified. Several issues are addressed in the paper: (i) whether features having super- and sub-Gaussian distribution facilitate facial expression classification; (ii) whether a nonlinear mixture of independent sources improves the classification accuracy; and (iii) whether an increased “amount” of sparseness yields more accurate facial expression recognition. In addition, performance enhancements by employing leave-one-set of expressions-out and subspace selection are studied. Statistically significant differences in accuracy between classifiers using several feature extraction methods are also indicated.     

Speech and Video Telephony Quality Characterization and Prediction of Live Contemporary Mobile Communication Networks

Quality of Service (QoS) characterization and prediction is of utmost importance in contemporary operating cellular communications networks. Measurements data of speech and video telephony have been collected using modern experimental equipment. More specifically, key performance indicators of radio, speech and video quality are evoked. The objective of our study is to critically investigate the performance of speech and video telephony at live cellular networks correlating significant QoS parameters from radio and the service side. Simple non-linear regression models are also proposed for speech and video quality prediction. Finally, the paper represents the splendid positive influences of the continuous performance evaluation for the optimization of the mobile networks. There are also briefly given guidelines for mobile networks benchmarking.     

Fuzzy cell Hough transform for curve detection

In this paper a new variation of Hough Transform is proposed. It can be used to detect shapes or contours in an image, with better accuracy, especially in noisy images. The parameter space of Hough Transform is split into fuzzy cells which are defined as fuzzy numbers. This fuzzy split provides the advantage to use the uncertainty of the contour point location which is increased when noisy images are used. By using fuzzy cells, each contour point in the spatial domain contributes in more than one fuzzy cell in the parameter space. The array that is created after the fuzzy voting process is smoother than in the crisp case and the effect of noise is reduced. The curves can now be detected with better accuracy. The computation time that is slightly increased by this method, can be minimized in comparison with classical Hough Transform, by using recursively the fuzzy voting process in a roughly split parameter space, to create a multiresolution fuzzily split parameter space.