The recent finalization of MPEG-4 will make this standard very attractive for a large range of applications such as video editing, Internet video distribution, wireless video communications. Some of these applications are likely to get great benefit from watermarking technology, since it can enable a number of innovative services, such as conditional access policies, data annotation, data labeling, content authentication, to be implemented at a low price. One of the key points of the MPEG-4 standard is the possibility to access and manipulate objects within a video sequence. Thus object watermarking has to be achieved in such a way that, while a video object is transferred from a sequence to another, it is still possible to correctly access the data embedded within the object itself. The algorithm proposed in this paper embeds a watermark in each video object by imposing a particular relationship between some predefined pairs of quantized discrete cosine transform (DCT) coefficients in the luminance blocks of pseudo-randomly selected macroblocks (MBs). Watermarks are equally embedded into intra and inter MBs. Experimental results are presented validating the effectiveness of the proposed approach.

The work described presents a procedure aimed at automatically extracting the medulla duct outlines from a human femur radiographic image. The outlines are retrieved by referring to a suitable geometric model of the generic femoral cross section; the projection function derived from such a model is fitted on the grey level values corresponding to the rows of the digitised radiographic image by means of a least squares algorithm. The resulting outlines are used in a software system performing hip prosthesis preoperational planning.

We propose near-lossless digital watermarking for copyright protection of remote sensing images. In particular, we show that, by forcing a maximum absolute difference between the original and watermarked scene, the near-lossless paradigm makes it possible to decrease the effect of watermarking on remote sensing applications to be carried out on the images. As an example, the effect of near-lossless watermarking on image classification is analyzed.

In the field of image watermarking, research has been mainly focused on grayscale image watermarking, whereas the extension to the color case is usually accomplished by marking the image luminance, or by processing each color channel separately. A DCT domain watermarking technique expressly designed to exploit the peculiarities of color images is presented. The watermark is hidden within the data by modifying a subset of full-frame DCT coefficients of each color channel. Detection is based on a global correlation measure which is computed by taking into account the information conveyed by the three color channels as well as their interdependency. To ultimately decide whether or not the image contains the watermark, the correlation value is compared to a threshold. With respect to existing grayscale algorithms, a new approach to threshold selection is proposed, which permits reducing the probability of missed detection to a minimum, while ensuring a given false detection probability. Experimental results, as well as theoretical analysis, are presented to demonstrate the validity of the new approach with respect to algorithms operating on image luminance only.

The peculiarities of digital map images are exploited to develop a watermarking algorithm which is robust against geometric distortions. Robustness against geometric attacks is achieved through text-based image normalization. First, text is extracted from the to-be-marked map, then text orientation and size are exploited to normalize the image geometry prior to watermark insertion. Watermarking is performed by means of any of the existing algorithms ensuring good robustness against image processing tools. At the decoder side, text is extracted again from the map and used to normalize image geometry. Owing to the robustness of text features with respect to common image manipulations, and to the likely spreading of text all across the digital map, the proposed system exhibits an excellent robustness, as is witnessed by the experimental results reported.

Motion estimation in image sequences is undoubtedly one of the most studied problems because for many applications, going from video coding to pattern recognition, motion estimation is a fundamental tool. A new methodology which, by minimizing a specific potential function, determines for each image pixel its motion parameter set is presented. The approach is based on MRFs (Markov random fields) acting on a first-order neighborhood for each selected point and on a simple motion model that accounts for rotations and translations. Experimental results on synthetic and real world sequences have demonstrated the good performance of the adopted technique and moreover a quantitative and qualitative comparison with another well-known approach has confirmed the goodness of the proposed algorithm.

This paper deals with robust watermarking of cartographic images. We present a method (text-based geometric normalization-TBGN) which, by exploiting the particular content of cartographic images, namely text content, permits one to cope with global geometric transformations. The validity of the method is validated by experimental results.

The performance of syntax-based error detection in the framework of H.263 video transmission is not sufficient to detect errors reliably, calling for the adoption of more effective error detection techniques. A new technique, based on data hiding concepts, is proposed here to increase the error detection rate in H.263 video sequences transmitted over error-prone communication channels. Some information is embedded into the compressed H.263 video stream aimed at highlighting the regions of the frame corrupted by transmission errors. The method preserves the image quality and maintains the original bit rate, without any modifications of the H.263 standard. The proposed approach allows one to avoid the transmission overhead typical of FEC-based or header-based error detection algorithms, and the extra computational burden peculiar to image analysis-based techniques, achieving better results with respect to syntax-based error detection, thanks to the use of side information at the decoder.

In automatic video surveillance (VS) systems, the issue of authenticating the video content is of primary importance. Given the ease with which digital images and videos can be manipulated, practically they do not have any value as legal proof, if the possibility of authenticating their content is not provided. In this paper, the problem of authenticating video surveillance image sequences is considered. After an introduction motivating the need for a watermarking-based authentication of VS sequences, a brief survey of the main watermarking-based authentication techniques is presented and the requirements that an authentication algorithm should satisfy for VS applications, are discussed. A novel algorithm which is suitable for VS visual data authentication is also presented and the results obtained by applying it to test data are discussed.

The impact of a regularization of motion vectors (MVs) on the performance of a block-DCT based video coder (H.263) is addressed. Postprocessing is accomplished by exploiting both the spatial correlation of the vector field and the confidence of the estimated block vectors. A previously proposed adaptive scheme for MV smoothing, based on the theory of vector median filters, is adjusted and embedded into an H.263 coder. With a bit stream that is perfectly H.263-compatible, results are improved, especially for very low bit rates and complex motion of the scene.

A watermarking algorithm operating in the wavelet domain is presented. Performance improvement with respect to existing algorithms is obtained by means of a new approach to mask the watermark according to the characteristics of the human visual system (HVS). In contrast to conventional methods operating in the wavelet domain, masking is accomplished pixel by pixel by taking into account the texture and the luminance content of all the image subbands. The watermark consists of a pseudorandom sequence which is adaptively added to the largest detail bands. As usual, the watermark is detected by computing the correlation between the watermarked coefficients and the watermarking code, and the detection threshold is chosen in such a way that the knowledge of the watermark energy used in the embedding phase is not needed, thus permitting one to adapt it to the image at hand. Experimental results and comparisons with other techniques operating in the wavelet domain prove the effectiveness of the new algorithm.

Watermark detection, i.e., the detection of an invisible signal hidden within an image for copyright protection or data authentication, has classically been tackled by means of correlation-based techniques. Nevertheless, when watermark embedding does not obey an additive rule, or when the features the watermark is superimposed on do not follow a Gaussian pdf, correlation-based decoding is not the optimum choice. A new decoding algorithm is presented here which is optimum for nonadditive watermarks embedded in the magnitude of a set of full-frame DFT coefficients of the host image. By relying on statistical decision theory, the structure of the optimum is derived according to the Neyman-Pearson criterion, thus permitting to minimize the missed detection probability subject to a given false detection rate. The validity of the optimum decoder has been tested thoroughly to assess the improvement it permits to achieve from a robustness perspective. The results we obtained confirm the superiority of the novel algorithm with respect to classical correlation-based decoding.

So far digital watermarking has been indicated as the most feasible answer for multimedia copyright protection issues, though many problems, especially regarding aspects of robustness against geometrical attacks, have not been completely and adequately solved yet. Robustness against geometric manipulations has been dealt with by inserting, together with the watermark, a synchronization template to be used later in the detection phase, to determine if a geometric distortion occurred and invert it before looking for the mark. A novel technique is presented, which, by exploiting the theory of geometric invariants, inserts a watermark intrinsically resistant to this sort of manipulations, thus avoiding the need of a synchronization pattern. Preliminary experimental results proving the goodness of the methodology are discussed along with some implementation problems due to the computational complexity.

Digital watermarking involves embedding copyright marks (watermarks), often imperceptibly, in multimedia objects to enhance or protect their value. In this paper we describe a novel watermarking algorithm suitable for video coding techniques such as MPEG-4 and H.263/H.324 and we test it in a wireless environment. The proposed algorithm satisfies critical properties not all of which are available in previous solutions. These properties include: resistance (robustness) of the embedded watermark to the error-prone nature of wireless channels as well as to video frame loss or misplacement, negligible probability of reading a non-embedded watermark, non-degradation of the marked video sequence and the possibility to mark video objects (e.g., MPEG-4 objects) in a single frame separately. Experimental results are given that show how these and other properties are achieved when video sequences are corrupted with errors that are typical of a wireless channel.

For reducing impulsive noise without degrading image contours, median filtering is a powerful tool. In multiband images, as for example color images or vector fields obtained by optic flow computation, a vector median filter can be used. Vector median filters are defined on the basis of a suitable distance, the best performing distance being the Euclidean. Euclidean distance is evaluated by using the Euclidean norm which is quite demanding from the point of view of computation given that a square root is required. In this paper an optimal piece-wise linear approximation of the Euclidean norm is presented which is applied to vector median filtering.

The evaluation of the number of bits that can be hidden within an image through digital watermarking is a crucial topic, which has been addressed only for additive watermarks. The evaluation of watermark capacity is very important because it allows to put a theoretical upper bound on the amount of information that can be hidden into an image by a given watermarking procedure, regardless of the watermark extraction technique. It is the purpose of this work to suggest a methodology for the evaluation of the watermark capacity in a nonadditive, non-Gaussian framework, and to discuss the results we obtained by applying it to a set of standard images.

In the last few years, digital watermarking has been proposed as a solution to the problem of copyright protection of multimedia data against unauthorized uses. In the field of image watermarking, research has been mainly focused on grey-scale image watermarking, whereas the extension to the color case is usually accomplished by marking the image luminance, or by processing each color channel separately. In this paper, a DCT domain technique expressly devised for watermarking of color images is presented, which exploits the characteristics of the human visual system and the correlation between the RGB image channels. Experimental results are presented to demonstrate the validity of the new approach with respect to algorithms operating on image luminance only.

Vector median filtering has been recently proposed as an effective method to refine estimated velocity fields. Here, the use of a weighted vector median filtering is suggested to improve the regularization of the optic flow field across motion boundaries. Information about the confidence of the estimated pixel velocities is exploited for the choice of the filter weights. Experimental results, on both synthetic and real-world sequences, show the effectiveness of the proposed procedure.

The interest in image watermarking techniques has rapidly grown during the years. Two requirements needed to be satisfied to use watermarking techniques for copyright protection are: unperceivability and robustness against image processing algorithms and forgery attacks. In particular, it is widely accepted that the exploitation of the characteristics of the human visual system should greatly help in satisfying both these requirements. Some solutions to the problem of building some perceptual masks for better hiding watermarks embedded in the full-frame DCT domain are presented. The results support the validity of the approach.

The interest in algorithms aimed at the estimation of object motion and aimed at simultaneous motion based image segmentation is rapidly increasing. Possible applications of such techniques can be found in many different fields, ranging from machine vision to video coding. In this paper an algorithm, based on least squares (LS), for the estimation of optical flow, and for the motion based segmentation of image sequences is described.

Digital watermarking has been proposed as a viable solution to the need of copyright protection and authentication of multimedia data in a networked environment, since it makes it possible to identify the author, owner, distributor or authorized consumer of a document. In this paper a new watermarking technique to add a code to digital images is presented; the method operates in the frequency domain embedding a pseudo-random sequence of real numbers in a selected set of DCT coefficients. Watermark casting is performed by exploiting the masking characteristics of the human visual system, to ensure watermark invisibility. The embedded sequence is extracted without resorting to the original image, so that the proposed technique represents a major improvement to methods relying on the comparison between the watermarked and original images. Experimental results demonstrate that the watermark is robust to most of the signal processing techniques and geometric distortions.

In the field of video coding the issues of backward prediction and standards conversion have focused an increasing attention towards techniques for an effective estimation of the true interframe motion. The problem of restoration of motion vector-fields computed by means of a standard block matching algorithm is addressed. The restoration must be carried out carefully by exploiting both the spatial correlation of the vector-field, and the significance of the obtained vectors as measures of the reliability of the previous estimation step. A novel approach matching both the above requirements is presented. Based on the theory of vector-median filters an adaptive scheme is developed and results are discussed.

The use of traffic monitoring techniques based on image processing algorithms for supervising urban vehicle flows could be very useful. Classical inductive loops can only compute traffic density on a single lane but are unable to estimate, for example, the behaviour of the vehicle flow at a crossroad. In this paper a system that estimates the turning rates at an urban crossroad by processing the sequence of images taken by a videocamera is presented. Block matching motion estimation, segmentation, and moving object tracking techniques are used. The good results obtained are presented and their relation to the camera position is discussed.

The progress of digital electroencephalography gave rise to the problem of EEG data recording. In the paper a DPCM scheme for EEG signal compression is discussed. In particular the performance of a class of predictors based on recurrent neural networks is presented. The training strategy is accurately described and the results of a comparison with some other classical linear and static neural predictors are given. The proposed recurrent neural predictor demonstrates to be competitive with the others in offering good performance at a very low computational cost.

For reducing impulsive noise without degrading image contours, median filtering is a powerful tool. In multiband images, as for example color images or vector field obtained by optic flow computation, a vector median filter can be used. Vector median filters are defined on the basis of a suitable distance, the best performing distance being the Euclidean. The Euclidean distance is computed by using the Euclidean norm which is quite demanding from the point of view of computation given that a square root is required. An optimal piecewise linear approximation of the Euclidean norm is presented which is applied to vector median filtering.

A system for coding video sequences at a low rate is presented. The system is very effective in coding sequences where motion is restricted to a not large area of each frame. Nevertheless knowledge based techniques are not used for not reducing the generalization power of the coding method. Techniques based on segmentation algorithms are used to encode both the displacement vector field and the prediction error image. Such techniques permit one to effectively distribute coding information in those areas of the image where it is required. Great care is given to a good estimation of motion of the scene objects: this is to reduce the amount of information to be coded in the prediction error image.>