Abstract
Intelligent surveillance is becoming increasingly important for the enhanced protection of facilities such as airports and power stations from various types of threats. We propose a surveillance system architecture based on multiple sources of information to apply on large scale surveillance networks. The main contribution of this paper is the definition of the requirements for a flexible and scalable architecture that supports intelligent surveillance using, alongside video, different sources of information, such as audio or other sensors.

Abstract
Higher-order statistics extend the analysis methods of non-linear systems and non-gaussian signals based on the autocorrelation and power spectrum. The main drawback of their use in real time applications is the high complexity of their estimation due to the large number of arithmetic operations. This paper presents an experimental vector architecture for the estimation of the higher-order moments. The processor's core is a pipelined multiply-accumulate unit that receives four data vectors and computes in parallel the moment taps up to the fourth-order. The design of custom cache memory organization and address generation circuits has led to more than 11 operations per clock cycle. The architecture was modeled and simulated in Verilog and is presently being implemented in XILINX field-programmable gate arrays (FPGAs) and one custom integrated circuit for the multiply-accumulate unit.

Abstract
Living Usability Lab for Next Generation Networks (www.livinglab.pt) is a Portuguese industry-academia collaborative R&D project, active in the field of live usability testing, focusing on the development of technologies and services to support healthy, productive and active citizens. The project adopts the principles of universal design and natural user interfaces (speech, gesture) making use of the benefits of next generation networks and distributed computing. Therefore, it will have impact on the general population, including the elderly and citizens with permanent or situational special needs. This paper presents project motivations, conceptual model, architecture and work in progress.

Abstract
A wide variety of automatic image registration methods have been proposed in the last years. However, under the scope of remote sensing applications, geometric correction is still mostly a manual work. A methodology for automatic image registration is proposed, which consists in three major steps: pre-processing, segmentation, and registration. The considered pre-processing is a new method, which is an iterative process based on a joint histogram analysis. Regarding the segmentation stage, global thresholding and a new method were used. The later comprises global thresholding and distance transforms in a single method. For both methods the following object properties were extracted: area, major and minor axis lengths of the adjusted ellipse and perimeter. The registration phase incorporates the matching of corresponding objects, a template matching technique to compute the distance between each pair of matched objects, and the computation of the transformation function parameters. The used dataset consisted in the pairs ETM+/ASTER, ETM+/SPOT and Orthophoto/IKONOS. The proposed methodology allows for the registration of a pair of images with translation and rotation effects, and to some extent with different spectral content, leading to a subpixel accuracy. Furthermore, it has been shown that the proposed pre-processing method allowed for the achievement of suitable segmented objects for later matching, even using global thresholding. © 2009 SPIE.

Abstract
Automatic image registration is a process related to various application fields such as remote sensing, medicine, computer vision, among others. Particularly in remote sensing, the ever increasing number of available satellite images asks for automatic image registration methods, capable of correctly align a new image. An automatic image registration method is proposed, based on the identification of a thin line through the Hough transform, from the diagonal brighter strip visible on the correlation images. This procedure is applied for both directions. Dividing an image into tiles and taking the center of each tile as a point, a geometric correction at the subpixel level may be achieved. Measures for an objective assessment of the geometric correction quality are also proposed, as a complement to the traditional RMS of the errors and visual inspection. An orthorectified Landsat image and an ASTER image with an approximate geometric correction were used. The images were superimposed and resampled. An image registration with subpixel accuracy was achieved. The proposed methodology has showed to be able to correctly align two images, having a priori a "gold standard" image covering a considerable part of the image to be registered. © 2008 SPIE.

Abstract
Line scratches and blotches are two of the most common and annoying artifacts of image sequences. A digital restoration chain for the removal of these artifacts was conceived and implemented. The basic elements of the chain are the digital encoder, the artifact generator, tile artifact detectors, the interpolators and the quality measurer. The digital encoder has the mission to convert analogue sequences into digital ones and, if necessary, to make a format conversion. The artifact generator allows quantitative and qualitative tests of the restoration algorithms. If we have access to the original non-degraded sequence we can add, in a controlled way, artifacts with the generator, and then measure efficiently the quality of the restoration algorithms, since we have the original, the degraded and the restored sequences to compare. In a real restoration process, the degraded sequence is directly applied to the artifact detector. The artifact detector finds the degraded regions in tile image and, somehow, marks them. Tile interpolator replaces the marked degraded pixels with others that are the result of an interpolation algorithm. Finally, the quality measurer rates the quality of the restored sequence.