Integration of Virtual Map Rooms as a support tool in historical and social research

At the present time almost all map libraries on the Internet are image collections generated by the digitization of early maps. This type of graphics files provides researchers with the possibility of accessing and visualizing historical cartographic information keeping in mind that this information has a degree of quality that depends upon elements such as the accuracy of the digitization process and proprietary constraints (e.g. visualization, resolution downloading options, copyright, use constraints). In most cases, access to these map libraries is useful only as a first approach and it is not possible to use those maps for scientific work due to the sparse tools available to measure, match, analyze and/or combine those resources with different kinds of cartography. This paper presents a method to enrich virtual map rooms and provide historians and other professional with a tool that let them to make the most of libraries in the digital era.

Single optical surface imaging designs with unconstrained object to image mapping

In this work, novel imaging designs with a single optical surface (either refractive or reflective) are presented. In some of these designs, both object and image shapes are given but mapping from object to image is obtained as a result of the design. In other designs, not only the mapping is obtained in the design process, but also the shape of the object is found. In the examples considered, the image is virtual and located at infinity and is seen from known pupil, which can emulate a human eye. In the first introductory part, 2D designs have been done using three different design methods: a SMS design, a compound Cartesian oval surface, and a differential equation method for the limit case of small pupil. At the point-size pupil limit, it is proven that these three methods coincide. In the second part, previous 2D designs are extended to 3D by rotation and the astigmatism of the image has been studied. As an advanced variation, the differential equation method is used to provide the freedom to control the tangential rays and sagittal rays simultaneously. As a result, designs without astigmatism (at the small pupil limit) on a curved object surface have been obtained. Finally, this anastigmatic differential equation method has been extended to 3D for the general case, in which freeform surfaces are designed.

Implementation techniques for evolvable HW systems: virtual vs. dynamic reconfiguration

Adaptive hardware requires some reconfiguration capabilities. FPGAs with native dynamic partial reconfiguration (DPR) support pose a dilemma for system designers: whether to use native DPR or to build a virtual reconfigurable circuit (VRC) on top of the FPGA which allows selecting alternative functions by a multiplexing scheme. This solution allows much faster reconfiguration, but with higher resource overhead. This paper discusses the advantages of both implementations for a 2D image processing matrix. Results show how higher operating frequency is obtained for the matrix using DPR. However, this is compensated in the VRC during evolution due to the comparatively negligible reconfiguration time. Regarding area, the DPR implementation consumes slightly more resources due to the reconfiguration engine, but adds further more capabilities to the system.

MIA - a free and open source software for gray scale medical image analysis

Background Gray scale images make the bulk of data in bio-medical image analysis, and hence, the main focus of many image processing tasks lies in the processing of these monochrome images. With ever improving acquisition devices, spatial and temporal image resolution increases, and data sets become very large. Various image processing frameworks exists that make the development of new algorithms easy by using high level programming languages or visual programming. These frameworks are also accessable to researchers that have no background or little in software development because they take care of otherwise complex tasks. Specifically, the management of working memory is taken care of automatically, usually at the price of requiring more it. As a result, processing large data sets with these tools becomes increasingly difficult on work station class computers. One alternative to using these high level processing tools is the development of new algorithms in a languages like C++, that gives the developer full control over how memory is handled, but the resulting workflow for the prototyping of new algorithms is rather time intensive, and also not appropriate for a researcher with little or no knowledge in software development. Another alternative is in using command line tools that run image processing tasks, use the hard disk to store intermediate results, and provide automation by using shell scripts. Although not as convenient as, e.g. visual programming, this approach is still accessable to researchers without a background in computer science. However, only few tools exist that provide this kind of processing interface, they are usually quite task specific, and don’t provide an clear approach when one wants to shape a new command line tool from a prototype shell script. Results The proposed framework, MIA, provides a combination of command line tools, plug-ins, and libraries that make it possible to run image processing tasks interactively in a command shell and to prototype by using the according shell scripting language. Since the hard disk becomes the temporal storage memory management is usually a non-issue in the prototyping phase. By using string-based descriptions for filters, optimizers, and the likes, the transition from shell scripts to full fledged programs implemented in C++ is also made easy. In addition, its design based on atomic plug-ins and single tasks command line tools makes it easy to extend MIA, usually without the requirement to touch or recompile existing code. Conclusion In this article, we describe the general design of MIA, a general purpouse framework for gray scale image processing. We demonstrated the applicability of the software with example applications from three different research scenarios, namely motion compensation in myocardial perfusion imaging, the processing of high resolution image data that arises in virtual anthropology, and retrospective analysis of treatment outcome in orthognathic surgery. With MIA prototyping algorithms by using shell scripts that combine small, single-task command line tools is a viable alternative to the use of high level languages, an approach that is especially useful when large data sets need to be processed.

A Dynamically Adaptable Image Processing Application Trading Off Between High Performance, Consumption and Dependability in Real Time

As embedded systems evolve, problems inherent to technology become important limitations. In less than ten years, chips will exceed the maximum allowed power consumption affecting performance, since, even though the resources available per chip are increasing, frequency of operation has stalled. Besides, as the level of integration is increased, it is difficult to keep defect density under control, so new fault tolerant techniques are required. In this demo work, a new dynamically adaptable virtual architecture (ARTICo3) to allow dynamic and context-aware use of resources is implemented in a high performance Wireless Sensor node (HiReCookie) to perform an image processing application.