Knowledge Based Image Processing Systems
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Knowledge-Based Image Processing Systems
Author: Deryn Graham
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
Knowledge-based (or expert systems) and image processing have been applied to many domains but, although both fields frequently address common application areas, they are rarely applied together. Often a combined knowledge-based system and image processing approach can be highly appropriate and this book provides an insight into both areas and show students how a judicious mix of the two can result in a more effective system. The authors include detailed case studies to illustrate the two approaches as well as worked examples and solutions to problems throughout the text. Third and fourth year undergraduates and MSc students with some computer science background will find this book invaluable. Postgraduates and researchers looking for an introduction to either area - or ways to combine the two - will also welcome this clearly written and comprehensive text.
Managing the Change: Software Configuration and Change Management
Author: Michael Haug
language: en
Publisher: Springer Science & Business Media
Release Date: 2001-10-23
C. Amting Directorate General Information Society, European Commission, Brussels th Under the 4 Framework of European Research, the European Systems and Soft ware Initiative (ESSI) was part of the ESPRIT Programme. This initiative funded more than 470 projects in the area of software and system process improvements. The majority of these projects were process improvement experiments carrying out and taking up new development processes, methods and technology within the software development process of a company. In addition, nodes (centres of exper tise), European networks (organisations managing local activities), training and dissemination actions complemented the process improvement experiments. ESSI aimed at improving the software development capabilities of European enterprises. It focused on best practice and helped European companies to develop world class skills and associated technologies to build the increasingly complex and varied systems needed to compete in the marketplace. The dissemination activities were designed to build a forum, at European level, to exchange information and knowledge gained within process improvement ex periments. Their major objective was to spread the message and the results of experiments to a wider audience, through a variety ofdifferent channels. The European Experience Exchange (tUR~X) project has been one ofthese dis semination activities within the European Systems and Software Initiative.~UR~X has collected the results of practitioner reports from numerous workshops in Europe and presents, in this series of books, the results of Best Practice achieve ments in European Companies over the last few years.
Knowledge-based Image Analysis
The work reported was directed toward employing a priori knowledge in the automatic analysis of aerial imagery. Major objectives of the research were directed toward (1) map-guided registration, (2) verification of geographic data bases extracted from imagery, (3) enrichment of geographic data bases, and (4) automatic terrain feature extraction using multiple sources of knowledge and multi-level decision making. The key component in all of the work was the matching of existing iconic structure in a geographic data base (GDB) with detected image structure. By using iconic knowledge, the image interpretation paradigm becomes a three step process. First, some primitive features of the imagery must be recognized without any area-specific knowledge. Second, the imagery is aligned or registered with the knowledge base by drawing correspondences between the image features and their iconic analogues in the GDB. The matching is formalized by derivation of a transformation which maps points (x, y) of the image to points (u, v) in GDB coordinates. The final step of the process is the analysis of those parts of the image which were not successfully interpreted in steps 1 and 2. This implies a top-down search for image structures which correspond to features in the GDB. Section 2 of the report treats primitive extraction. The emphasis is currently on lineal, point, and region features only. A method for automatically inferring a rotation and translation transforming image to map is given in Section 3. Classification of registered regions is discussed in Section 4. Verification of lineal GDB features in gray-scale imagery is introduced in Section 5. (Author).