Research Projects (2003)

Most technological paper qualities are directly or indirectly influenced by the three-dimensional paper structure which means the spatial arrangement of fibres, fillers, pores and if necessary of the coating. In the area of the structure analysis, two main groups can be distinguished: destructive and non-destructive approaches.

The paper structure analysis methods have to fulfil the following basic requirements. The quality of the 3D data must be high enough to make an exact delimitation between the relevant paper contents possible. Furthermore the spatial resolution must at least lie in the area of a micron. In order to be able to make statistically reasonable statements for the complete paper sample, sizes of the range of at least one square centimetre must be analyzed. To conclude, the time expenditure to the digitalization of the paper sample should also lie within a practicable area of hours.

Primary objective of the project is the detailed analysis of the fibre network structure of a paper sample by means of image analysis methods. Still this application is an extremely complex problem and in this resolution (microns) and sample size (square centimetre) unsolved. Therefore the development of a completely new concept is necessary. This concept should finally make a general assignment of the three-dimensional paper structure to pre-defined paper-ingredients classes possible. As a final result the segmentation of single fibres and their three-dimensional tracking is realizable.

Soft tissue like tendons, arteries, veins or skins are important biological materials. A greater understanding of the foundations and interactions of structure and function of soft tissue, and, in particular, the associated mechanobiology is of great interest in the field. A thorough understanding of the complex interrelations between mechanical factors and the associated biological responses may help to improve diagnostics which allow disease and injury to be treated earlier. The research proposed here will develop a fully automatic system for analyzing macroscopic structures obtained from histological images of arteries by means of modern computer vision techniques. Besides being interesting from the mechanobiological point of view the structural analysis of images of collagen fibers poses also several challenging questions from a computer vision point of view. In particular, due to the wide variety of different appearances of collagen fibers in images this task is non trivial. The main task of this research is the development of novel segmentation techniques for robustly segmenting individual fibril bundles and estimating their parameters, like location and shape, fibril density, mean fibril orientation, wriggling of fibrils etc. This will be achieved by developing novel perceptual grouping methods operating on the extracted orientation data of fibrils. Another major challenge of this research is to extend the structural analysis from 2D to 3D.

Current paper and corresponding presentation

The concept of "directed evolution" is dependent on the availability of systems that allow the identification of interesting enzyme variants within a large, artificially generated diversity. Thus, one prerequisite is the availability of systems that allow the detection of specific enzyme features such as activity, selectivity, stability etc. at smallest culture scales and at high-throughput conditions. Therefore, focus is put on the development of methods witch are rapid, sensitive and cost-effective and preferably work at the microwell-plate, single colony or even single cell level.

Surrogate substrate analogues which would allow easy detection of reaction products by e.g. fluorescence techniques are not feasible due to the "First Law of Directed Evolution" which says "you get what you screen for". The "real" substrates should be converted or at least derivatives that are very close to these substrates have to be used in such systems. Therefore, general analytical methods which allow following the enzyme-catalyzed reaction of any desired substrate are developed.

Another important prerequisite is the availability of methods that allow a high degree of automation. Such methods include high throughput detection systems based on image analysis and software for accurately recognizing hits. In addition, statistical methods and systems for data management are developed to properly set up and evaluate the results of screening programs and to handle large data volumes.

Robust and Adaptive Approaches to Scene and Object Recognition: The goal of this joint project is to investigate new robust and adaptive approaches in the area of object and scene recognition. Object and scene recognition is a necessary requirement for developing truly cognitive systems as well as for the development of advanced and novel multimodal interfaces leading to ambient intelligence. Having a robust object and scene recognition system the following applications will greatly benefit: novel user interfaces which understand human activities, intelligent surveillance, indexing multi-media databases and content analysis of images, autonomous mobile systems and robotics, industrial inspection and robotics, etc. The goal is to develop computer vision based systems that can recognize objects, and in the context of environment perform localization and navigation. The major challenge is to develop systems and methods that can work under realistic unconstrained conditions (i.e., outside the lab). The three partners proposing this project (Center for Machine Perception, Czech Technical University Prague, CMP, Computer Vision Lab, Faculty of Computer and Information Science, University of Ljubljana, CVL, and Institute for Computer Graphics and Vision, Graz University of Technology ICG) have considerable expertise in this area and developed complementary methods and techniques. The goal of the project is to join the efforts and combine the expertise. In particular, we do the following activities:

• Organization of joint workshops and colloquia
• Exchange of PhD. students
• Joint research/joint papers