Advances in Computing Sciences – serie

The calculus of relations has been an important component of the development of logic and algebra since the middle of the nineteenth century, when Augustus De Morgan observed that since a horse is an animal we should be able to infer that the head of a horse is the head of an animal. For this, Aristotelian syllogistic does not suffice: We require relational reasoning. George Boole, in his Mathematical Analysis of Logic of 1847, initiated the treatment of logic as part of mathematics, specifically as part of algebra. Quite the opposite conviction was put forward early this century by Bertrand Russell and Alfred North Whitehead in their Principia Mathematica (1910 - 1913): that mathematics was essentially grounded in logic. Logic thus developed in two streams. On the one hand algebraic logic, in which the calculus of relations played a particularly prominent part, was taken up from Boole by Charles Sanders Peirce, who wished to do for the "calculus of relatives" what Boole had done for the calculus of sets. Peirce's work was in turn taken up by Schroder in his Algebra und Logik der Relative of 1895 (the third part of a massive work on the algebra of logic). Schroder's work, however, lay dormant for more than 40 years, until revived by Alfred Tarski in his seminal paper "On the calculus of binary relations" of 1941 (actually his presidential address to the Association for Symbolic Logic).

Computer vision solutions used to be very specific and difficult to adapt to different or even unforeseen situations. The current development is calling for simple to use yet robust applications that could be employed in various situations. This trend requires the reassessment of some theoretical issues in computer vision. A better general understanding of vision processes, new insights and better theories are needed. The papers selected from the conference staged in Dagstuhl in 1996 to gather scientists from the West and the former eastern-block countries address these goals and cover such fields as 2D images (scale space, morphology, segmentation, neural networks, Hough transform, texture, pyramids), recovery of 3-D structure (shape from shading, optical flow, 3-D object recognition) and how vision is integrated into a larger task-driven framework (hand-eye calibration, navigation, perception-action cycle).

There is hardly a science that is without the notion of "system". We have systems in mathematics, formal systems in logic, systems in physics, electrical and mechanical engineering, architectural-, operating-, infonnation-, programming systems in computer science, management-and PJoduction systems in industrial applications, economical-, ecological-, biological systems, and many more. In many of these disciplines formal tools for system specification, construction, verification, have been developed as well as mathematical concepts for system modeling and system simulation. Thus it is quite natural to expect that systems theory as an interdisciplinary and well established science offering general concepts and methods for a wide variety of applications is a subject in its own right in academic education. However, as can be seen from the literature and from the curricula of university studies -at least in Central Europe-, it is subordinated and either seen as part of mathematics with the risk that mathematicians, who may not be familiar with applications, define it in their own way, or it is treated separately within each application field focusing on only those aspects which are thought to be needed in the particular application. This often results in uneconomical re-inventing and re-naming of concepts and methods within one field, while the same concepts and methods are already well introduced and practiced in other fields. The fundamentals on general systems theory were developed several decades ago. We note the pioneering work of M. A. Arbib, R. E. Kalman, G. 1. Klir, M. D.