Andrew C. Jones

OLAF: The GOAD Active Database Event/Rule Tracer

In this paper we discuss OLAF, a tracing tool that we have developed which enables the active database designer to watch the flow of events and rules through our Active Database system (GOAD). We shall show how we use active rules to halt the execution of active components that we wish to trace, and demonstrate how our emphasis on generality of design enables us to trace each type of active component (i.e. primitive events, composite events, rules etc.) without making any additional changes to the tracer. We shall discuss the OLAF tracer itself, showing the facilities it provides and how it is integrated with the rest of the GOAD toolset.

Design and Implementation of an Active Object-Oriented Database Supporting Construction of Database Tools

We discuss the implementation of GOAD (Gemstone Object-oriented Active Database), an active object-oriented database built on top of GemStone. This system has been developed with the specific aim of supporting interface tools for the creation and maintenance of rule bases, and we give particular attention to explaining how GOAD is designed to meet this aim. We show how objects, classes and metaclasses can support a three level event model which integrates with the underlying system in an ‘open’ manner. Moreover, by providing a uniform interface to these different objects, we are providing support for the implementation of more generic tools. We discuss the design of the system and how we gather inherited rules at run-time in an efficient manner. We explain the problems that arise as a result of our desired mode of implementation and how they were circumvented. Finally we discuss our future work and specifically how we plan to implement tools for the easier creation of rule bases.

Visibility Issues in an active OODBMS

We discuss the design and implementation of an active object-oriented database built upon Gemstone, and an associated debugger. We concentrate upon the issue of visibility of ‘wrapping’ code, explaining why it is desirable for users of our system to be able to access and debug the code in both its ‘raw’ form and with the wrapping code hidden.

Software organization for a prolog-based prototyping system for machine vision

We describe PIP (prolog image processing)--a prototype system for interactive image processing using Prolog, implemented on an Apple Macintosh computer. PIP is the latest in a series of products that the third author has been involved in the implementation of, under the collective title Prolog+. PIP differs from our previous systems in two particularly important respects. The first is that whereas we previously required dedicated image processing hardware, the present system implements image processing routines using software. The second difference is that our present system is hierarchical in structure, where the top level of the hierarchy emulates Prolog+, but there is a flexible infrastructure which supports more sophisticated image manipulation which we will be able to exploit in due course . We discuss the impact of the Apple Macintosh operating system upon the implementation of the image processing functions, and the interface between these functions and the Prolog system. We also explain how the existing set of Prolog+ commands has been implemented. PIP is now nearing maturity, and we will make a version of it generally available in the near future. However, although the represent version of PIP constitutes a complete image processing tool, there are a number of ways in which we are intending to enhance future versions, with a view to added flexibility and efficiency: we discuss these ideas briefly near the end of the present paper.

Hypertext/Prolog user interface for a flexible inspection cell

An inexpensive but versatile human-computer interface (HCI) for a machine vision system is described. Widely available hardware and computing components are controlled by software based on HyperCard and Prolog. While considerable benefit is obtained using just one of these programming tools, it has been found that the combination provides many advantages, including ease of use and great flexibility. Details of what is possible using HyperCard and Prolog individually and both working in harmony are discussed.

Networks of intelligent multi-camera vision systems for industrial applications

The role of multicamera machine vision systems for the inspection of complex artifacts and assemblies, as well as the monitoring of manufacturing process, is briefly reviewed. There is a need for a vision system which allows images obtained using several different cameras to be digitized and then described in abstract symbolic terms. The representation of an image in this way enables logical inferences to be made about it, prior to inter-relating it to similar data derived from other cameras and/or the same camera at a different time. A distributed computing system, intended specifically for this type of task, is described in this article. It comprises several standard computers, connected together using a conventional data network. Each of these computers controls dedicated image processing hardware attached to it, using a Prolog program. These are called slaves and are controlled using another computer, termed the master, which provides overall control of all slaves attached to the network. There may be as many as 32 slaves, each one being able to operate up to 32 cameras. A similar network configuration could be used to control a set of image processing sub-systems, each one being implemented in software. A prototype network, incorporating three computers, has been built and demonstrated by the authors, who are now developing a model manufacturing system, with the intention of demonstrating the effectiveness of the network in monitoring and controlling industrial processes.

Multimedia extensions to prototyping software for machine vision

PIP (prolog image processing) is a prototyping tool, intended to assists designers of intelligent industrial machine vision systems. This article concentrates on the multi-media extensions to PIP, including: 1) on-line HELP, which allows the user to satisfy PIP goals from within the HELP facility, 2) lighting advisor, which gives advice to a vision engineer about which lighting/viewing arrangement is appropriate to use in a given situation, 3) device control, for operating a robot work cell, 4) speech input and (simple) natural language understanding, 5) speech synthesis, 6) remote operation of PIP via a local area network, and 7) remote operation of PIP via a local area network. At the time of writing, on-line access to PIP, via the Internet, is being developed.

Implementing full backtracking facilities for Prolog-based image processing

PIP (Prolog image processing) is a system currently under development at UWCC, designed to support interactive image processing using the PROLOG programming language. In this paper we discuss Prolog-based image processing paradigms and present a meta-interpreter developed by the first author, designed to support an approach to image processing in PIP which is more in the spirit of Prolog than was previously possible. This meta-interpreter allows backtracking over image processing operations in a manner transparent to the programmer. Currently, for space-efficiency, the programmer needs to indicate over which operations the system may backtrack in a program; however, a number of extensions to the present work, including a more intelligent approach intended to obviate this need, are mentioned at the end of this paper, which the present meta-interpreter will provide a basis for investigating in the future.

Software architecture for intelligent image processing using Prolog

We describe a prototype system for interactive image processing using Prolog, implemented by the first author on an Apple Macintosh computer. This system is inspired by Prolog+, but differs from it in two particularly important respects. The first is that whereas Prolog+ assumes the availability of dedicated image processing hardware, with which the Prolog system communicates, our present system implements image processing functions in software using the C programming language. The second difference is that although our present system supports Prolog+ commands, these are implemented in terms of lower-level Prolog predicates which provide a more flexible approach to image manipulation. We discuss the impact of the Apple Macintosh operating system upon the implementation of the image-processing functions, and the interface between these functions and the Prolog system. We also explain how the Prolog+ commands have been implemented. The system described in this paper is a fairly early prototype, and we outline how we intend to develop the system, a task which is expedited by the extensible architecture we have implemented.