The Use Of A Priori Knowledge In The Analysis Of Fringe Patterns

Abstract

Considerable claims have been made for knowledge-based systems; see e.g. (1). However it would appear that their impact in industrial and commercial applications has been small (1). This may be attributed at least partly to their isolation from other disciplines such as numerical methods and traditional pattern recognition. The aim of the project discussed here is to automatically analyse the photoelastic fringe patterns. Rather than construct a stand-alone expert system as outlined in (2), the authors have attempted to combine the best features from different methods in a joint knowledge-based system'. A 'traditional' knowledge elicitation exercise was used to break down the task into its component parts. Each stage was then considered for the best method to be adopted. The first stage, described elsewhere (3), (4), (5) uses adapted image processing methods to rapidly provide much useful information about the image. The remaining stages are concerned with furthering the analysis by using the results from image processing coupled with a priori knowledge of the image. The system is interactive, and allows for a flexible balance between human and machine judgement. This balance is determined by the quality of the information obtained from low level image processing, and the precision of the knowledge concerning the fringe pattern. Case study results will be presented to illustrate the approach, and some guidelines presented describing the most appropriate use of knowledge in the analysis of photoelastic fringe patterns.