Knowledge-Based Image Understanding: A Rule-Based Production System for X-Ray Segmentation

Image Understanding (IU) concerns the issues of how to interpret images. Knowledge-based image understanding studies the theory and techniques of computational image understanding, which uses explicit, independent knowledge about the images, such as their context and objects in them, as well as knowledge about the imaging system. Two related disciplines, Artificial Intelligence (AI) and Image Processing (IP), can contribute significantly to image understanding. A rule-based production system is a widely used knowledge representation technique, which may be used to capture various kinds of knowledge, such as perceptual, functional, and semantic knowledge, in image understanding system. This paper addresses some issues of knowledge-based approach to image understanding, presents a rule-based production system for X-ray segmentation, and proposes its expansion of incorporation with multiple knowledge sources. Here we just present the segmentation part of our research project, which aims at applying knowledge-based approach to interpret X-ray images of bone and to identify the fractured regions.

[1]  Anil K. Jain,et al.  Statistical Pattern Recognition: A Review , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  O. Reiser,et al.  Principles Of Gestalt Psychology , 1936 .

[3]  James G. Shanahan Soft Computing for Knowledge Discovery , 2000 .

[4]  Martin D. Levine,et al.  Low Level Image Segmentation: An Expert System , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.