ISES - an image segmentation expert system for aerial photographs based on the use of edge and texture features
A major problem in implementing an image understanding system (such as a photo-interpretation system or a robot vision system) is to segment images into disjoint regions of uniform gray tone or texture. This dissertation presents a new image segmentation expert system (ISES) approach for solving this problem based on the use of both edge and texture features. The ISES is composed of two parts: (1) image processing tools that process images by localized brightness compensation (LBC), heuristic edge extraction (HEE), and region formation (RF), and (2) a knowledge-based controller composed of an inference engine, rule base, and hypothesis base. The LBC is a preprocessing operation for an input image for improving the image quality. The HEE is used to obtain spatially accurate, one pixel wide boundaries of uniform regions. The RF operation contains a new version of the A/sup */ algorithm (minimum-cost search) and a modified Fisher's pattern classification scheme based on the simultaneous use of both edge and texture features. The software of the ISES was implemented on the PRIME 750 Computer and DeAnza image display system in the RPI Image Processing Laboratory. It was also implemented on a VAX/VMS 785 Computer and Raster Technologies image display system.
- Research Organization:
- Rensselaer Polytechnic Inst., Troy, NY (USA)
- OSTI ID:
- 6683833
- Resource Relation:
- Other Information: Thesis (Ph. D.)
- Country of Publication:
- United States
- Language:
- English
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