Share Email Print
cover

Proceedings Paper

Artificial Intelligence In Image Processing
Author(s): John F. Gilmore
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Image processing technology concentrates on the development of data extraction techniques applied toward the statistical classification of visual imagery. In classical image processing systems, an image is [1] preprocessed to remove noise, [2] segmented to produce close object boundaries, [3] analyzed to extract a representative feature vector, and [4] compared to ideal object feature vectors by a classifier to determine the nearest object classification and its associated confidence level. This type of processing attempts to formulate a two-dimensional interpretation of three-dimensional scenes using local statistical analysis, an entirely numerical process. Symbolic information dealing with contextual relationships, object attributes, and physical constraints is ignored in such an approach. This paper describes a number of artificial intelligence techniques which allow symbolic information to be exploited in conjunction with numerical data to improve object classification performance.

Paper Details

Date Published: 22 July 1985
PDF: 10 pages
Proc. SPIE 0528, Digital Image Processing, (22 July 1985); doi: 10.1117/12.946419
Show Author Affiliations
John F. Gilmore, Georgia Tech Research Institute (United States)


Published in SPIE Proceedings Vol. 0528:
Digital Image Processing
Andrew G. Tescher, Editor(s)

© SPIE. Terms of Use
Back to Top