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Proceedings Paper

A Rule-Based High-Level Vision System
Author(s): Michael J. Conlin
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Paper Abstract

This Paper Discusses A High-Level Knowledge-Based Vision System. We Have Implemented A Human Face Recognition System In Ops83, A Rule-Based Production System Language. The System Currently Is Capable Of Identifying The Components Of A Human Face From An Input Set Of Line Segments In A Manner Consistent With That Performed By Human Observers. The System Consists Of Independent Modules (Knowledge Sources), Each Of Which Is Capable Of Recognizing/Detecting A Particular Component Of The Face (E.G. Eye, Nose, Etc.) In An Image. Each Knowledge Source Posts, To A Section Of Memory, Information Regarding What Is Recognized And An Associated Confidence Level. This Global Data Area, The Blackboard, Allows The Posted Information To Be Available To All The Knowledge Sources. The Sharing Of Results Among The Knowledge Sources Provides Flexibility Such That The System Operates With Incomplete Image Information. The Extracted Results From The Knowledge Sources Are Evaluated And The Highest Confidence Face Is Presented.

Paper Details

Date Published: 27 March 1987
PDF: 8 pages
Proc. SPIE 0726, Intelligent Robots and Computer Vision V, (27 March 1987); doi: 10.1117/12.937743
Show Author Affiliations
Michael J. Conlin, Carnegie Group Inc. (United States)


Published in SPIE Proceedings Vol. 0726:
Intelligent Robots and Computer Vision V
David P. Casasent, Editor(s)

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