Image Understanding for Database Query.
Abstract
The objective of the Image Understanding for Database Query (IU4DBQ) effort was to combine the powerful reasoning capabilities of the Loom knowledge representation system with the extensive image processing and feature extraction capabilities of KB Vision TM. Another important aspect of this effort was to apply the algorithms developed to realistic reconnaissance imagery. A major challenge was to integrate Loom and KB Vision TM within a useful context for the softcopy reconnaissance imagery available in the Rome Laboratory (RL) IE 2000 facility. The most practical use for Loom is to query the imagery server databases and determine images that have specific characteristics that are most suitable for processing. This suitability is based on the target area of interest, the presence of unconfirmed targets, and the quality of the imagery.
Document Details
- Document Type
- Technical Report
- Publication Date
- Apr 01, 1997
- Accession Number
- ADA327320
Entities
People
- Charles Ferrara
- Scott Barrett