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Proceedings Paper

Hybrid solution for high-speed target acquisition and identification systems
Author(s): Gabriel Udomkesmalee; Marija Scholl; Michael S. Shumate
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Paper Abstract

A typical hierarchy for a general object recognition problem consists of object detection, classification and identification. Detection pinpoints the presence of an object or objects, classification categorizes the object(s), and identification distinguishes the object(s). This paper establishes necessary building blocks required for high-speed object recognition applications. An architecture that combines digital and optical processing, exploiting current image processing techniques for detection and classification, and optical processing hardware is described. An optical processing scheme is suggested for the identification aspect. Pre-processings that suppress background noise, minimize the number of matching filters and optimize post-processings of correlation outputs are performed by initially detecting objects in a background suppressed 2D scene via texture analysis and blob representation (detection), then scale/rotation estimation and shape recognition techniques (classification) are used as a precursor to optical processing. Post processing techniques which analyze and detect correlation peak(s) are also discussed. In addition, numerical results of each proposed concept are presented.

Paper Details

Date Published: 1 March 1991
PDF: 11 pages
Proc. SPIE 1468, Applications of Artificial Intelligence IX, (1 March 1991); doi: 10.1117/12.45451
Show Author Affiliations
Gabriel Udomkesmalee, Noetic Innovations Co. (United States)
Marija Scholl, Jet Propulsion Lab. (United States)
Michael S. Shumate, Jet Propulsion Lab. (United States)


Published in SPIE Proceedings Vol. 1468:
Applications of Artificial Intelligence IX
Mohan M. Trivedi, Editor(s)

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