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Proceedings Paper

Two-level processing for real-time image understanding
Author(s): Tadashi Ae; Hiroyuki Araki; Saku Hiwatashi; Ken-ichi Katakawa
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Paper Abstract

A two-level processing scheme for real-time image understanding is proposed, where an example-based reasoning in neural AI systems is introduced. The system has tow levels; component level and structure level. At the component level, an elementary pattern recognition is performed as in the conventional pattern recognition, while the syntax pattern recognition is done at the structure level. Both levels are essentially time-consuming. The pattern recognition assisted by syntax recognition reduces the total complexity of processes, and the system can perform a real-time image understanding, when the VLSI chips are introduced. As a result, we show a reasonable real-time image understanding scheme by introducing a neural pattern recognition at the component level and a case-based AI technique at the structure level.

Paper Details

Date Published: 3 April 1997
PDF: 12 pages
Proc. SPIE 3028, Real-Time Imaging II, (3 April 1997); doi: 10.1117/12.270333
Show Author Affiliations
Tadashi Ae, Hiroshima Univ. (Japan)
Hiroyuki Araki, Hiroshima Univ. (Japan)
Saku Hiwatashi, Hiroshima Univ. (Japan)
Ken-ichi Katakawa, Hiroshima Univ. (Japan)

Published in SPIE Proceedings Vol. 3028:
Real-Time Imaging II
Divyendu Sinha, Editor(s)

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