3 April 1997 Two-level processing for real-time image understanding
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Proceedings Volume 3028, Real-Time Imaging II; (1997); doi: 10.1117/12.270333
Event: Electronic Imaging '97, 1997, San Jose, CA, United States
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.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tadashi Ae, Hiroyuki Araki, Saku Hiwatashi, Ken-ichi Katakawa, "Two-level processing for real-time image understanding", Proc. SPIE 3028, Real-Time Imaging II, (3 April 1997); doi: 10.1117/12.270333; http://dx.doi.org/10.1117/12.270333
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KEYWORDS
Image processing

Scanning tunneling microscopy

Image understanding

Pattern recognition

Neural networks

Network architectures

Neurons

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