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Proceedings Paper

Implementing early vision algorithms in analog hardware: an overview
Author(s): Christof Koch
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Paper Abstract

In the last ten years, significant progress has been made in understanding the first steps in visual processing. Thus, a large number of algorithms exist that locate edges, compute disparities, estimate motion fields and find discontinuities in depth, motion, color and intensity. However, the application of these algorithms to real-life vision problems has been less successful, mainly because the associated computational cost prevents real-time machine vision implementations on anything but large-scale expensive digital computers. We here review the use of analog, special-purpose vision hardware, integrating image acquisition with early vision algorithms on a single VLSI chip. Such circuits have been designed and successfully tested for edge detection, surface interpolation, computing optical flow and sensor fusion. Thus, it appears that real-time, small, power-lean and robust analog computers are making a limited comeback in the form of highly dedicated, smart vision chips.

Paper Details

Date Published: 9 July 1991
PDF: 15 pages
Proc. SPIE 1473, Visual Information Processing: From Neurons to Chips, (9 July 1991); doi: 10.1117/12.45546
Show Author Affiliations
Christof Koch, California Institute of Technology (United States)

Published in SPIE Proceedings Vol. 1473:
Visual Information Processing: From Neurons to Chips
Bimal P. Mathur; Christof Koch, Editor(s)

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