9 July 1991 Implementing early vision algorithms in analog hardware: an overview
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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.
© (1991) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Christof Koch, "Implementing early vision algorithms in analog hardware: an overview", Proc. SPIE 1473, Visual Information Processing: From Neurons to Chips, (9 July 1991); doi: 10.1117/12.45546; https://doi.org/10.1117/12.45546


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