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Open AccessJournal ArticleDOI

The Illinois Pattern Recognition Computer-ILLIAC III

TLDR
The Pattern Articulation Unit is the first modular parallel processor which is capable of more reliable visual identification than part analog/part digital preprocessors of much less generality and potential virtuosity and can serve as a prototype to a new generation of parallel computers that will capitalize upon thin film and integrated semiconductor circuitry of the immediate future.
Abstract
This report describes the system design of an all-digital computer for visual recognition. One processor, the Pattern Articulation Unit (PAU), has been singled out for detailed discussion. Other units, in particular the Arithmetic Unit and the Taxicrinic Unit, are treated in reports listed in the bibliography. The PAU has been shown to be a processor of fundamentally new design-its logical organization has no analog in the central processing unit of existing computers. The PAU is the first modular parallel processor which because of its digital organization is capable of more reliable visual identification than part analog/part digital preprocessors of much less generality and potential virtuosity; is faster than any presently suggested alternative realizable today at comparable cost; and can serve as a prototype to a new generation of parallel computers that will capitalize upon thin film and integrated semiconductor circuitry of the immediate future.

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Citations
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Patent

Bit enable circuitry for an image analyzer system

TL;DR: In this paper, a serial neighborhood transformation (SND) is used for analyzing patterns made up of a matrix of points, with each point being represented by a multi-bit digital electrical signal.
Patent

Image analyzer with cyclical neighborhood processing pipeline

TL;DR: In this paper, a transformation control logic in each stage is operative for analyzing the pixels contained in the neighborhood extraction portion and provides a transformation output signal to the next stage in the pipeline.
Journal ArticleDOI

Parallel Detection of Concavities in Cellular Blobs

TL;DR: It is shown how any such MPP may be computed by a sequence of simultaneous local operations in a parallel-structured computer, and that the ratio of computation times for sequential algorithms to those for parallel algorithms operating on the cellular image of a large circular blob is approximately proportional to the square root of the blob's perimeter.
BookDOI

Real-time/parallel computing

TL;DR: The main subject areas covered are theoretical development, languages for image processing, new computer techniques, and implementation in special purpose real-time digital systems.
Journal ArticleDOI

A dynamic associative processor for machine vision applications

TL;DR: The use of massively parallel associative processors as coprocessors for accelerating machine vision applications is considered, and a dense, dynamic, content-addressable memory cell supports fully parallel operation, and pitch-matched word logic improves arithmetic performance with minimal area cost.