The proceedings contain 15 papers. The topics discussed include: review of machine vision architectures;a comparison of the wire frame and mathematical morphology approaches to machine vision;normalized correlation se...
The proceedings contain 15 papers. The topics discussed include: review of machine vision architectures;a comparison of the wire frame and mathematical morphology approaches to machine vision;normalized correlation search in alignment, gauging, and inspection;advanced image-processing architectures for machine vision;recognition methodology: algorithms TGZ architecture;an analysis of hypercube architectures for imagepatternrecognitionalgorithms;optical patternrecognition and ai algorithms and architectures for ATR and computer vision;tools for productive development of image analysis algorithms;and user interface design for a general purpose patternrecognition package.
Hypercube architectures are introduced. The reasons behind their becoming the first widespread commercial massively parallel processors are outlined. A classification for imagepatternrecognition is proposed and char...
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A critique is provided which first analyzes the nature of image processing (machine vision) algorithm development. The critical need for, and the pre-requisite techniques for, addressing improved productivity of algor...
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The success of a variety of techniques in patternrecognition led to a sense that patternrecognition was "a solved problem" and a mature discipline. Simultaneously, the appearance of methods of Artificial I...
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Researchers with backgrounds in fields other than patternrecognition are becoming increasingly aware of the contribution that quantitative image analysis and patternrecognition can make in their work. These unlimite...
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Computer recognition and inspection of objects is, in general , a complex procedure requiring a variety of kinds of steps which successively transform the iconic data to recognition information. We hypothesize that th...
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Computer recognition and inspection of objects is, in general , a complex procedure requiring a variety of kinds of steps which successively transform the iconic data to recognition information. We hypothesize that the difficulty of today's computer vision and recognitiontechnology to be able to handle unconstrained environments is due to the fact that the existing algorithms are specialized and do not develop one or more of the necessary steps to a high enough degree. Our thesis is that there are no shortcuts. A recognition methodology must pay substantial attention to each of the following five steps: conditioning, labeling, grouping, extracting, and matching.
Optical patternrecognition has provided many attractive algorithms and architecture for advanced use in Automatic Target recognition (ATR) and computer vision. This work is reviewed and highlighted in this paper. Att...
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Many types of image processing operations can be performed sequentially at frame rates, but many of the global operations needed in computer vision systems cannot be performed in real time unless suitable parallel har...
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A description is given of a prototype address block finding system which is currently under development. This system is intended to support a wider application of machine vision and robotic technologies for the handli...
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