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Fundamental Structures for the Design of Machine Vision Systems

Authors
  • Johnson, Jeffrey1
  • Simon, Jean-Claude2
  • 1 The Open University, Design and Innovation, Milton Keynes, England , Milton Keynes
  • 2 A2iA, 222 Avenue du Maine, Paris, 75014, France , Paris
Type
Published Article
Journal
Mathematical Geology
Publisher
Kluwer Academic Publishers-Plenum Publishers
Publication Date
Apr 01, 2001
Volume
33
Issue
3
Pages
331–352
Identifiers
DOI: 10.1023/A:1007638323533
Source
Springer Nature
Keywords
License
Yellow

Abstract

The chicken-and-egg problem of machine vision is that (a) abstracting objects requires images to be segmented, (b) segmentation requires greyscale statistics, (c) greyscale statistics are defined by segmented regions, and this leads back to (a). New image structures called gradient runs and gradient polygons are presented. These lead to new types of three-dimensional histograms.The histogram of a whole image mixes histograms from different regions within the image. These regions and their histrograms may need separating. Global histrograms can be used for preliminary segmentations. These then generate new historagms of the statistics for more coherent locally structured regions. These ideas have used to binarise documents for automated document reading systems, and they may be developed in the desingn of machine vision systems for other areas of application.

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