Multi-Image Pattern Recognition: Ideas and Results.

Abstract

A tutorial introduction to some of the pattern recognition problems is presented in a unified perspective. Special concentrated effort is given to pattern recognition techniques for use with sequential data especially multi-image data sets. Some of these techniques are experimentally tested on a photographic data set. The following are among the original pattern recognition techniques presented; identifying a data set with a measure of association, spatial quantizing, measurement space clustering, spatial clustering, texture analysis, registering and congruencing images. The spatial quantizing and spatial clustering techniques were tested with some imagery from Michigan's 12 channel scanner system. The spatial quantizing procedure produced a better quality quantized image than the linearly quantized image. The spatial clustering procedure produced a map of the natural homogeneous classes of environmental objects seen like the sensor sees them. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1969
Accession Number
AD0863596

Entities

People

  • Robert M. Haralick

Organizations

  • University of Kansas

Tags

DTIC Thesaurus Topics

  • Clustering
  • Data Sets
  • Measurement
  • Pattern Recognition
  • Recognition

Readers

  • Computer Vision.

Technology Areas

  • AI & ML
  • Space
  • Space - Space Objects