The Representation of Image Texture.

Abstract

This thesis explores how to represent image texture in order to obtain information about the geometry and structure of surfaces, with particular emphasis on locating surface discontinuities. Theoretical and psychophysical results lead to the following conclusions for the representation of image texture: (1) A texture edge primitive is needed to identify texture change contours, which are formed by an abrupt change in the 2-D organization of similar items in an image. The texture edge can be used for locating discontinuities in surface structure and surface geometry and for establishing motion correspondence; (2) Abrupt changes in attributes that vary with changing surface geometry -- orientation, density, length, and width -- should be used to identify discontinuities in surface geometry and surface structure; (3) Texture tokens are needed to separate the effects of different physical processes operating on a surface. They represent the local structure of the image texture. Their spatial variation can be used in the detection of texture discontinuities and texture gradients, and their temporal variation may be used for establishing motion correspondence. What precisely constitutes the texture tokens is unknown; it appears, however, that the intensity changes alone will not suffice, but local groupings of them may; and (4) The above primitives need to be assigned rapidly over a large range in an image. (Author)

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1981
Accession Number
ADA107636

Entities

People

  • Michael Dennis Riley

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Boundaries
  • Change Detection
  • Computer Science
  • Computer Vision
  • Contrast
  • Convolution
  • Data Displays
  • Detection
  • Geometry
  • Illumination
  • Intensity
  • Order Statistics
  • Orientation (Direction)
  • Recognition
  • Three Dimensional
  • Two Dimensional

Readers

  • Computer Vision.
  • Systems Analysis and Design