Image Segmentation by Texture Using Pyramid Node Linking.

Abstract

In a 'pyramid' of successively reduced-resolution versions of an image, by linking nodes representing image blocks to nodes representing nearby larger blocks that most closely resemble them, we can construct trees (defined by the links) representing homogeneous parts of the input image. In this paper, we apply this approach to segmenting an image on the basis of texture. We start from an initial decomposition of the image into small blocks (e.g., 8 by 8); compute a textural property for each block, yielding an array of property values; build a 'pyramid' of reduced-resolution versions of this array; and apply the node linking process to this pyramid. The resulting trees define a segmentation of the original image into unions of the small blocks. This segmentation is similar to that obtained by minimum-error thresholding of the textural property values. Substantially better results are obtained when this 'bottom-up' block linking process is preceded by a 'top-down' process in which large homogeneous blocks are linked to all of their subblocks; the bottom-up linking is then used only for the blocks that were not linked by the top-down process. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1981
Accession Number
ADA098070

Entities

People

  • Azriel Rosenfeld
  • Matti Pietikäinen

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Accuracy
  • Applied Computer Science
  • Computations
  • Computer Science
  • Computer Vision
  • Computers
  • Decomposition
  • Errors
  • Filtration
  • Histograms
  • Image Processing
  • Image Segmentation
  • Iterations
  • Maryland
  • Pattern Recognition
  • Security
  • Universities

Fields of Study

  • Computer science

Readers

  • Graph Algorithms and Convex Optimization.
  • Image Processing and Computer Vision.
  • Operations Research