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Texture segmentation using hierarchical wavelet decomposition

Authors
Journal
Pattern Recognition
0031-3203
Publisher
Elsevier
Publication Date
Volume
28
Issue
12
Identifiers
DOI: 10.1016/0031-3203(95)00054-2
Keywords
  • Texture Segmentation
  • Wavelet Transform
  • Clustering Algorithm
  • Multiresolution Segmentation
Disciplines
  • Computer Science

Abstract

Abstract This paper presents a texture segmentation algorithm based on a hierarchical wavelet decomposition. Using Daubechies four-tap filter, an original image is decomposed into three detail images and one approximate image. The decomposition can be recursively applied to the approximate image to generate a lower resolution of the pyramid. The segmentation starts at the lowest resolution using the K-means clustering scheme and textural features obtained from various sub-bands. The result of segmentation is propagated through the pyramid to a higher resolution with continuously improving the segmentation. The lower resolution levels help to build the contour of the segmented texture, while higher levels refine the process, and correct possible errors.

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