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Proceedings Paper

Hierarchical texture motifs
Author(s): Shawn Newsam
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Paper Abstract

A fundamental challenge in analyzing spatial patterns in images is the notion of scale. Texture based analysis typically characterizes spatial patterns only at the pixel level. Such small scale analysis usually fails to capture spatial patterns that occur over larger scales. This paper presents a novel solution, termed hierarchical texture motifs, to this texture-of-textures problem. Starting at the pixel level, spatial patterns are characterized using parametric statistical models and unsupervised learning. Higher levels in the hierarchy use the same analysis to characterize the motifs learned at the lower levels. This multi-level analysis is shown to outperform single-level analysis in classifying a standard set of image textures.

Paper Details

Date Published: 27 February 2007
PDF: 9 pages
Proc. SPIE 6497, Image Processing: Algorithms and Systems V, 649708 (27 February 2007); doi: 10.1117/12.704749
Show Author Affiliations
Shawn Newsam, University of California, Merced (United States)

Published in SPIE Proceedings Vol. 6497:
Image Processing: Algorithms and Systems V
Jaakko T. Astola; Karen O. Egiazarian; Edward R. Dougherty, Editor(s)

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