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articleTop 1% cited

Texture features for browsing and retrieval of image data

B.S. ManjunathWeixin Ma

Abstract

Image content based retrieval is emerging as an important research area with application to digital libraries and multimedia databases. The focus of this paper is on the image processing aspects and in particular using texture information for browsing and retrieval of large image data. We propose the use of Gabor wavelet features for texture analysis and provide a comprehensive experimental evaluation. Comparisons with other multiresolution texture features using the Brodatz texture database indicate that the Gabor features provide the best pattern retrieval accuracy. An application to browsing large air photos is illustrated.

Image Retrieval and Classification TechniquesAdvanced Image and Video Retrieval TechniquesMedical Image Segmentation TechniquesComputer scienceImage retrievalImage textureFocus (optics)Texture (cosmology)Artificial intelligenceVisual WordGabor waveletAutomatic image annotationContent-based image retrieval

Funding

  • National Science Foundation
  • National Aeronautics and Space Administration
  • University of California, Santa Barbara
Citations
3,708
FWCI
49.16
field-weighted impact
References
21
Percentile
100%
vs. same field & year
Citations per year
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References
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IEEE Transactions on Computers · 1993 · 1,811 citations
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IEEE Transactions on Pattern Analysis and Machine Intelligence · 1993 · 3,232 citations
Texture features for browsing and retrieval of image data
IEEE Transactions on Pattern Analysis and Machine Intelligence · 1996 · 3,708 citations
<title>Photobook: tools for content-based manipulation of image databases</title>
Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1994 · 883 citations
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