Texture analysis and clustering using the Wigner distribution

Clustering (or grouping), defined as the taxonomy of objects (image regions) into categories based on the similarity of their characteristics, is examined. Both in computer and human vision, the use of joint spatial/spatial-frequency (s/sf) representations in this process are suggested. The Wigner a...

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Bibliographic Details
Published in[1988 Proceedings] 9th International Conference on Pattern Recognition pp. 770 - 772 vol.2
Main Authors Reed, T.R., Wechsler, H.
Format Conference Proceeding
LanguageEnglish
Published IEEE Comput. Soc. Press 1988
Subjects
Computer vision
Frequency
Humans
Image segmentation
Random processes
Shape
Spatial resolution
Spectrogram
Surface texture
Taxonomy
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Summary:Clustering (or grouping), defined as the taxonomy of objects (image regions) into categories based on the similarity of their characteristics, is examined. Both in computer and human vision, the use of joint spatial/spatial-frequency (s/sf) representations in this process are suggested. The Wigner and pseudo-Wigner distributions, examples of s/sf representations, are discussed. A comparison is made between the Wigner distribution, the spectrogram, the difference-of-Gaussians representation, and the Gabor representation. Experimental results in the areas of texture segmentation and Gestalt grouping using the Wigner distribution are presented, proving the feasibility of such an approach.< >
ISBN:9780818608780
0818608781
DOI:10.1109/ICPR.1988.28354