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Cited by 987

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Mean shift analysis and applications

Comaniciu, D., Meer, P.·1999·Proceedings of the Seventh IEEE International Conference on Computer Vision

Abstract

A nonparametric estimator of density gradient, the mean shift, is employed in the joint, spatial-range (value) domain of gray level and color images for discontinuity preserving filtering and image segmentation. Properties of the mean shift are reviewed and its convergence on lattices is proven. The proposed filtering method associates with each pixel in the image the closest local mode in the density distribution of the joint domain. Segmentation into a piecewise constant structure requires only one more step, fusion of the regions associated with nearby modes. The proposed technique has two parameters controlling the resolution in the spatial and range domains. Since convergence is guaranteed, the technique does not require the intervention of the user to stop the filtering at the desired image quality. Several examples, for gray and color images, show the versatility of the method and compare favorably with results described in the literature for the same images.

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Crossref · 10.1109/iccv.1999.790416

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Metadata

Authors
Comaniciu, D., & Meer, P.
Venue
Proceedings of the Seventh IEEE International Conference on Computer Vision
Publisher
IEEE
Published
1999
Pages
1197-1203 vol.2
OpenAlex
W1964443764
Cited by
987
References
1
FWCI
16.41
Type
conference paper
Language
en
Open access
closed

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