A de-texturing and spatially constrained K-means approach for image segmentation-Reference-Cited by-同舟云学术

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A de-texturing and spatially constrained K-means approach for image segmentation

Published:2011-01 Issue:2 Volume:32 Page:359-367
ISSN:0167-8655
Container-title:Pattern Recognition Letters
language:en
Short-container-title:Pattern Recognition Letters

Author:

Mignotte Max

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference20 articles.

1. Signal Processing, Image Processing and Pattern Recognition;Banks,1990

2. Berkhin, P., 2002. Survey of Clustering Data Mining Techniques. Technical Report, Accrue Software, San Jose, CA.

3. Comparison and optimization of methods of color image quantization;Braquelaire;IEEE Trans. Image Process.,1997

4. Mean shift: A robust approach toward feature space analysis;Comaniciu;IEEE Trans. Pattern Anal. Machine Intell.,2002

5. Unsupervised segmentation of color-texture regions in images and video;Deng;IEEE Trans. Pattern Anal. Machine Intell.,2001

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