Color Image Segmentation Based on Mean Shift and Normalized Cuts

In this correspondence, we develop a novel approach that provides effective and robust segmentation of color images. By incorporating the advantages of the mean shift (MS) segmentation and the normalized cut (Ncut) partitioning methods, the proposed method requires low computational complexity and i...

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Veröffentlicht in:	IEEE transactions on cybernetics 2007-10, Vol.37 (5), p.1382-1389
Hauptverfasser:	Tao, Wenbing, Jin, Hai, Zhang, Yimin
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial Intelligence Clustering Clustering algorithms Color Color image segmentation Colorimetry - methods Computational complexity graph partitioning Graphs Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image segmentation Layout mean shift (MS) Noise reduction normalized cut (Ncut) Optimization methods Partitioning Partitioning algorithms Pattern Recognition, Automated - methods Pixel Pixels Reproducibility of Results Robustness Segmentation Sensitivity and Specificity Studies
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