KmsGC: An Unsupervised Color Image Segmentation Algorithm Based on K-Means Clustering and Graph Cut
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-05-12
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
For unsupervised color image segmentation, we propose a two-stage algorithm, KmsGC, that combines K-means clustering with graph cut.
In the first stage, K-means clustering algorithm is applied to make an initial clustering, and the optimal number of clusters is automatically determined by a compactness criterion that is established to find clustering with maximum intercluster distance and minimum intracluster variance.
In the second stage, a multiple terminal vertices weighted graph is constructed based on an energy function, and the image is segmented according to a minimum cost multiway cut.
A large number of performance evaluations are carried out, and the experimental results indicate the proposed approach is effective compared to other existing image segmentation algorithms on the Berkeley image database.
American Psychological Association (APA)
Liang, Binmei& Zhang, Jianzhou. 2014. KmsGC: An Unsupervised Color Image Segmentation Algorithm Based on K-Means Clustering and Graph Cut. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-13.
https://search.emarefa.net/detail/BIM-1044284
Modern Language Association (MLA)
Liang, Binmei& Zhang, Jianzhou. KmsGC: An Unsupervised Color Image Segmentation Algorithm Based on K-Means Clustering and Graph Cut. Mathematical Problems in Engineering No. 2014 (2014), pp.1-13.
https://search.emarefa.net/detail/BIM-1044284
American Medical Association (AMA)
Liang, Binmei& Zhang, Jianzhou. KmsGC: An Unsupervised Color Image Segmentation Algorithm Based on K-Means Clustering and Graph Cut. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-13.
https://search.emarefa.net/detail/BIM-1044284
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1044284