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Mathematical Problems in Engineering
Volume 2014, Article ID 464875, 13 pages
Research Article

KmsGC: An Unsupervised Color Image Segmentation Algorithm Based on -Means Clustering and Graph Cut

1College of Computer Science, Sichuan University, Chengdu, Sichuan 610065, China
2College of Mathematics and Information Science, Guangxi University, Nanning, Guangxi 530004, China

Received 26 August 2013; Revised 17 March 2014; Accepted 2 April 2014; Published 12 May 2014

Academic Editor: Gerhard-Wilhelm Weber

Copyright © 2014 Binmei Liang and Jianzhou Zhang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [4 citations]

The following is the list of published articles that have cited the current article.

  • Gaurav Gupta, and Alexandra Psarrou, “Adaptive-Threshold Region Merging via Path Scanning,” Proceedings - International Conference on Pattern Recognition, pp. 948–953, 2014. View at Publisher · View at Google Scholar
  • Jose Batz, Mario Méndez-Dorado, and J. Thomasson, “Imaging for High-Throughput Phenotyping in Energy Sorghum,” Journal of Imaging, vol. 2, no. 1, pp. 4, 2016. View at Publisher · View at Google Scholar
  • Shibai Yin, Yiming Qian, and Minglun Gong, “Unsupervised hierarchical image segmentation through fuzzy entropy maximization,” Pattern Recognition, vol. 68, pp. 245–259, 2017. View at Publisher · View at Google Scholar
  • Guangzhu Xu, Xinyu Li, Ke Lv, and Bangjun Lei, “Unsupervised color image segmentation with color-alone feature using region growing pulse coupled neural network,” Neurocomputing, vol. 306, pp. 1–16, 2018. View at Publisher · View at Google Scholar