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DENG Xiao-zheng, JIAO Li-cheng. Automatic Immune Clonal Clustering Method Using Manifold Distance for Image Segmentation[J]. Journal of University of Electronic Science and Technology of China, 2014, 43(5): 742-748. doi: 10.3969/j.issn.1001-0548.2014.05.019
Citation: DENG Xiao-zheng, JIAO Li-cheng. Automatic Immune Clonal Clustering Method Using Manifold Distance for Image Segmentation[J]. Journal of University of Electronic Science and Technology of China, 2014, 43(5): 742-748. doi: 10.3969/j.issn.1001-0548.2014.05.019
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Automatic Immune Clonal Clustering Method Using Manifold Distance for Image Segmentation

doi: 10.3969/j.issn.1001-0548.2014.05.019
  • 1.

    Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China,Xidian University Xi'an 710071

  • Received Date: 2014-01-03
  • Rev Recd Date: 2014-07-08
  • Publish Date: 2014-10-15
  • There are several difficulties in using a partitional clustering algorithm to deal with image segmentation problem including choosing the correct number of clusters without any prior knowledge, measuring the image datasets with complicated manifold structures and reducing the computation time. In this paper, an automatic immune clonal clustering method using manifold distance is applied to image segmentation. This method can automatically determine the number of clusters, measure the complicated manifold dataset by using manifold distance, and less computation time by using super-pixels instead of pixels. Experimental results on four artificial data sets and four Berkeley images show that the novel method outperforms the k-means algorithm and the GCUK algorithm.
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    沈阳化工大学材料科学与工程学院 沈阳 110142

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Automatic Immune Clonal Clustering Method Using Manifold Distance for Image Segmentation

doi: 10.3969/j.issn.1001-0548.2014.05.019
  • 1. Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China,Xidian University Xi'an 710071
  • Received Date: 2014-01-03
  • Rev Recd Date: 2014-07-08
  • Publish Date: 2014-10-15

Abstract: There are several difficulties in using a partitional clustering algorithm to deal with image segmentation problem including choosing the correct number of clusters without any prior knowledge, measuring the image datasets with complicated manifold structures and reducing the computation time. In this paper, an automatic immune clonal clustering method using manifold distance is applied to image segmentation. This method can automatically determine the number of clusters, measure the complicated manifold dataset by using manifold distance, and less computation time by using super-pixels instead of pixels. Experimental results on four artificial data sets and four Berkeley images show that the novel method outperforms the k-means algorithm and the GCUK algorithm.

DENG Xiao-zheng, JIAO Li-cheng. Automatic Immune Clonal Clustering Method Using Manifold Distance for Image Segmentation[J]. Journal of University of Electronic Science and Technology of China, 2014, 43(5): 742-748. doi: 10.3969/j.issn.1001-0548.2014.05.019
Citation: DENG Xiao-zheng, JIAO Li-cheng. Automatic Immune Clonal Clustering Method Using Manifold Distance for Image Segmentation[J]. Journal of University of Electronic Science and Technology of China, 2014, 43(5): 742-748. doi: 10.3969/j.issn.1001-0548.2014.05.019
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