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  • 标题:AN ACCELERATED K-MEANS CLUSTERING ALGORITHM FOR IMAGE SEGMENTATION
  • 本地全文:下载
  • 作者:SEYED MOJTABA TAFAGHOD SADAT ZADEH ; ALIREZA MEHRSINA ; MINA BASIRAT
  • 期刊名称:Journal of Theoretical and Applied Information Technology
  • 印刷版ISSN:1992-8645
  • 电子版ISSN:1817-3195
  • 出版年度:2013
  • 卷号:48
  • 期号:3
  • 出版社:Journal of Theoretical and Applied
  • 摘要:

    This paper proposes a new enhancement and efficient approach for diminution of iterations in K-Means algorithm. Also a quantized color and gray scale histograms are used for HSV color environments to reduce the process of image segmentation. As an apposed to traditional K-Means technique, in the suggested approach the initial centroids are automatically designated by an effective set of relations. Thus, pixel clustering process is only necessary to be done once after discovering all the centroids. Experimental results show that the new enhanced proposed approach gives better outcome in terms of speed and the results got from this research is closer to human visual perception from the colors.

  • 关键词:Color Image Segmentation; K-Means; Quantization; Image Processing; HSV Color Space
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