A top-down region dividing approach for image segmentation

Yi Ta Wu, Frank Y. Shih, Jiazheng Shi, Yih Tyng Wu

Research output: Contribution to journalArticlepeer-review

32 Scopus citations


Histogram-based and region-based segmentation approaches have been widely used in image segmentation. Difficulties arise when we use these techniques, such as the selection of a proper threshold value for the histogram-based technique and the over-segmentation followed by the time-consuming merge processing for the region-based technique. To provide efficient algorithms that not only produce better segmentation results but also maintain low computational complexity, a novel top-down region dividing based approach is developed for image segmentation, which combines the advantages of both histogram-based and region-based approaches. Experimental results show that our algorithm can efficiently perform image segmentation without distorting the spatial structure of an image. Furthermore, two potential applications in medical image analysis are presented to show the advantages of using the proposed algorithm.

Original languageEnglish (US)
Pages (from-to)1948-1960
Number of pages13
JournalPattern Recognition
Issue number6
StatePublished - Jun 2008

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence


  • Feature-based segmentation
  • Image segmentation
  • Medical image analysis
  • Spatial-based segmentation
  • Watershed


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