Automatic tongue image segmentation based on gradient vector flow and region merging

Jifeng Ning, Dapeng Zhang, Chengke Wu, Feng Yue

Research output: Journal article publicationJournal articleAcademic researchpeer-review

42 Citations (Scopus)

Abstract

This paper presents a region merging-based automatic tongue segmentation method. First, gradient vector flow is modified as a scalar diffusion equation to diffuse the tongue image while preserving the edge structures of tongue body. Then the diffused tongue image is segmented into many small regions by using the watershed algorithm. Third, the maximal similarity-based region merging is used to extract the tongue body area under the control of tongue marker. Finally, the snake algorithm is used to refine the region merging result by setting the extracted tongue contour as the initial curve. The proposed method is qualitatively tested on 200 images by traditional Chinese medicine practitioners and quantitatively tested on 50 tongue images using the receiver operating characteristic analysis. Compared with the previous active contour model-based bi-elliptical deformable contour algorithm, the proposed method greatly enhances the segmentation performance, and it could reliably extract the tongue body from different types of tongue images.
Original languageEnglish
Pages (from-to)1819-1826
Number of pages8
JournalNeural Computing and Applications
Volume21
Issue number8
DOIs
Publication statusPublished - 1 Nov 2012

Keywords

  • Gradient vector flow (GVF)
  • Image segmentation
  • Region merging
  • Traditional Chinese tongue diagnosis (TCTD)
  • Watershed

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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