Tongue body segmentation is a prerequisite to tongue image analysis and has recently received considerable\r\nattention. The existing tongue body segmentation methods usually involve two key steps: edge detection and\r\nactive contour model (ACM)-based segmentation. However, conventional edge detectors cannot faithfully detect\r\nthe contour of the tongue body, and the initialization of ACM suffers from the edge discontinuity problem. To\r\naddress these issues, we proposed a novel tongue body segmentation method, GaborFM, which initializes ACM by\r\nperforming fast marching over the two-dimensional (2D) Gabor magnitude domain of the tongue images. For the\r\nenhancement of the contour of the tongue body, we used the 2D Gabor magnitude-based detector. To cope with\r\nthe edge discontinuity problem, the fast marching method was utilized to connect the discontinuous contour\r\nsegments, resulting in a closed and continuous tongue body contour for subsequent ACM-based segmentation.\r\nQualitative and quantitative results showed that GaborFM is superior to the other methods for tongue body\r\nsegmentation.
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