Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/7626
Title: Fast marching over the 2D Gabor magnitude domain for tongue body segmentation
Authors: Cui, Z
Zhang, H
Zhang, DD 
Li, N
Zuo, W
Keywords: Image segmentation
Tongue diagnosis
Fast marching
2D Gabor filter
Active contour model
Issue Date: 26-Dec-2013
Publisher: Springer
Source: EURASIP Journal on advances in signal processing, 26 Dec. 2013, v. 2013:190, p. 1-13 How to cite?
Journal: EURASIP journal on advances in signal processing 
Abstract: Tongue body segmentation is a prerequisite to tongue image analysis and has recently received considerable attention. The existing tongue body segmentation methods usually involve two key steps: edge detection and active contour model (ACM)-based segmentation. However, conventional edge detectors cannot faithfully detect the contour of the tongue body, and the initialization of ACM suffers from the edge discontinuity problem. To address these issues, we proposed a novel tongue body segmentation method, GaborFM, which initializes ACM by performing fast marching over the two-dimensional (2D) Gabor magnitude domain of the tongue images. For the enhancement of the contour of the tongue body, we used the 2D Gabor magnitude-based detector. To cope with the edge discontinuity problem, the fast marching method was utilized to connect the discontinuous contour segments, resulting in a closed and continuous tongue body contour for subsequent ACM-based segmentation. Qualitative and quantitative results showed that GaborFM is superior to the other methods for tongue body segmentation.
URI: http://hdl.handle.net/10397/7626
ISSN: 1687-6172
EISSN: 1687-6180
DOI: 10.1186/1687-6180-2013-190
Rights: © 2013 Cui et al.; licensee Springer. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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