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.
Original language | English |
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Journal | Eurasip Journal on Advances in Signal Processing |
DOIs | |
Publication status | Published - 26 Dec 2013 |
Keywords
- Image segmentation
- Tongue diagnosis
- Fast marching
- 2D Gabor filter
- Active contour model
ASJC Scopus subject areas
- Hardware and Architecture
- Signal Processing
- Electrical and Electronic Engineering