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

Content Provider	Springer Nature Link
Author	Ning, Jifeng Zhang, David Wu, Chengke Yue, Feng
Copyright Year	2010
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.
Starting Page	1819
Ending Page	1826
Page Count	8
File Format	PDF
ISSN	09410643
Journal	Neural Computing and Applications
Volume Number	21
Issue Number	8
e-ISSN	14333058
Language	English
Publisher	Springer-Verlag
Publisher Date	2010-12-23
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Image segmentation Gradient vector flow (GVF) Watershed Region merging Traditional Chinese tongue diagnosis (TCTD) Computational Biology/Bioinformatics Computational Science and Engineering Image Processing and Computer Vision Artificial Intelligence (incl. Robotics) Data Mining and Knowledge Discovery Probability and Statistics in Computer Science
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Histogram-based automatic segmentation of images

Principal pixel analysis and SVM for automatic image segmentation

Relevance vector machines approach for long-term flow prediction

Constructing support vector machine ensemble with segmentation for imbalanced datasets

Adaptive k-means clustering algorithm for MR breast image segmentation

Nonstationary regression with support vector machines

Recognizing handwritten Chinese day and month words by combining a holistic method and a segmentation-based method

Distance metric-based time-efficient fuzzy algorithm for abnormal magnetic resonance brain image segmentation

Robust t-distribution mixture modeling via spatially directional information

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

Similar Documents

Histogram-based automatic segmentation of images

Principal pixel analysis and SVM for automatic image segmentation

Relevance vector machines approach for long-term flow prediction

Constructing support vector machine ensemble with segmentation for imbalanced datasets

Adaptive k-means clustering algorithm for MR breast image segmentation

Nonstationary regression with support vector machines

Recognizing handwritten Chinese day and month words by combining a holistic method and a segmentation-based method

Distance metric-based time-efficient fuzzy algorithm for abnormal magnetic resonance brain image segmentation

Robust t-distribution mixture modeling via spatially directional information

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