Tongue Texture Analysis Using Gabor Wavelet Opponent Colour Features for Tongue Diagnosis in Traditional Chinese Medicine

Pong C. Yuen; Z. Y. Kuang; W. Wu; Y. T. Wu

doi:10.1142/9789812792495_0013

Tongue Texture Analysis Using Gabor Wavelet Opponent Colour Features for Tongue Diagnosis in Traditional Chinese Medicine

Pong C. Yuen^*, Z. Y. Kuang, W. Wu, Y. T. Wu

^*Corresponding author for this work

Department of Computer Science

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

Abstract

This article reports an application of using Gabor Wavelet Opponent Colour Features (GWOCF) for tongue diagnosis in Traditional Chinese Medicine (TCM). This project focuses on the standardization of the tongue diagnosis in TCM. The objective is to develop a set of quantitative measurement for tongue diagnosis using computer vision techniques. To achieve this goal, we propose to use GWOCF for determining different types of tongue proper and tongue coating textures from a tongue image. Two experiments are presented. In the first experiment, GWOCF is directly extracted from tongue image for recognition. In the second experiment, we employ colour information to pre-classify the known texture image before extracting GWOCF. 63 tongue images captured from 63 patients in Guangzhou University of Traditional Chinese Medicine's hospital are used for testing. It is found that with colour pre-classification process, 89% of recognition accuracy can be achieved. This is a revised version of our conference paper in [12].

Original language	English
Title of host publication	Texture Analysis in Machine Vision
Editors	M. K. Pietikäinen
Place of Publication	Singapore
Publisher	World Scientific Publishing Co. Pte Ltd
Pages	179-188
Number of pages	10
Edition	1st
ISBN (Print)	9810243731, 9789810243739
DOIs	https://doi.org/10.1142/9789812792495_0013
Publication status	Published - Oct 2000
Event	International Workshop on Texture Analysis in Machine Vision 1999 - University of Oulu, Oulu, Finland Duration: 14 Jun 1999 → 15 Jun 1999 https://www.worldscientific.com/worldscibooks/10.1142/4483#t=aboutBook

Publication series

Name	Series in Machine Perception and Artificial Intelligence
Publisher	World Scientific Publishing Co. Pte. Ltd.
Volume	40
ISSN (Print)	1793-0839

Workshop

Workshop	International Workshop on Texture Analysis in Machine Vision 1999
Country/Territory	Finland
City	Oulu
Period	14/06/99 → 15/06/99
Internet address	https://www.worldscientific.com/worldscibooks/10.1142/4483#t=aboutBook

User-Defined Keywords

Tongue diagnosis
Traditional Chinese Medicine
Texture Analysis
Gabor Wavelet opponent colour features

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1142/9789812792495_0013

Cite this

Yuen, P. C., Kuang, Z. Y., Wu, W., & Wu, Y. T. (2000). Tongue Texture Analysis Using Gabor Wavelet Opponent Colour Features for Tongue Diagnosis in Traditional Chinese Medicine. In M. K. Pietikäinen (Ed.), Texture Analysis in Machine Vision (1st ed., pp. 179-188). (Series in Machine Perception and Artificial Intelligence; Vol. 40). World Scientific Publishing Co. Pte Ltd. https://doi.org/10.1142/9789812792495_0013

Yuen, Pong C. ; Kuang, Z. Y. ; Wu, W. et al. / Tongue Texture Analysis Using Gabor Wavelet Opponent Colour Features for Tongue Diagnosis in Traditional Chinese Medicine. Texture Analysis in Machine Vision. editor / M. K. Pietikäinen. 1st. ed. Singapore : World Scientific Publishing Co. Pte Ltd, 2000. pp. 179-188 (Series in Machine Perception and Artificial Intelligence).

@inproceedings{bc9ce94e2d774910bd993ed0c12796d6,

title = "Tongue Texture Analysis Using Gabor Wavelet Opponent Colour Features for Tongue Diagnosis in Traditional Chinese Medicine",

abstract = "This article reports an application of using Gabor Wavelet Opponent Colour Features (GWOCF) for tongue diagnosis in Traditional Chinese Medicine (TCM). This project focuses on the standardization of the tongue diagnosis in TCM. The objective is to develop a set of quantitative measurement for tongue diagnosis using computer vision techniques. To achieve this goal, we propose to use GWOCF for determining different types of tongue proper and tongue coating textures from a tongue image. Two experiments are presented. In the first experiment, GWOCF is directly extracted from tongue image for recognition. In the second experiment, we employ colour information to pre-classify the known texture image before extracting GWOCF. 63 tongue images captured from 63 patients in Guangzhou University of Traditional Chinese Medicine's hospital are used for testing. It is found that with colour pre-classification process, 89% of recognition accuracy can be achieved. This is a revised version of our conference paper in [12].",

keywords = "Tongue diagnosis, Traditional Chinese Medicine, Texture Analysis, Gabor Wavelet opponent colour features",

author = "Yuen, {Pong C.} and Kuang, {Z. Y.} and W. Wu and Wu, {Y. T.}",

note = "Publisher copyright: {\textcopyright} 2000 by World Scientific Publishing Co. Pte. Ltd.; International Workshop on Texture Analysis in Machine Vision 1999 ; Conference date: 14-06-1999 Through 15-06-1999",

year = "2000",

month = oct,

doi = "10.1142/9789812792495_0013",

language = "English",

isbn = "9810243731",

series = "Series in Machine Perception and Artificial Intelligence",

publisher = "World Scientific Publishing Co. Pte Ltd",

pages = "179--188",

editor = "Pietik{\"a}inen, {M. K.}",

booktitle = "Texture Analysis in Machine Vision",

address = "Singapore",

edition = "1st",

url = "https://www.worldscientific.com/worldscibooks/10.1142/4483#t=aboutBook",

}

Yuen, PC, Kuang, ZY, Wu, W & Wu, YT 2000, Tongue Texture Analysis Using Gabor Wavelet Opponent Colour Features for Tongue Diagnosis in Traditional Chinese Medicine. in MK Pietikäinen (ed.), Texture Analysis in Machine Vision. 1st edn, Series in Machine Perception and Artificial Intelligence, vol. 40, World Scientific Publishing Co. Pte Ltd, Singapore, pp. 179-188, International Workshop on Texture Analysis in Machine Vision 1999 , Oulu, Finland, 14/06/99. https://doi.org/10.1142/9789812792495_0013

Tongue Texture Analysis Using Gabor Wavelet Opponent Colour Features for Tongue Diagnosis in Traditional Chinese Medicine. / Yuen, Pong C.; Kuang, Z. Y.; Wu, W. et al.
Texture Analysis in Machine Vision. ed. / M. K. Pietikäinen. 1st. ed. Singapore: World Scientific Publishing Co. Pte Ltd, 2000. p. 179-188 (Series in Machine Perception and Artificial Intelligence; Vol. 40).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

TY - GEN

T1 - Tongue Texture Analysis Using Gabor Wavelet Opponent Colour Features for Tongue Diagnosis in Traditional Chinese Medicine

AU - Yuen, Pong C.

AU - Kuang, Z. Y.

AU - Wu, W.

AU - Wu, Y. T.

PY - 2000/10

Y1 - 2000/10

N2 - This article reports an application of using Gabor Wavelet Opponent Colour Features (GWOCF) for tongue diagnosis in Traditional Chinese Medicine (TCM). This project focuses on the standardization of the tongue diagnosis in TCM. The objective is to develop a set of quantitative measurement for tongue diagnosis using computer vision techniques. To achieve this goal, we propose to use GWOCF for determining different types of tongue proper and tongue coating textures from a tongue image. Two experiments are presented. In the first experiment, GWOCF is directly extracted from tongue image for recognition. In the second experiment, we employ colour information to pre-classify the known texture image before extracting GWOCF. 63 tongue images captured from 63 patients in Guangzhou University of Traditional Chinese Medicine's hospital are used for testing. It is found that with colour pre-classification process, 89% of recognition accuracy can be achieved. This is a revised version of our conference paper in [12].

AB - This article reports an application of using Gabor Wavelet Opponent Colour Features (GWOCF) for tongue diagnosis in Traditional Chinese Medicine (TCM). This project focuses on the standardization of the tongue diagnosis in TCM. The objective is to develop a set of quantitative measurement for tongue diagnosis using computer vision techniques. To achieve this goal, we propose to use GWOCF for determining different types of tongue proper and tongue coating textures from a tongue image. Two experiments are presented. In the first experiment, GWOCF is directly extracted from tongue image for recognition. In the second experiment, we employ colour information to pre-classify the known texture image before extracting GWOCF. 63 tongue images captured from 63 patients in Guangzhou University of Traditional Chinese Medicine's hospital are used for testing. It is found that with colour pre-classification process, 89% of recognition accuracy can be achieved. This is a revised version of our conference paper in [12].

KW - Tongue diagnosis

KW - Traditional Chinese Medicine

KW - Texture Analysis

KW - Gabor Wavelet opponent colour features

UR - https://www.worldscientific.com/worldscibooks/10.1142/4483#t=aboutBook

UR - https://library.hkbu.edu.hk/record/?ID=alma991021725719703409&T=P2P

U2 - 10.1142/9789812792495_0013

DO - 10.1142/9789812792495_0013

M3 - Conference proceeding

SN - 9810243731

SN - 9789810243739

T3 - Series in Machine Perception and Artificial Intelligence

SP - 179

EP - 188

BT - Texture Analysis in Machine Vision

A2 - Pietikäinen, M. K.

PB - World Scientific Publishing Co. Pte Ltd

CY - Singapore

T2 - International Workshop on Texture Analysis in Machine Vision 1999

Y2 - 14 June 1999 through 15 June 1999

ER -

Yuen PC, Kuang ZY, Wu W, Wu YT. Tongue Texture Analysis Using Gabor Wavelet Opponent Colour Features for Tongue Diagnosis in Traditional Chinese Medicine. In Pietikäinen MK, editor, Texture Analysis in Machine Vision. 1st ed. Singapore: World Scientific Publishing Co. Pte Ltd. 2000. p. 179-188. (Series in Machine Perception and Artificial Intelligence). doi: 10.1142/9789812792495_0013

Tongue Texture Analysis Using Gabor Wavelet Opponent Colour Features for Tongue Diagnosis in Traditional Chinese Medicine

Abstract

Publication series

Workshop

User-Defined Keywords

UN SDGs

Access to Document

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Cite this