Responsive image
博碩士論文 etd-0706110-012818 詳細資訊
Title page for etd-0706110-012818
論文名稱
Title
自動化舌部特徵擷取
Automatic Tongue Feature Extraction
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
100
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2010-06-14
繳交日期
Date of Submission
2010-07-06
關鍵字
Keywords
舌正面影像、自動化舌診系統、舌診
tongue inspection, tongue diagnosis, tongue image
統計
Statistics
本論文已被瀏覽 5680 次,被下載 0
The thesis/dissertation has been browsed 5680 times, has been downloaded 0 times.
中文摘要
近年來中醫在西方醫學界中引發一波新潮流,而中醫乃是以望聞問切四診對病人進行診斷,望診又居四診之首,其中舌診乃中醫望診中重要之項目,舌診之結果乃根據醫師對舌頭特徵加以判讀而來,而舌頭特徵觀察重點為舌形、舌質和舌苔所構成之舌象。舌形病理計有中、胖、瘦及歪斜等;舌質病理中,舌色包括淡白、偏淡、淡紅、偏紅、紅、絳、黯及瘀斑、裂紋、齒痕及朱點等特徵;舌苔病理可區分為白、黃、黑、膩、厚、薄、剝或無等。臨床上中醫師多依個人知識與經驗,透過眼睛觀察特徵而推斷病人身體主要病症,診斷結果易囿於知識、經驗、思維模式、診斷技巧、對顏色感知及詮釋等主觀判定影響,不同醫生對同一舌象可能做出互異判斷,重複性不佳。因此藉由科學方法輔助醫生進行診斷,循標準化判別程序,獲得可靠斷症結果,以提高中醫臨床應用價值。藉由電腦判讀達到客觀化及定量化之目標,故中醫舌診電腦化研究是必然發展趨勢。
自動化舌診系統乃是先分離舌頭部位,再擷取舌面上之特徵,如津液、裂紋、瘀斑、齒痕、朱點、舌苔及舌質、舌苔厚薄度與腐膩度、舌色等。流程如下:首先須由患者嘴部擷取舌正面影像作為輸入影像,經由亮度與色彩校正分別補償亮度、色彩偏移得到校正後之影像;接著,自校正後影像擷取舌部區域,本論文經由分析舌頭、嘴唇及皮膚部位之RGB色彩分量表現,轉換為易於人眼認知之HSI色彩空間,經由移除皮膚、矩形檢測、牙齒區域與黑色區域檢測、控制點偵測後,使用主動輪廓技術擷取舌面輪廓。分離舌頭部位後,根據RGB色彩分量變化,色調、飽和度及亮度等特性,藉由拉開對比、臨界值法及連通影像元件檢測舌部相關特徵,如津液、裂紋、瘀斑、齒痕、朱點、舌苔及舌質、舌苔厚薄度與腐膩度等,最後進行特徵分析,量化特徵之數目、面積或長度,並統計特徵分析結果產生舌診報告表,提供中醫師作為臨床上診斷之參考。
Abstract
In recent years, Chinese medicine in the medical profession in the West triggered a wave of new wave. Chinese medicine is based on four examinations which are listening and smelling examination, inquiry, and palpation to diagnose the patient. Tongue diagnosis is also the first of four diagnostic. The result of tongue diagnosis is based on features of tongue which are diagnosed by doctor. Observation of the tongue focuses on the tongue phenomenon which is structured by the shape of the tongue, and the substance of the tongue, and the coating of the tongue. Pathology of the tongue-shaped includes the medium, fat, lean and crooked, etc. In Pathology of the tongue-substanced, tongue color includes pale, closed to pale, reddish, red, dark red, dark purple, also have some features about ecchymosis, breaken line, tooth mark, and red dot. Pathology for the coating of the tongue includes white, yellow, black, greasy, thick, thin, peeling, or no, etc. Clinically, doctors mostly rely on their own knowledge and experience when determining major lesions of a patient by observing the coloration, overall modalities, and volume of salivary on different parts of the tongue. As a result, the diagnosis tends to be limited by knowledge, experience, train of thought, and diagnostic techniques.The subjective determination is likely to be affected by the doctor’s color sensitivity and interpretation.Different doctors may come to drastically different judgments on the same tongue presentation with little overlap. Therefore, it is important to develop scientific methods that can help doctors diagnose based on standardized differentiation procedures and render reliable diagnoses in order to enhance the clinical application value of Chinese Medicine.The computerized automatic capture of characteristics shown on the images of the surface.At first, the captured image achieves brightness and color correction by brightness calibration and color calibration. Then, the original tongue images go through HSI color space conversion, detection of the control points inside and outside the surface of the tongue, curve smoothness modification and active contour model to capture images of the tongue. After that, the tongue shape, tongue fur, tongue body, and body fluid are captured from the image of the tongue.
目次 Table of Contents
摘要.................................................................................i
目錄................................................................................v
圖目錄..........................................................................vii
表目錄...........................................................................xi
第一章 簡介...................................................................1
1.1中醫舌診................................................................2
1.1.1舌診辨證.......................................................... 3
1.1.2舌診特徵.......................................................... 7
1.2相關研究................................................................9
1.2.1基於HSI色調偵測.................... ........................9
1.2.2基於極座標轉換.............................................12
1.2.3利用彩色型態學參數輔助舌苔性狀辨識.....15
1.3研究總述..............................................................20
第二章 理論基礎.........................................................22
2.1 Snake模型..........................................................22
2.1.1原始Snake模型..............................................22
2.1.2 Greedy Snake模型.......................................27
2.2影像色彩校正.......................................................32
第三章 研究方法..........................................................38
3.1取像環境...............................................................38
3.2擷取流程...............................................................40
3.3亮度校正...............................................................41
3.4色彩校正...............................................................43
3.5移除皮膚區域.......................................................46
3.6矩形檢測...............................................................48
3.7牙齒與黑色區域檢測.................... ......................49
3.8控制點偵測.......................................................... 51
3.9主動性輪廓修正曲線.................... .......................53
3.10舌面擷取.............................................................55
3.11特徵擷取.............................................................55
3.11.1舌面津液........................................................55
3.11.2舌苔與舌質分離............................................57
3.11.3舌苔之厚薄度................................................59
3.11.4舌苔之腐膩度................................................60
3.11.5舌面裂紋........................................................61
3.11.6舌面瘀斑........................................................62
3.11.7舌面齒痕........... .............................................62
3.11.8舌面朱點........... .............................................63
3.11.9舌色................... .............................................64
第四章 實驗結果...........................................................66
第五章 結論與未來展望...............................................78
5.1結論........................................................................78
5.2未來展望................................................................78
參考文獻.......................... .............................................81
附錄.................................. .............................................83
A 舌診總報告................. .............................................83
參考文獻 References
[1] 李乃民等:中國舌診大全,學苑出版社,北京,1995:1-525。
[2] 王季藜等:舌診源鑑,立得出版社,台北 1993:2-15。
[3] 洪禎徽:舌診,立得出版社,台北,1996。
[4] 黃帝內經章句索引。啟業書局,台北,1987 :7~459。
[5] 三原陳素中:最新實用溫病學。國際書局,台中,1987:17-24。
[6] 尚瑞梅:舌體大小的臨床意義與客觀化計量化研究。浙江中醫雜誌 1993;(11):518。
[7] 狄群英等:600例纖維胃鏡與舌象的對照觀察。雲南中醫雜誌 1986;1:1-2。
[8] 趙榮菜等:舌質舌苔的計算機定量描述和分類。中醫雜誌 1989;2:47。
[9] 張永賢、邱創乾:以色彩學探討中醫舌象之研究。第六十六屆國醫節中醫學術研討會 1996;三月:2。
[10] 宋汝濬APSC著:攝影學,藝術圖書公司,台北 1993:10-11,65-69。
[11] 林傑人編著:實用攝影,渤海堂文化事業有限公司,台北 1993:106-123,265-272。
[12] Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing, Addison-Wesley Publishing Company, USA, 1992.
[13] William K. Pratt, Digital Image Processing, Second Edition, A Wiley-Interscience Publication, USA, 1991.
[14] Anil K. Jain, Fundamentals of Digital Image Processing, Prentice-Hall International, Inc., USA, 1989.
[15] Kenneth R. Castleman, Digital Image Processing, Prentice-Hall International, Inc., USA, 1996.
[16] George J. Klir and Tina A. Folger, Fuzzy Sets, Uncertainty, and Information, New Jersey, 1988.
[17] Shinichi Tamura, Seihaku Higuchi, and Kokichi Tanaka, “Pattern Classification Based on Fuzzy Relations,” IEEE Transactions on Systems, Man, and Cybernetics, vol. SMC-1, no. 1, pp. 61-66, Jan. 1971.
[18] L. A. Zadeh, “Fuzzy algorithms,” Inform. Contr., vol. 12, pp. 99-102, Feb. 1968.
[19] L. A. Zadeh, “Fuzzy sets and systems,” Proc. 1965 Symp. On Syst. Theory, pp. 29-39, 1965.
[20] 菅野道夫原著,楊英魁編譯:Fuzzy控制,全華科技圖書出版,台北 1993:1-66。
[21] Bart Kosko原著,林基興編譯:模糊思考,全華科技圖書出版,台北 1995:121-154。
[22] L. A. Zadeh, “Fuzzy sets,” Inform. Contr., vol. 8, pp. 338-353, June 1965.
[23] R. Bellman, R. Kalaba, and L. Zadeh, “Abstraction and pattern classification,” J. Math. Anal. Appl., vol. 13, pp. 1-7, Jan. 1966.
[24] Krzysztof J. Cios, Inho Shin and Lucy S. Goodenday, “Using Fuzzy Sets to Diagnose Coronary Artery Stenosis,” IEEE Computer, pp. 57-63, Mar. 1991.
[25] Zhao Zhong-xu, Wang Ai-min, Shen Lan-sun. “The Color Tongue Image Segmentation Based on Mathematical Morphology and HIS Model,” Journal of Beijing Industry University, vol. 25, no. 2, pp. 67-71, 1999.
[26] Du Jian-qiang, Lu Yan-sheng, Zhu Ming-feng, Zhang Kang and Ding Cheng-hua, “A Novel Algorithm of Color Tongue Image Segmentation Based on HSI,” BMEI 2008. International Conf. on BioMedical Engineering and Informatics, pp.733-737, vol. 1, 27-30, May 2008.
[27] Soo-Chang Pei. Image sampling structure conversion by morphological filters, Signal Processing: Image Communication, pp. 13-24, 1994.
[28] Wangmeng Zuo, Kuanquan Wang, Zhang D. and Hongshi Zhang, “Combination of polar edge detection and active contour model for automated tongue segmentation,” The 3rd International Conf. on Image and Graphics, pp.270-273, 18-20 Dec. 2004.
[29] A.A. Amini, T.E. Weymouth, R.C. Jain, “Using Dynamic Programming for solving variational problems in vision,” IEEE Trans. PAMI, vol. 12, no. 9, pp. 855-867, 1990.
[30] 王嘉麒。2007。利用色彩型態學參數輔助舌苔性狀辨識。碩士論文。台中:逢甲大學自動控制工程學研究所。
[31] Wang Aimin, Shen Lansun and Zhao Zhongxu, “Color Tongue Image Segmentation using fuzzy Kohonen networks and genetic algorithm,” Proceedings of SPIE, pp.182-190, 2000.
[32] 王永剛、王愛民、沈蘭蓀:舌象分析儀中舌色重現方法的研究,照明工程學報,2001,12(2):4-10。
[33] M. Kass, A. Witkin, and D. Terzopoulos, “Snakes: Active contour models,” IEEE Trans. IJCV, vol. 1, pp. 321-331, 1987.
[34] Williams, D. J. and Shah, M. “A Fast Algorithm for Active Contours,” Proc. 3rd Inter. Conf. on Computer Vision, pp. 592-595, 4-7 Dec. 1990.
[35] Po Pang, Zhang D. and Kuanquan Wang, “The Bi-elliptical Deformable Contour and its Application to Automated Tongue Segmentation in Chinese Medicine,” IEEE Trans. Medical Imaging, vol. 24, no. 8, pp. 946-956, 2005.
[36] Roullot, E. “A Unifying Framework for Color Image Calibration,” 15th Inter. Conf. on Systems, Signals and Image Proc. IWSSIP., pp. 97-100, Dec 2008.
電子全文 Fulltext
本電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。
論文使用權限 Thesis access permission:校內校外均不公開 not available
開放時間 Available:
校內 Campus:永不公開 not available
校外 Off-campus:永不公開 not available

您的 IP(校外) 位址是 54.89.70.161
論文開放下載的時間是 校外不公開

Your IP address is 54.89.70.161
This thesis will be available to you on Indicate off-campus access is not available.

紙本論文 Printed copies
紙本論文的公開資訊在102學年度以後相對較為完整。如果需要查詢101學年度以前的紙本論文公開資訊,請聯繫圖資處紙本論文服務櫃台。如有不便之處敬請見諒。
開放時間 available 已公開 available

QR Code