北京生物醫(yī)學(xué)工程

一種基于活動形狀模型算法的耳郭穴區(qū)定位方法

A location method of auricular point area based on active shape model algorithm

作者：王逸卉江淼黃娜溫軍玲

單位：上海中醫(yī)藥大學(xué)針灸推拿學(xué)院（上海201203）

關(guān)鍵詞：中醫(yī)；耳穴療法；耳穴分區(qū)；圖像處理；活動形狀模型

分類號：R318

出版年·卷·期（頁碼）：2021·40·2（145-150）

摘要：

目的耳穴療法是中醫(yī)的重要組成部分，而耳穴定位是治療的前提。由于耳郭面積較小、耳穴眾多導(dǎo)致自動尋穴十分麻煩，本文提出一種基于圖像處理技術(shù)的耳郭穴區(qū)定位方法。方法通過對來自于USTB人耳圖像庫和自行采集圖像共30幅構(gòu)建訓(xùn)練集，在最新耳穴國家標(biāo)準(zhǔn)GB/T13734-2008的基礎(chǔ)上，選取包含耳郭邊緣點、曲率極大值點、等分點等在內(nèi)的65個特征點構(gòu)建點分布模型（point distribution model, PDM），采用基于活動形狀模型(active shape model, ASM)的圖像處理方法，對待測人耳圖像進行搜索匹配后，通過分別連接構(gòu)成耳郭穴區(qū)的特征點，實現(xiàn)對人耳圖像的穴區(qū)定位。最后通過計算定位后與人工標(biāo)定的特征點之間的歐幾里得距離，對定位的精度進行評估。結(jié)果該方法能初步實現(xiàn)耳郭的穴區(qū)定位，歐幾里得平均距離為6.246±0.429；結(jié)論基于活動形狀模型的耳郭穴區(qū)定位方法能初步實現(xiàn)人耳圖像的穴區(qū)定位，有利于耳穴療法的穴區(qū)定位、耳穴自動化儀器的開發(fā)和中醫(yī)耳穴示教等

Objective Auricular therapy is an important part of traditional Chinese medicine, and the location of auricular point is the premise of treatment. But it is hard to locate the auricular points automatically because of too small auricular area and too many auricle points. This paper proposes a location method of auricular point area based on image processing technology. Methods A training set of 30 human ear images from the Human Ear Recognition Laboratory of University of Science and Technology Beijing was constructed. Then integrated with the latest national standard of auricular points (GB /T13734-2008), 65 feature points including auricle edge point, curvature maximum point and bisection point were selected for each image to establish a point distribution model (PDM). Next an image processing method based on active shape model (ASM) was used to search the object ear image. And then through connecting the feature points of each auricular point area, the location of ear image was realized. Finally, the accuracy was evaluated by using Euclidean distance evaluation index between the location results of auricular points and the location of artificial landmarks. Results Our method can realize the location of auricular point areas. The average Euclidean distance value is 6.246 ± 0.429. Conclusions The auricular points location method based on active shape model can realize the location of auricular point area, which is benefit to the development of automatic instrument for auricular therapy and can help the teaching of the related ear points of traditional Chinese medicine.

參考文獻：

[1] 程爵棠. 耳穴療法治百病[M]. 4版. 鄭州：河南科學(xué)技術(shù)出版社, 2017：1-7.

[2] 劉繼洪,許藝燕,徐光鎮(zhèn),等.耳穴醫(yī)療是中西醫(yī)結(jié)合的一座“橋梁”[J].中國中西醫(yī)結(jié)合雜志,2019,39(6):750-752.

Liu JH, Xu YY, Xu GZ, et al. Auricular medicine is the "bridge" of the integrated traditional Chinese medicine and western medicine[J]. Chinese Journal of Integrated Traditional and Western Medicine, 2019, 39(6): 750-752.

[3] 陳盼碧,楊孝芳,王興桂,等.圖示教學(xué)法在耳針法耳穴定位教學(xué)中的運用[J].亞太傳統(tǒng)醫(yī)藥, 2019,15(6): 214-215.

[4] Yang YT, Huang QF, Jia YF, et al. Current situation and analysis of clinical application of auricular acupoint sticking therapy[J]. Journal of Acupuncture and Tuina Science, 2016,14(2):141-148.

[5] 中華人民共和國國家質(zhì)量監(jiān)督檢驗檢疫總局.GB/T 13734—2008耳穴名稱與定位[S].北京:中國標(biāo)準(zhǔn)出版社, 2008.

[6] 李一波,黃增喜,張海軍,等.一種基于改進GVF Snake的自動人耳檢測方法[J].模式識別與人工智能, 2010, 23(4): 552-559.

Li YB, Huang ZX, Zhang HJ, et al. An automatic ear detection method based on improved GVF Snake[J]. Pattern Recognition and Artificial Intelligence, 2010, 23(4): 552-559.

[7] 李素娟,封筠,牛江川.人耳識別中歸一化對特征提取和識別影響的研究[J].電腦知識與技術(shù),2008,4(36):2984-2985.

Li SJ, Feng J, Niu JC. The research of the impact of normalization for feature extraction and recognition on ear biomitrice recognition[J].Computer Knowledge and Technology,2008,4(36): 2984-2985.

[8] 高淑欣,穆志純.人耳識別中的圖像歸一化研究[J].控制工程,2008,15(1):18-21.

Gao SX, Mu ZC. On image normalization in ear recognition[J]. Control Engineering of China, 2008,15(1): 18-21.

[9] 楊陽.基于ASM算法的肺部輪廓提取研究[D].沈陽：東北大學(xué), 2015.

Yang Y. A study on ASM-based lung edge extraction[D]. Shenyang: Northeastern University, 2015.

[10] 黃飛,尤啟房,楊晉吉. ASM的手骨提取方法研究[J].計算機工程與應(yīng)用,2016,52(3):164-168,219.

Huang F,You QF,Yang JJ. Hand bone extraction method research based on ASM[J]. Computer Engineering and Applications, 2016,52(3):164-168,219.

[11] 常夢龍.基于特征點定位算法的面部穴位定位方法的研究[D]. 北京:北京工業(yè)大學(xué), 2017.

Chang ML. Research on facial acupuncture point positioning method based on feature point location algorithm[D]. Beijing: Beijing University of Technology, 2017.

[12] 易佳,王碧琳,劉姝秀,等.結(jié)合ASM算法和邊緣檢測的人臉定位方法研究[J].信息系統(tǒng)工程, 2015(12):125-127.

[13] Cootes TF, Taylor CJ, Cooper DH, et al. Active shape models-their training and application[J]. Computer Vision and Image Understanding, 1995,61(1): 38-59.

[14] 張學(xué).視頻中多姿態(tài)人臉的特征點定位研究[D].天津：河北工業(yè)大學(xué),2015.

Zhang X. Research on feature points location of multi-pose face in video[D].Tianjin: Hebei University of Technology, 2015.

[15] 劉騰龍.視頻人臉替換中目標(biāo)分割算法的研究[D].天津：河北工業(yè)大學(xué), 2018.

Liu TL.Research on target segmentation algorithm in video face replacement[D]. Tianjin: Hebei University of Technology, 2018.

服務(wù)與反饋：

【文章下載】【加入收藏】

提示：您還未登錄，請登錄！點此登錄

51黑料吃瓜在线观看,51黑料官网|51黑料捷克街头搭讪_51黑料入口最新视频