基于內(nèi)容和時(shí)空特征的面癱程度定量評(píng)價(jià)的鑒別研究
[Abstract]:Facial paralysis (facial paralysis) is a common clinical disease, according to statistics every 100000 people with 20 to 25 patients. The disease is usually caused by nerve damage, which can lead to severe sequelae if not properly treated at an early stage. If there is an effective method to evaluate the degree of facial paralysis objectively and quantitatively, it is very helpful for the treatment. In response to this demand, this paper uses facial expression data to extract more accurate feature information, and provides guidance for doctors to identify the degree of facial paralysis more objectively. The main research results are as follows: (1) aiming at the traditional research methods to locate the static image, Illumination, shadow and itself cause asymmetry. On the one hand, based on image content, a method based on LBP and Gabor filter is proposed to extract asymmetric features and motion features by (LBP Gabor). The advantages of LBP rotation invariance and gray invariance are used to remove the illumination effect, and the Gabor filter is used to reduce the noise and redundant information in the image processed by LBP. On the other hand, aiming at the nonuniformity of passband in Gabor filter, the feature extraction based on CMF (Concentric Modulation Filter) method is proposed, and LBP and CMF are combined with (LBP CMF). Because the passband of CMF is the same in all directions, it can extract more accurate features. The experimental results show that the LBP Gabor and LBP CMF methods are more effective and practical than the traditional methods. (2) the accuracy of feature extraction is affected by the uncorrelated regions in the still images (such as teeth in the mouth, shadows and nevus in the corners of the mouth). In order to solve these problems, based on the feature information of facial data, a target tracking method is proposed to extract temporal and spatial features for the first time. The method firstly selects Marker from the first frame of facial image, and then tracks the marker to extract temporal and spatial features in the image sequence. In this paper, two tracking methods, KLT and Mean-Shift, are used to prove the effectiveness of extracting spatio-temporal features for discriminating. (3) aiming at the asynchronous performance of different patient's facial expressions, this paper synchronizes and normalizes the start and end points of facial expressions. The experiments of multi-class data show that compared with content-based methods, the accuracy of temporal and spatial feature extraction, synchronization and normalization is higher than that of content-based method, and it is more practical for doctors. At the same time, the proposed method extends the application field of target tracking method and provides a new idea for quantitative evaluation of facial paralysis degree. The conclusion of the experiment is helpful for doctors to make reasonable judgment and treatment of the patient's condition.
【學(xué)位授予單位】:中南林業(yè)科技大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2017
【分類號(hào)】:R745.12;TN713
【相似文獻(xiàn)】
相關(guān)會(huì)議論文 前5條
1 尹軍;;世界優(yōu)秀田徑速度項(xiàng)群技術(shù)動(dòng)作結(jié)構(gòu)與時(shí)空特征的研究[A];第4屆全國(guó)青年體育科學(xué)學(xué)術(shù)會(huì)議論文摘要匯編[C];2005年
2 胡宇娜;曹艷英;;女性日常休閑時(shí)空特征研究——以青島市為例[A];第十五屆全國(guó)區(qū)域旅游學(xué)術(shù)開(kāi)發(fā)研討會(huì)暨度假旅游論壇論文冊(cè)[C];2010年
3 謝五三;田紅;;氣候變暖背景下安徽省干旱時(shí)空特征分析[A];第27屆中國(guó)氣象學(xué)會(huì)年會(huì)副熱帶季風(fēng)與氣候變化分會(huì)場(chǎng)論文集[C];2010年
4 劉曉冉;李國(guó)平;范廣洲;李洪權(quán);;我國(guó)西南地區(qū)近40年降水異常的時(shí)空特征[A];中國(guó)氣象學(xué)會(huì)2006年年會(huì)“首屆研究生年會(huì)”分會(huì)場(chǎng)論文集[C];2006年
5 閆慧敏;劉紀(jì)遠(yuǎn);曹明奎;;基于遙感模型的近20年來(lái)中國(guó)農(nóng)田生產(chǎn)力變化時(shí)空特征研究[A];生態(tài)學(xué)與全面·協(xié)調(diào)·可持續(xù)發(fā)展——中國(guó)生態(tài)學(xué)會(huì)第七屆全國(guó)會(huì)員代表大會(huì)論文摘要薈萃[C];2004年
相關(guān)重要報(bào)紙文章 前1條
1 景天魁;建立具有中國(guó)時(shí)空特征的理論框架[N];人民日?qǐng)?bào);2004年
相關(guān)碩士學(xué)位論文 前4條
1 任紅洋;基于內(nèi)容和時(shí)空特征的面癱程度定量評(píng)價(jià)的鑒別研究[D];中南林業(yè)科技大學(xué);2017年
2 劉曉曉;氣象監(jiān)測(cè)數(shù)據(jù)的時(shí)空特征分析與建模研究[D];河南大學(xué);2009年
3 李蘭;東北夏季(6—8月)氣溫異常的多尺度時(shí)空特征分析[D];南京氣象學(xué)院;2003年
4 王允;1960~2013年西北綠洲物候性節(jié)氣氣溫的時(shí)空特征與成因分析[D];西北師范大學(xué);2015年
,本文編號(hào):2148529
本文鏈接:http://sikaile.net/yixuelunwen/shenjingyixue/2148529.html