本文關(guān)鍵詞：希爾伯特黃變換方法及其在特征提取中的應(yīng)用研究　出處：《北京科技大學(xué)》2017年博士論文　論文類(lèi)型：學(xué)位論文

  更多相關(guān)文章： 希爾伯特黃變換(HHT) 經(jīng)驗(yàn)?zāi)Ｊ椒纸?EMD) 分形維數(shù) 相位一致性 中藥指紋圖譜 光照人臉識(shí)別

【摘要】：希爾伯特黃變換(Hilbert Huang transform簡(jiǎn)記HHT)具有數(shù)據(jù)驅(qū)動(dòng)性,它是依據(jù)信號(hào)自身特性設(shè)定特征時(shí)間尺度,可將信號(hào)分解成由高頻到低頻的內(nèi)膜函數(shù)(intrinsic mode functions,簡(jiǎn)記IMFs),更能反映非平穩(wěn)信號(hào)的局部特征,從而更能準(zhǔn)確的提取非平穩(wěn)信號(hào)的特征。中藥色譜圖譜識(shí)別問(wèn)題是中藥質(zhì)量控制、中藥真假鑒別、指導(dǎo)中藥材栽培等的重要依據(jù)。同一種中藥因產(chǎn)地不同、野生和栽培不同、栽培方法不同等,其色譜圖存在一定差異,但差異性微小,相似性極高,對(duì)識(shí)別分類(lèi)帶來(lái)了困難,這是中藥質(zhì)量控制、中藥真假鑒別、指導(dǎo)中藥材栽培中的難點(diǎn)問(wèn)題。這一問(wèn)題的解決,關(guān)鍵是對(duì)中藥色譜圖譜特征提取的研究,而中藥色譜圖譜是一系列不同頻率的高斯函數(shù)構(gòu)成的一維信號(hào),其特征提取問(wèn)題應(yīng)是一類(lèi)非平穩(wěn)信號(hào)特征提取問(wèn)題。光照人臉圖像識(shí)別問(wèn)題是人臉識(shí)別難點(diǎn)問(wèn)題,研究其特征提取方法仍是現(xiàn)在人臉識(shí)別研究的熱點(diǎn),光照人臉圖像是二維信號(hào),不同頻率成分在圖像上表現(xiàn)不均勻,增加了識(shí)別的難度。這兩類(lèi)模式識(shí)別問(wèn)題雖然研究的模式背景不同,模式表達(dá)形式不同,但是它們都具有非平穩(wěn)信號(hào)特點(diǎn)。希爾伯特黃變換恰恰針對(duì)非線性非平穩(wěn)信號(hào)處理,具有獨(dú)特的優(yōu)勢(shì),本論文嘗試應(yīng)用希爾伯特黃變換方法解決中藥色譜圖譜和光照人臉圖像特征提取問(wèn)題,并在中藥甘草色譜圖譜識(shí)別和光照人臉圖像識(shí)別中加以驗(yàn)證。本文主要研究工作與創(chuàng)新點(diǎn)如下:1)研究應(yīng)用希爾伯特黃變換(HHT),提取在不同栽培條件下的中藥甘草色譜圖譜的特征。針對(duì)在不同栽培條件下的中藥甘草色譜圖譜,提出了希爾伯特黃變換的經(jīng)驗(yàn)?zāi)Ｊ椒纸?EMD)與分形維數(shù)相結(jié)合的方法,應(yīng)用于中藥甘草色譜圖譜識(shí)別,提取不同栽培條件下的中藥甘草色譜圖譜的特征,即EMD分形特征,并與小波分形特征相比較,識(shí)別結(jié)果表明EMD分形特征分辨能力好于小波分形特征。在此基礎(chǔ)上,為進(jìn)一步提高分類(lèi)識(shí)別效果,有效提取甘草中藥特征,設(shè)計(jì)了一種分割窗EMD分形特征提取算法,并應(yīng)用于不同栽培條件下的甘草色譜圖譜的分類(lèi)。從實(shí)驗(yàn)驗(yàn)證結(jié)果可以明顯看出,分割窗EMD分形特征好于單純使用EMD和EMD分形特征,而且隨著訓(xùn)練樣本集中樣本數(shù)和樣本分解層數(shù)的增加,分類(lèi)識(shí)別率表現(xiàn)非常穩(wěn)定。2)研究利用希爾伯特黃變換(HHT),提取光照人臉的高頻特征。針對(duì)同一個(gè)人在不同光照條件下的人臉識(shí)別問(wèn)題,本文提出了基于EMD高頻IMF特征提取方法和高頻IMF的人臉融合特征提取方法。根據(jù)EMD的自適應(yīng)性和數(shù)據(jù)驅(qū)動(dòng)特性,可以將信號(hào)分解成由高頻到低頻的若干個(gè)IMFs,依據(jù)高頻成分對(duì)光照表現(xiàn)較穩(wěn)定的特點(diǎn),提出用第一個(gè)IMF作為光照人臉識(shí)別特征,在PIE人臉庫(kù)實(shí)驗(yàn)結(jié)果顯示用此特征識(shí)別效果好于用db4小波變換的高頻特征識(shí)別;在此基礎(chǔ)上,進(jìn)一步提出了高頻IMF的人臉融合特征提取方法,光照人臉經(jīng)過(guò)融合,基本消除了不同方向光源在人臉圖像上的影響,在PIE人臉庫(kù)上實(shí)驗(yàn)結(jié)果顯示,融合后識(shí)別率比融合前識(shí)別率提高了近30%。3)研究用數(shù)學(xué)分析方法改進(jìn)希爾伯特黃變換的數(shù)值計(jì)算方法,提取光照人臉的相位特征。由于希爾伯特黃變換的EMD分解過(guò)程,上下包絡(luò)的獲取是采用了三次樣條插值擬合法,缺乏數(shù)學(xué)原理分析,本文提出了一種改進(jìn)的二維移動(dòng)平均濾波方法,替代三次樣條插值擬合得到的上下包絡(luò)均值,經(jīng)過(guò)篩分過(guò)程(BEMD),獲得二維IMFs(BIMF),并將其應(yīng)用于光照人臉相位特征提取,根據(jù)相位一致性原理,對(duì)每一個(gè)BIMF經(jīng)Riesz變換,獲得每個(gè)IMF的單演信號(hào),計(jì)算相位一致函數(shù)值(Phase Congruence 簡(jiǎn)記PC),從而得到光照人臉圖像的相位特征,經(jīng) PIE(Pose,Illumination,and Expression(PIE)face database ofthe Carnegie Mellon University)人臉庫(kù)識(shí)別驗(yàn)證,效果好于改進(jìn)前的傳統(tǒng)EMD方法。本文研究成果不僅對(duì)中藥色譜圖譜和光照人臉識(shí)別特征提取方法研究具有一定指導(dǎo)意義,而且對(duì)一類(lèi)非平穩(wěn)信號(hào)特征提取問(wèn)題以及希爾伯特黃變換方法本身理論和應(yīng)用研究都具有一定的參考價(jià)值。
[Abstract]:Hilbert Huang transform (Hilbert Huang transform abbreviated HHT) is a data driven, it is to set up the characteristic time scale according to the signal characteristics, the signals can be decomposed into low-frequency function into the intima by high frequency (intrinsic mode functions, abbreviated IMFs), to better reflect the local characteristics of non stationary signals, which can more accurately extract features non stationary signal. Chromatographic pattern recognition problem is the quality control of traditional Chinese medicine, Chinese medicine identification, an important basis for the cultivation of medicinal materials in the guide. The same kind of traditional Chinese medicine from different habitats, wild and cultivated different, different cultivation methods, there are some differences between the chromatograms, but the difference is small, high similarity, brought it is difficult to identify the classification and quality control of traditional Chinese medicine, Chinese medicine identification, and difficult problems in cultivation of medicinal materials in the guidance. To solve this problem, the key is to extract the feature of chromatographic From the study, and the traditional Chinese medicine chromatographic fingerprinting is a series of one-dimensional signals of different frequencies of the Gauss function, the feature extraction problem is the extraction problem for a class of nonstationary signal feature. Illumination face image recognition is the face recognition problem, study the method of feature extraction is still a research hotspot now face recognition, illumination face the image is a two-dimensional signal of different frequency components is not uniform in the image, increase the recognition difficulty. These two kinds of pattern recognition problems while different mode of background research, expression patterns of different forms, but they all have non-stationary characteristics. Hilbert Huang transform just to deal with nonlinear and nonstationary signal, has unique advantages. This thesis attempts to apply Hilbert Huang transform method of chromatographic and illumination face image feature extraction problem, and in the chromatographic fingerprints of licorice The identification and illumination face image recognition is verified. The main research work and innovations are as follows: 1) study on the application of Hilbert Huang transform (HHT) feature extraction, chromatographic fingerprints of licorice in different cultivation conditions. The chromatographic fingerprints of licorice in different cultivation conditions, put forward the empirical mode decomposition of Hilbert Huang transform (EMD) method combined with fractal dimension, used in traditional Chinese medicine licorice chromatographic identification, feature extraction of licorice Chromatognun under different cultivation condition, namely EMD fractal characteristics, and the fractal features and wavelet phase comparison, identification results show that the EMD fractal feature resolution better than wavelet based fractal characteristics., in order to further improve the classification effect of traditional Chinese medicine, licorice extract features effectively, design a EMD algorithm to extract the fractal feature segmentation window, and applied in different cultivation conditions The classification of licorice chromatogram. From the experimental results it is clear that the split window EMD fractal feature is better than the simple use of EMD and EMD fractal characteristics, and with the increase of the training sample set the sample number and sample decomposition, classification rate performance is very stable.2) study using Hilbert Huang transform (HHT), extraction of light high frequency facial features. Aiming at the problem of face recognition in the same person under different illumination conditions, this paper put forward a method to extract facial feature extraction method EMD high frequency IMF and high frequency IMF fusion based on the characteristics of driving adaptability and. According to the characteristic of EMD data, it can decompose the signal into several IMFs from high frequency to low frequency. According to the characteristics of high frequency light performance is stable, the first IMF as a light face recognition feature in PIE face database, experimental results show that the recognition effect is better than DB High frequency feature recognition 4 wavelet transform; on this basis, further puts forward the extraction method of high frequency IMF face feature fusion, illumination face after fusion, the effects of different light source in the direction of face image basically eliminated, show the experimental results on PIE face database, the fusion recognition rate before the fusion recognition rate increased 30%.3) numerical calculation method of mathematical analysis method improved Hilbert Huang transform, extracting illumination phase facial features. Because of the decomposition process of Hilbert Huang transform EMD, obtain the envelope is the use of the three spline interpolation fitting, lack of mathematical analysis principle, this paper proposes an improved two-dimensional moving average filtering method, substitute three times by the spline interpolation on the mean envelope, through the screening process (BEMD), IMFs (BIMF), obtained and applied to illumination face feature extraction phase According to the principle, the consistency of phase, for each BIMF by Riesz transform, obtain the monogenic signal of each IMF, calculate the phase congruency function value (Phase Congruence or PC), so as to obtain the light phase features of face image, by PIE (Pose, Illumination, and Expression (PIE) face database ofthe Carnegie Mellon University) face database identification, the effect is better than the traditional EMD method before improvement. This paper research not only on chromatographic profiles and illumination face recognition feature extraction method has a certain guiding significance, but also has a certain reference value and the extraction problem of Hilbert Huang transform method theory and Application Research of a class of nonstationary signal feature.

【學(xué)位授予單位】：北京科技大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TP391.41

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 邵高平;安建平;;基于希爾伯特—黃變換的多項(xiàng)式相位信號(hào)檢測(cè)[J];信號(hào)處理;2009年07期

2 劉麗;匡綱要;;圖像紋理特征提取方法綜述[J];中國(guó)圖象圖形學(xué)報(bào);2009年04期

3 劉小平;賴(lài)劍煌;張智斌;;基于小波子帶圖像的人臉光照歸一化方法[J];中山大學(xué)學(xué)報(bào)(自然科學(xué)版);2007年05期

4 聶祥飛;郭軍;;人臉識(shí)別中基于多小波變換的光照補(bǔ)償[J];計(jì)算機(jī)工程與應(yīng)用;2007年18期

5 陳洋;王潤(rùn)生;;結(jié)合Gabor濾波器和ICA技術(shù)的紋理分類(lèi)方法[J];電子學(xué)報(bào);2007年02期

6 楊云;朱學(xué)峰;;基于第二代小波變換的中藥指紋圖譜的基線提取[J];華南理工大學(xué)學(xué)報(bào)(自然科學(xué)版);2007年01期

7 杜建衛(wèi);程乾生;劉乃強(qiáng);林立;;基于小波變換與分形的中藥指紋圖譜的特征提取[J];信號(hào)處理;2006年05期

8 楊云;朱學(xué)峰;;局部最小二乘法校正中藥指紋圖譜信號(hào)的組分保留時(shí)間漂移[J];華東理工大學(xué)學(xué)報(bào)(自然科學(xué)版);2006年07期

9 杜建衛(wèi);程乾生;劉乃強(qiáng);;中藥色譜指紋圖譜的小波變換與分形[J];數(shù)學(xué)的實(shí)踐與認(rèn)識(shí);2006年07期

10 程乾生;武連文;;時(shí)間序列的經(jīng)驗(yàn)?zāi)B(tài)頻率分解EMFD[J];數(shù)學(xué)的實(shí)踐與認(rèn)識(shí);2006年05期

相關(guān)碩士學(xué)位論文 前1條

1 段天璇;甘草液相色譜指紋圖譜及其應(yīng)用研究[D];北京中醫(yī)藥大學(xué);2006年

，

本文編號(hào)：1393343