基于弹性变分模态分解的癫痫脑电信号分类方法

癫痫脑电信号分类对于癫痫诊治具有重要意义.为了实现病灶性与非病灶性癫痫脑电信号的分类,本文利用弹性网回归重构变分模态分解算法,提出弹性变分模态分解算法并将其应用到所提癫痫脑电信号分类方法中.该方法先将原信号分割成多个子信号,并对各子信号进行弹性变分模态分解,然后从分解后的不同变分模态函数中提取精细复合多尺度散布熵作为特征,最后利用支持向量机进行分类.针对癫痫脑电的公共数据集,最终的实验结果表明,准确率、灵敏度和特异度三个性能指标分别达到92.54%,93.22%和91.86%.     

基于变分模态分解的语音情感识别方法*

针对传统语音情感特征参数在进行情感分类时性能不佳的问题,该文提出了一种基于变分模态分解的语音情感识别方法。情感语音信号首先由变分模态分解提取固有模态函数,然后对所选主导固有模态函数进行重新聚合,再提取梅尔倒谱系数和各固有模态函数的希尔伯特边际谱。为了验证该文提出的特征性能,选用两种语音数据库(EMODB、RAVDESS)进行实验,按该文方法提取特征后使用极限学习机进行语音情感分类识别。实验结果表明:相比基于经验模态分解和集合经验模态分解的语音情感特征,该文提出的特征有更好的识别性能,验证了该方法的实用性。     

Differential 3D shape retrieval

We are presenting a differential three-dimensional (3-D) shape profiling method that is based on the combination of orthogonal fringe projection. It allows us to compute depth gradient maps in a fast and efficient manner. What we are demonstrating is that depth gradients can be computed in a simple way by measuring fringe deformation throughout a novel single-shot approach. We show the usefulness and potential applications of the proposed approach. Validation experiments are presented as well.     

Orthogonal-triangular decomposition ghost imaging

Ghost imaging (GI) offers great potential with respect to conventional imaging techniques. However, there are still some obstacles for reconstructing images with high quality, especially in the case that the orthogonal measurement matrix is impossible to construct. In this paper, we propose a new scheme based on the orthogonal-triangular (QR) decomposition, named QR decomposition ghost imaging (QRGI) to reconstruct a better image with good quality. In the scheme, we can change the randomly non-orthogonal measurement matrix into orthonormal matrix by performing QR decomposition in two cases. (1) When the random measurement matrix is square, it can be firstly decomposed into an orthogonal matrix $\bm Q$ and an upper triangular matrix $\bm R$. Then let the off-diagonal values of $\bm R$ equal to 0.0, the diagonal elements of $\bm R$ equal to a constant $k$, where $k$ is the average of all values of the main diagonal, so the resulting measurement matrix can be obtained. (2) When the random measurement matrix is with full rank, we firstly compute its transpose, and followed with above QR operation. Finally, the image of the object can be reconstructed by correlating the new measurement matrix and corresponding bucket values. Both experimental and simulation results verify the feasibility of the proposed QRGI scheme. Moreover, the results also show that the proposed QRGI scheme could improve the imaging quality comparing to traditional GI (TGI) and differential GI (DGI). Besides, in comparison with the singular value decomposition ghost imaging (SVDGI), the imaging quality and the reconstruction time by using QRGI are similar to those by using SVDGI, while the computing time (the time consuming on the light patterns computation) is substantially shortened.     

Iris segmentation using variational level set method

Continuous efforts have been made to process degraded iris images for enhancement of the iris recognition performance in unconstrained situations. Recently, many researchers have focused on developing the iris segmentation techniques, which can deal with iris images in a non-cooperative environment where the probability of acquiring unideal iris images is very high due to gaze deviation, noise, blurring, and occlusion by eyelashes, eyelids, glasses, and hair. Although there have been many iris segmentation methods, most focus primarily on the accurate detection of iris images captured in a closely controlled environment. The novelty of this research effort is that we propose to apply a variational level set-based curve evolution scheme that uses a significantly larger time step to numerically solve the evolution partial differential equation (PDE) for segmentation of an unideal iris image accurately, and thereby, speeding up the curve evolution process drastically. The iris boundary represented by the variational level set may break and merge naturally during evolution, and thus, the topological changes are handled automatically. The proposed variational model is also robust against poor localization and weak iris/sclera boundaries. In order to solve the size irregularities occurring due to arbitrary shapes of the extracted iris/pupil regions, a simple method is applied based on connection of adjacent contour points. Furthermore, to reduce the noise effect, we apply a pixel-wise adaptive 2D Wiener filter. The verification and identification performance of the proposed scheme is validated on three challenging iris image datasets, namely, the ICE 2005, the WVU Unideal, and the UBIRIS Version 1.     

Noise source identification of diesel engine based on variational mode decomposition and robust independent component analysis

Through separating and identifying the noise sources of diesel engine, each independent noise obtained can be used as reference for the noise reduction, condition monitoring and fault diagnosis. In the noise source identification of diesel engine, the combustion noise and the piston slap noise are found to be overlapped in time domain and frequency domain. So it is intricate to accurately separate them. Therefore, the noise source identification method which is based on variational mode decomposition (VMD), robust independent component analysis (RobustICA) and continuous wavelet transform (CWT) is proposed. In the test, a 6-cylinder diesel engine was tested in a semi-anechoic chamber. The lead wrapped method was adopted to wrap No. 1–5 cylinders so as to isolate the interference noises, only the No. 6 cylinder part was bared. The single channel noise signal of cylinder head was measured. Then the variational mode decomposition algorithm is utilized to decompose the noise signal into several variational mode components. The RobustICA algorithm is adopted to extract the independent components. Finally, the continuous wavelet transform and the prior knowledge of diesel engine are applied to further identify the separated results. The results show that by using the proposed method to separate and identify the radiation noise of the cylinder head of the diesel engine, the independent components obtained are respectively the combustion noise and the piston slap noise. Comparing with the EEMD-RobustICA-CWT method, each independent noises obtained through the proposed method are more accurate and pure with less other interference noises.     

基于改进经验模态分解域内心动物理特征识别模式分量的心电信号重建

心电图(electrocardiogram,ECG)诊断心脏疾病的严格标准,要求有效地消除噪声并准确地重建ECG信号.经验模式分解(empirical mode decomposition,EMD)方法重建ECG信号中,模式混叠及重建采用模式分量的识别以经验为基础,导致重建ECG信号准确度降低,且方法不具有自适应和通用性.本文首先基于积分均值定理提出一种改进的EMD方法——积分均值模式分解(integral mean mode decomposition,IMMD)方法,经5000个高斯白噪声样本的蒙特卡罗法验证,IMMD方法比EMD具有更优多分辨率分析能力,能够有效地缓解模式混叠.其次,基于ECG信号内固有心动物理特征量识别重建ECG信号所采用的模式分量,具有现实物理意义,因此,方法具有自适应和通用性.经验证,提出方法重建47例ECG信号与原ECG信号的相关系数中:31例优于变分模式分解方法;33例优于Haar小波软阈值法;42例优于集总经验模式分解方法;45例优于EMD方法.相关系数均值为0.8904,方差为0.0071,表现稳定且最优.     

基于彩色光栅投影的快速三维测量方法

 针对条纹投影术提取物体高度信息的问题,提出了一种新的基于彩色光栅投影的三维测量方法。对选取G分量为255,R,B分量各取0或255而组成的青、白、黄、绿四色遵循格雷码原理进行编码,然后将G分量作正弦调制形成投影光栅投向被测物体。提取采集到的光栅变形图中G分量,利用傅里叶变换方法得到其初始相位;同时对采集到图像中的R,B分量作阈值迭代分割而G分量自动赋值为255,综合三分量信息得到条纹颜色信息进而获取条纹的周期信息,从而展开相位。全过程仅需投影一幅彩色光栅图就能完成三维测量,实验结果表明该算法易于实现,在测量实时性和精确性上表现良好。     

Phase retrieval from fringe pattern with 1-D discrete wavelet transform

This paper proposes a novel method to obtain frequency modulation (FM) signals from a single fringe pattern for phase retrieval. First, a 1D discrete Meyer wavelet is employed to decompose the pattern image signal row by row and the soft-thresholding approach is applied to remove noise. The low frequency coefficients of the wavelet decomposition are then set to 0, and the signal is reconstructed. Moreover, the optimal wavelet decomposition level is adaptively determined using a cost function-based method. The reconstructed signal, which no longer contains a background component, is normalized using a nonlinear and piecewise normalization method. The proposed method is faster and more accurate than some other phase retrieval approaches, which is illustrated with two test cases.     

Strong and weak constraint variational assimilations for reduced order fluid flow modeling

In this work we propose and evaluate two variational data assimilation techniques for the estimation of low order surrogate experimental dynamical models for fluid flows. Both methods are built from optimal control recipes and rely on proper orthogonal decomposition and a Galerkin projection of the Navier Stokes equation. The techniques proposed differ in the control variables they involve. The first one introduces a weak dynamical model defined only up to an additional uncertainty time-dependent function whereas the second one, handles a strong dynamical constraint in which the dynamical system’s coefficients constitute the control variables. Both choices correspond to different approximations of the relation between the reduced basis on which is expressed the motion field and the basis components that have been neglected in the reduced order model construction. The techniques have been assessed on numerical data and for real experimental conditions with noisy particle image velocimetry data.     

A flexible fast 3D profilometry based on modulation measurement

This paper proposes a flexible fast profilometry based on modulation measurement. Two orthogonal gratings through a beam splitter are vertically projected on an object surface, and the measured object is placed between the imaging planes of the two gratings. Then the image of the object surface modulated by the orthogonal gratings can be obtained by a CCD camera in the same direction as the grating projection. This image is processed by the operations consisting of performing the Fourier transform, spatial frequency filtering and inverse Fourier transform. Using the modulation distributions of two grating patterns, we can reconstruct the 3D shape of the object. In the measurement process, we only need to capture one fringe pattern, so it is faster than the MMP and remains the advantages of it. In the article, the principle of this method, the setup of the measurement system, some simulations and primary experiment results are given. The simulative and experimental result proves it can restore the 3D shape of the complex object fast and comparatively accurate. Because only one fringe pattern is needed in the testing, our method has a promising extensive application prospect in real-time acquiring and dynamic measurement of 3D data of complex objects.     

Fringe pattern denoising via image decomposition

Filtering off noise from a fringe pattern is one of the key tasks in optical interferometry. In this Letter, using some suitable function spaces to model different components of a fringe pattern, we propose a new fringe pattern denoising method based on image decomposition. In our method, a fringe image is divided into three parts: low-frequency fringe, high-frequency fringe, and noise, which are processed in different spaces. An adaptive threshold in wavelet shrinkage involved in this algorithm improves its denoising performance. Simulation and experimental results show that our algorithm obtains smooth and clean fringes with different frequencies while preserving fringe features effectively.     

Three-dimensional shape measurement technique for shiny surfaces by adaptive pixel-wise projection intensity adjustment

Conventional methods based on analyses of the absolute gray levels of pixels in fringe pattern images are affected by the problems of image saturation, interreflection, and high sensitivity to noise when obtaining three-dimensional (3D) shape measurements of shiny surfaces. This study presents a robust, adaptive, and fast 3D shape measurement technique, which adaptively adjusts the pixel-wise intensity of the projected patterns, thus it avoids image saturation and has a high signal to noise ratio (SNR) during 3D shape measurement for shiny surfaces. Compared with previous time-consuming methods using multiple exposures and the projection of fringe patterns with multiple intensities, where a large number of fringe pattern images need to be captured, the proposed technique needs to capture far fewer pattern images for measurement. In addition, it can greatly reduce the time costs to obtain the optimal projection intensities by the fusion of uniform gray level patterns and coordinates mapping. Our experimental results demonstrate that the proposed technique can achieve highly accurate and efficient 3D shape measurement for shiny surfaces.     

遗传算法优化变分模态分解提取舰船辐射噪声特征线谱方法

特征线谱提取是舰船目标识别的一个重要研究环节,常采用传统的DEMON谱分析方法,处理过程中,一般对舰船噪声时域信号未予抑噪,低信噪比情况下,传统DEMON谱分析性能差。对此,提出一种采用遗传算法优化变分模态分解方法,用于分解舰船噪声原时域信号,获得抑制噪声后的舰船噪声重构信号,进而有效提取了舰船目标噪声幅度调制特征线谱。该方法首先采用遗传算法优化变分模态分解的两个关键输入参数(分解所取模态个数和惩罚因子),对变分模态分解得到的各阶固有模态分量加以判别,去除噪声主导分量,保留信号主导分量,使重构舰船噪声信号显著抑制了干扰噪声,然后对降噪后的重构信号进行频谱分析,获得目标噪声调制特征线谱。理论分析、仿真和实验数据处理结果表明,相比传统DEMON谱分析法,基于遗传算法优化变分模态分解的舰船噪声特征线谱提取方法具有更好的噪声抑制能力,所获取的舰船噪声幅度调制特征线谱信噪比明显高于传统DEMON方法,具有一定优势,前景良好。     

基于变分模态分解与多尺度排列熵的生物组织变性识别

根据高强度聚焦超声(HIFU)治疗中超声散射回波信号的特点,本文利用变分模态分解(VMD)与多尺度排列熵(MPE)对生物组织变性识别进行了研究.首先对生物组织中的超声散射回波信号进行变分模态分解,根据各阶模态的功率谱信息熵值分离出噪声分量和有用分量;对分离出的有用信号进行重构并提取其多尺度排列熵;然后通过Gustafson-Kessel (GK)模糊聚类确定聚类中心,采用欧氏贴近度与择近原则对生物组织进行变性识别.将所提方法应用于HIFU治疗中超声散射回波信号实验数据,用遗传算法对多尺度排列熵的参数优化后,对293例未变性组织和变性组织的超声散射回波信号数据进行了多尺度排列熵分析,发现变性组织的超声散射回波信号的多尺度排列熵值要高于未变性组织;多尺度排列熵可以较好地识别生物组织是否变性.相对于EMD-MPE-GK模糊聚类以及VMD-小波熵(WE)-GK模糊聚类变性识别方法,本文所提方法中变性与未变性组织特征交叠区域数据点更少,聚类效果和分类性能更好;本实验环境下生物组织变性识别结果表明,该方法的识别率更高,高达93.81%.     

A novel color fringe projection based Fourier transform 3D shape measurement method

A novel Fourier transform 3D shape measurement method based on color fringe projection is proposed in order to solve the spectrum overlapping and phase unwrapping problems existed in Fourier transform profilometry (FTP). The R and G components of the color fringe are set to two sinusoidal patterns with different frequencies and the B component is set to the average value of R or G component. Then this pattern is projected to the object and the deformed fringe image is captured. Three gray patterns are separated from the color fringe, the background and high frequency noise can be eliminated using our method and the accurate unwrapped phase can be got. Only one shot color pattern is projected to get the 3D information of the object. Experiment results show that the 3D information of an object can be obtained rapidly and accurately.     

A novel variational principle in electrostatics and its consequences

We propose a novel variational principle in electrostatics and show that one can derive mirror equation in the context of image problem starting from this principle.     

Anti-spoof touchless 3D fingerprint recognition system using single shot fringe projection and biospeckle analysis

Fingerprint is a unique, un-alterable and easily collected biometric of a human being. Although it is a 3D biological characteristic, traditional methods are designed to provide only a 2D image. This touch based mapping of 3D shape to 2D image losses information and leads to nonlinear distortions. Moreover, as only topographic details are captured, conventional systems are potentially vulnerable to spoofing materials (e.g. artificial fingers, dead fingers, false prints, etc.). In this work, we demonstrate an anti-spoof touchless 3D fingerprint detection system using a combination of single shot fringe projection and biospeckle analysis. For fingerprint detection using fringe projection, light from a low power LED source illuminates a finger through a sinusoidal grating. The fringe pattern modulated because of features on the fingertip is captured using a CCD camera. Fourier transform method based frequency filtering is used for the reconstruction of 3D fingerprint from the captured fringe pattern. In the next step, for spoof detection using biospeckle analysis a visuo-numeric algorithm based on modified structural function and non-normalized histogram is proposed. High activity biospeckle patterns are generated because of interaction of collimated laser light with internal fluid flow of the real finger sample. This activity reduces abruptly in case of layered fake prints, and is almost absent in dead or fake fingers. Furthermore, the proposed setup is fast, low-cost, involves non-mechanical scanning and is highly stable.     

复杂刚性运动物体的高精度三维测量算法

基于相移法的三维形貌重建精度高,对环境噪声和阴影等不敏感,但由于多幅条纹解相位,难以应用于动态物体的三维测量中,为此,提出了一种新的算法.基于Harris算法提取刚性运动棋盘格的角点,确定相邻两帧采集条纹图像之间的像素偏差并校正采集条纹图像;根据投影仪和摄像机的标定参数建立投影图像和采集图像之间的空间变换矩阵,并根据变...