Registration and integration algorithm in structured light three-dimensional scanning based on scale-invariant feature matching of multi-source images

Based on the homography between a multi-source image and three-dimensional (3D) measurement points, this letter proposes a novel 3D registration and integration method based on scale-invariant feature matching. The matching relationships of two-dimensional (2D) texture gray images and two-and-a-half- dimensional (2.5D) range images are constructed using the scale-invariant feature transform algorithms. Then, at least three non-collinear 3D measurement points corresponding to image feature points are used to achieve a registration relationship accurately. According to the index of overlapping images and the local 3D border search method, multi-view registration data are rapidly and accurately integrated. Experimental results on real models demonstrate that the algorithm is robust and effective.     

基于邻域特征点提取和匹配的点云配准

为解决噪声干扰、数据丢失情况下迭代最近点算法的鲁棒性差、配准精度低等问题,提出一种基于邻域特征点提取和匹配的点云配准方法.首先定义一个由点的k邻域曲率、点与邻近点的法向量内积均值以及邻近点与邻域拟合平面的欧氏距离方差等三部分组成的邻域特征参数,结合在移动最小二乘表面构造的曲率特征参数对点云进行两次特征点提取;其次依据直方图特征定义三个匹配条件,并用双重约束获得正确的匹配点对;最后在配准阶段,采用双向构建k维树的迭代最近点算法实现精确配准.实验结果表明,该算法的配准精度较迭代最近点算法提高了90%以上,并且能够在噪声环境下有效地完成缺失点云的配准,在鲁棒性和精确配准方面有明显优势.     

基于局部血管结构特征的眼底图像二级配准

提出了一种结合全局配准和局部配准技术的眼底图像二级配准算法,该算法采用4个相连的分叉点组成的局部血管结构来代替单独的分叉点作为配准特征,通过减少配对点集,提高了配准效率.同时针对非线性形变造成的局部配准偏移较大的问题,在全局配准基础上进一步采用局部配准技术,提升了配准的准确度.实验结果表明,该算法以很高的配准效率和准确度有效实现了眼底图像的配准.     

Interactions between global and grazing bifurcations in an impacting system

It is well known that the locus of boundary crises in smooth systems contains gaps that give rise to periodic windows. We show that this phenomenon can also be observed in an impacting system, and that the mechanism by which these gaps are created is different. Namely, here gaps are created and disappear at points along the branches of boundary crises where they are intersected by branches of grazing bifurcations. We locate a novel type of double-crisis vertex which we call a grazing-crisis vertex. Additionally, we illustrate several types of basin-boundary metamorphosis that are intricately related with grazing bifurcations.     

Adaptive registration of diffusion tensor images on lie groups

With diffusion tensor imaging (DTI), more exquisite information on tissue microstructure is provided for medical image processing. In this paper, we present a locally adaptive topology preserving method for DTI registration on Lie groups. The method aims to obtain more plausible diffeomorphisms for spatial transformations via accurate approximation for the local tangent space on the Lie group manifold. In order to capture an exact geometric structure of the Lie group, the local linear approximation is efficiently optimized by using the adaptive selection of the local neighborhood sizes on the given set of data points. Furthermore, numerical comparative experiments are conducted on both synthetic data and real DTI data to demonstrate that the proposed method yields a higher degree of topology preservation on a dense deformation tensor field while improving the registration accuracy.     

A novel method for detecting and counting overlapping tracks in SSNTD by image processing techniques

Overlapping object detection and counting is a challenge in image processing. A new method for detecting and counting overlapping circles is presented in this paper. This method is based on pattern recognition and feature extraction using “neighborhood values“ in an object image by implementation of image processing techniques. The junction points are detected by assignment of a value for each pixel in an image. As is shown, the neighborhood values for junction points are larger than the values for other points. This distinction of neighborhood values is the main feature which can be utilized to identify the junction points and to count the overlapping tracks. This method can be used for recognizing and counting charged particle tracks, blood cells and also cancer cells. The method is called “Track Counting based on Neighborhood Values” and is symbolized by “TCNV”.     

Spline based least squares integration for two-dimensional shape or wavefront reconstruction

In this work, we present a novel method to handle two-dimensional shape or wavefront reconstruction from its slopes. The proposed integration method employs splines to fit the measured slope data with piecewise polynomials and uses the analytical polynomial functions to represent the height changes in a lateral spacing with the pre-determined spline coefficients. The linear least squares method is applied to estimate the height or wavefront as a final result. Numerical simulations verify that the proposed method has less algorithm errors than two other existing methods used for comparison. Especially at the boundaries, the proposed method has better performance. The noise influence is studied by adding white Gaussian noise to the slope data. Experimental data from phase measuring deflectometry are tested to demonstrate the feasibility of the new method in a practical measurement.     

基于非采样Contourlet变换高分辨率遥感图像配准

为了提高高分辨率遥感图像配准的精确度,将非采样Contourlet变换应用于高分辨率遥感图像配准算法中.首先对高分辨率遥感图像进行非采样Contourlet变换.利用非采样Contourlet变换的平移不变性在变换域提取图像的边缘并选择合适的阈值准确地得到图像的边缘特征点.然后利用归一化互相关匹配法和概率支撑法对特征点进行匹配.最后通过三角形局部变换映射甬数实现图像配准.实验结果表明,该方法更能准确地提取高分辨率遥感图像的特征点,大大提高了正确匹配的概率,与基于小波方法的图像配准效果相比有更高的准确性和稳健性.     

Navier-Stokes方程的最小二乘等几何方法

基于Hermite多项式的C¹型单元构造复杂,限制了最小二乘有限元法的应用.引入高阶光滑的非均匀有理B样条作为基函数简化C¹型单元构造,提出求解黏性不可压流动Navier-Stokes方程的最小二乘等几何方法.用Newton法或Picard法对Navier-Stokes方程线性化,用线性化偏微分方程的余量定义最小二乘泛函,导出最小二乘变分方程,用NURBS构造高阶光滑的有限维空间来近似速度场和压力场.计算表明:本文方法计算的二维顶盖驱动流数值解能准确描述流动状况,计算的二维通道内圆柱绕流全局质量损失由最小二乘有限元法的6%降为0.018%,该方法可用于Navier-Stokes方程的求解,并且具有较好的质量守恒性.     

Rapid and robust medical image elastic registration using mean shift algorithm

In landmark-based image registration, estimating the landmark correspondence plays an important role. In this letter, a novel landmark correspondence estimation technique using mean shift algorithm is proposed. Image corner points are detected as landmarks and mean shift iterations are adopted to find the most probable corresponding point positions in two images. Mutual information between intensity of two local regions is computed to eliminate mis-matching points. Multi-level estimation (MLE) technique is proposed to improve the stability of corresponding estimation. Experiments show that the precision in location of correspondence landmarks is exact. The proposed technique is shown to be feasible and rapid in the experiments of various mono-modal medical images.     

Phase transition of surface models with intrinsic curvature

It is reported that a surface model of Polyakov strings undergoes a first-order phase transition between smooth and crumpled (or branched polymer) phases. The Hamiltonian of the model contains the Gaussian term and a deficit angle term corresponding to the weight of the integration measure dX in the partition function.     

一种新的基于场景的红外焦平面阵列非均匀性校正算法

设计了基于小波变换去噪、序列图像配准、正交最小二乘拟合的基于场景的非均匀性校正算法,该算法不仅能适应红外焦平面阵列非(IRFPA)均匀性随时间和环境变化而发生缓慢变化的情况,而且对一般基于场景分析的校正算法中形成的校正虚像也有很好的抑制作用.模拟实验结果验证了其有效性和先进性.     

Balanced multi-image demons for non-rigid registration of magnetic resonance images

A new approach is introduced for non-rigid registration of a pair of magnetic resonance images (MRI). It is a generalization of the demons algorithm with low computational cost, based on local information augmentation (by integrating multiple images) and balanced implementation. Specifically, a single deformation that best registers more pairs of images is estimated. All these images are extracted by applying different operators to the two original ones, processing local neighbors of each pixel. The following five images were found to be appropriate for MRI registration: the raw image and those obtained by contrast-limited adaptive histogram equalization, local median, local entropy and phase symmetry. Thus, each local point in the images is supplemented by augmented information coming by processing its neighbor. Moreover, image pairs are processed in alternation for each iteration of the algorithm (in a balanced way), computing both a forward and a backward registration.The new method (called balanced multi-image demons) is tested on sagittal MRIs from 10 patients, both in simulated and experimental conditions, improving the performances over the classical demons approach with minimal increase of the computational cost (processing time around twice that of standard demons). Specifically, a simulated deformation was applied to the MRIs (either original or corrupted by additive Gaussian or speckle noises). In all tested cases, the new algorithm improved the estimation of the simulated deformation (squared estimation error decreased by about 65% in the average). Moreover, statistically significant improvements were obtained in experimental tests, in which different brain regions (i.e., brain, posterior fossa and cerebellum) were identified by the atlas approach and compared to those manually delineated (in the average, Dice coefficient increased of about 6%).The conclusion is that a balanced method applied to multiple information extracted from neighboring pixels is a low cost approach to improve registration of MRIs.     

基于静态小波分解和能量函数优化的图像拼接

提出了一种基于静态小波分解和能量函数优化的全景图拼接算法.该算法首先使用静态小波分解初始图像,并利用序贯检验法对高频图像快速搜索计算粗略匹配序列,在此基础上对初始图像细致搜索计算精确匹配点；对于传统图像融合处理中采用的线性加权函数通常引起的重叠区域模糊问题,采用包含图像梯度的能量函数计算高频图像的全局最优融合因子进行融合,而低频图像则采用线性因子融合.实验表明,该算法在降低匹配运算时间的同时又能获得满意的视觉效果.     

Two-loop quark self-energy in a new formalism (I) Overlapping divergences

A new integration technique for multi-loop Feynman integrals, called the matrix method, is developed and then applied to the divergent part of the overlapping two-loop quark self-energy function iΣ in the light-cone gauge n · A^a(x) = 0, n² = 0. It is shown that the coefficient of the double-pole term is strictly local, even off mass-shell, while the coefficient of the single-pole term contains local as well as nonlocal parts. On mass-shell, the single-pole part is local, of course. It is worth noting that the original overlapping self-energy integral reduces eventually to 10 covariant and 38 noncovariant-gauge integrals. We were able to verify explicitly that the divergent parts of the 10 double covariant-gauge integrals agreed precisely with those currently used to calculate radiative corrections in the Standard Model.

Our new technique is amazingly powerful, being applicable to massive and massless integrals alike, and capable of handling both covariant-gauge integrals and the more difficult noncovariant-gauge integrals. Perhaps the most important feature of the matrix method is the ability to execute the 4ω-dimensional momentum integrations in a single operation, exactly and in analytic form. The method works equally well for other axial-type gauges, notably the temporal gauge (n² > 0) and the pure axial gauge (n² < 0).     

Accurate,high-order representation of complex three-dimensional surfaces via Fourier continuation analysis

We present a new method for construction of high-order parametrizations of surfaces: starting from point clouds, the method we propose can be used to produce full surface parametrizations (by sets of local charts, each one representing a large surface patch – which, typically, contains thousands of the points in the original point-cloud) for complex surfaces of scientific and engineering relevance. The proposed approach accurately renders both smooth and non-smooth portions of a surface: it yields super-algebraically convergent Fourier series approximations to a given surface up to and including all points of geometric singularity, such as corners, edges, conical points, etc. In view of their C^∞ smoothness (except at true geometric singularities) and their properties of high-order approximation, the surfaces produced by this method are suitable for use in conjunction with high-order numerical methods for boundary value problems in domains with complex boundaries, including PDE solvers, integral equation solvers, etc. Our approach is based on a very simple concept: use of Fourier analysis to continue smooth portions of a piecewise smooth function into new functions which, defined on larger domains, are both smooth and periodic. The “continuation functions” arising from a function f converge super-algebraically to f in its domain of definition as discretizations are refined. We demonstrate the capabilities of the proposed approach for a number of surfaces of engineering relevance.     

Reduced surface point selection options for efficient mesh deformation using radial basis functions

Previous work by the authors has developed an efficient method for using radial basis functions (RBFs) to achieve high quality mesh deformation for large meshes. For volume mesh deformation driven by surface motion, the RBF system can become impractical for large meshes due to the large number of surface (control) points, and so a particularly effective data reduction scheme has been developed to vastly reduce the number of surface points used. The method uses a chosen error function on the surface mesh to select a reduced subset of the surface points; this subset contains a sufficiently small number of points so as to make the volume deformation fast, and a correction function is used to correct those surface points not included. Hence, the scheme is split such that both parts are working on appropriate problems. RBFs are an excellent way of finding smooth orthogonality preserving global deformations, but are less suitable for enforcing an exact geometry for a large number of points, while a simpler approach is ideal for diffusing small changes evenly but has quality (and possibly expense) drawbacks if used for the entire volume. However, alternatives exist for the error function used to select the reduced data set, so here a comparison is made between three different options: the surface error function, the unit function and the power function. Tests run on structured and unstructured meshes show that the surface error function gives the lowest errors, but this also requires a deformed surface shape to be known in advance of the simulation. The unit and power functions both avoid the need for a deformed surface, and the unit function is shown to be superior.     

Accurate, high-order representation of complex three-dimensional surfaces via Fourier continuation analysis

We present a new method for construction of high-order parametrizations of surfaces: starting from point clouds, the method we propose can be used to produce full surface parametrizations (by sets of local charts, each one representing a large surface patch – which, typically, contains thousands of the points in the original point-cloud) for complex surfaces of scientific and engineering relevance. The proposed approach accurately renders both smooth and non-smooth portions of a surface: it yields super-algebraically convergent Fourier series approximations to a given surface up to and including all points of geometric singularity, such as corners, edges, conical points, etc. In view of their C^∞ smoothness (except at true geometric singularities) and their properties of high-order approximation, the surfaces produced by this method are suitable for use in conjunction with high-order numerical methods for boundary value problems in domains with complex boundaries, including PDE solvers, integral equation solvers, etc. Our approach is based on a very simple concept: use of Fourier analysis to continue smooth portions of a piecewise smooth function into new functions which, defined on larger domains, are both smooth and periodic. The “continuation functions” arising from a function f converge super-algebraically to f in its domain of definition as discretizations are refined. We demonstrate the capabilities of the proposed approach for a number of surfaces of engineering relevance.     

The influence of different integration time on stoichiometric analysis in near infrared grating spectrometers

Grating spectrometers are widely used in NIR spectroscopic analysis as a spectrum acquisition instrument. The sensitivity of the spectrometer can be varied by changing the integration time. In this paper, we study the influence of varying integration time on Stoichiometric analysis. The NIR spectra of different intralipid suspensions measured at five integration time were collected, which were then used to establish a model to predict the intralipid suspensions concentration by using the partial least squares regression (PLSR) method. “Cross-validation method” was used to evaluate the errors caused by the different integration times. Experimental results showed that the model accuracy is different based on the root-mean-square error of the calibration set (RMSEC), which ranged from 0.0016 to 0.3488. With the method of “Cross-validation,” all the root-mean-square errors of the prediction set (RMSEP) were larger than the RMSECs, up to two orders of magnitude. This study demonstrates that the integration time has a nonlinear relationship with the light intensity obtained by the spectrometer, this nonlinearity will affect the measurement accuracy. Therefore, we should pay attention to the influence by varying integration time on the measurement in the stoichiometric analysis.