基于形态特征提取的图像匹配搜索技术研究

传统的图像搜索方法一般是由图像处理软件自动抽取图像的颜色、形状、纹理等特征,并以此建立特征索引库,进而由用户输入要查找的物品图像,从而找出与之具有相近特征的图像。而文中给出了从数学形态学的角度来提取图像的关键形态特征,然后建立海量物品图片的形态细化骨架库,并以此简化图像搜索的关键内容,降低数据库存储量,提高匹配效率以及准确性的具体方法。     

求解泊松方程的紧致修正法

将紧致格式与低阶格式结合,构造紧致格式的修正项,并将修正项加入到源项中进行求解,得到了一种基于非均分网格求解泊松方程的紧致修正法,且将该方法应用于二维和三维泊松方程的数值求解中。数值计算结果表明:紧致修正方法的精度高于经典方法的精度,但四阶紧致修正方法比二阶经典方法对网格的依赖性强。     

The Output Feedback H∞ Control Design for the Linear Stochastic System Driven by Both Brownian Motion and Poisson Jumps: A Nonlinear Matrix Inequality Approach

We extend the output feedback H_∞ control approaches to the stochastic system including Poisson jumps. In this model, both the control and exogenous disturbance simultaneously enter the volatility and jumps. By completing square methods, a nonlinear matrix inequality is used for solving such problems to give the necessary and sufficient conditions for the existence of a compensator.     

Multi-block Poisson grid generator for cascade simulations

High quality computational grids can greatly enhance the accuracy of turbine and compressor cascade simulations especially when time-dependent results are sought where vortical structures are convected through the computational domain. A technique for generating periodic structured grids for cascade simulations based on the Poisson equations is described. To allow for more complex geometries, the grid can be divided into individual zones or blocks. The grids are generated simultaneously in all blocks, assuring continuity of the grid lines and their slopes across the zonal boundaries. Simple geometric rules can be employed for enforcing orthogonality at block boundaries. The method results in grids with low grid distortion by allowing both, block boundaries and grid points on physical boundaries, to move freely. Results are presented for a linear turbine and a linear compressor cascade.     

基于透明度的目标提取的研究

景象提取的目的是将数字图像中的景物从背景中分离出来,为了更好地实现这一目的,微软亚洲研究院Jian Sun等人于2004年提出Poisson Matting方法.该方法将透明度(α值)作为图像的一种内在属性,变分地寻求其最优解,来达到目标提取的目的.主要介绍Poisson算法,针对Poisson算法中程序运行时间比较长的问题,对算法中耗用时间多的两个步骤:图像初始α值的计算以及前景图像F、背景图像B的计算进行了改进,在VC6.0中进行了实现,并取得了较好效果.     

基于抠像技术的图像无缝融合算法

为了更快更好的进行图像融合,在用自由融合算法对泊松图像编辑与抠像技术进行改进的基础上,实现了一套图像自由无缝融合算法。该融合算法首先利用抠像技术来提取图像中的物体边缘,然后迭代求解泊松方程,从而取得了自然的融合效果。该算法与最新的无缝融合算法相比,其优点在于:①对于前景与背景的颜色变化复杂的图像,仍可得到准确的边缘;②可以使用户能引导前景映射图的走向;③无论图像前景层中存在多少个洞,融合效果将不受任何影响。这使得该算法的应用具有相当的灵活性。对于目前的图像融合技术而言,该算法可以获得更高的融合质量、更快的处理速度以及多样的融合效果。     

Path integral solution for nonlinear systems under parametric Poissonian white noise input

In this paper the problem of the response evaluation in terms of probability density function of nonlinear systems under parametric Poisson white noise is addressed. Specifically, extension of the Path Integral method to this kind of systems is introduced. Such systems exhibit a jump at each impulse occurrence, whose value is obtained in closed form considering two general classes of nonlinear multiplicative functions. Relying on the obtained closed form relation liking the impulses amplitude distribution and the corresponding jump response of the system, the Path Integral method is extended to deal with systems driven by parametric Poissonian white noise. Several numerical applications are performed to show the accuracy of the results and comparison with pertinent Monte Carlo simulation data assesses the reliability of the proposed procedure.     

On the Modelling and Monitoring of General Inflated Poisson Processes

In this work, we propose and study general inflated probability distributions that can be used for modelling and monitoring unusual count data. The considered models extend the well‐known zero‐inflated Poisson distribution because they allow the excess of values, other than zero. Four simple upper‐sided control schemes are considered for the monitoring of count data based on the proposed general inflated Poisson distributions, and their performance is evaluated under various out‐of‐control situations. The usefulness of the considered models and techniques is illustrated via two real‐data examples, while practical guidelines are provided as well. Copyright © 2015 John Wiley & Sons, Ltd.     

Control Charts with Variable Dimension for Linear Combination of Poisson Variables

This article analyzes the simultaneous control of several correlated Poisson variables by using the Variable Dimension Linear Combination of Poisson Variables (VDLCP) control chart, which is a variable dimension version of the LCP chart. This control chart uses as test statistic, the linear combination of correlated Poisson variables in an adaptive way, i.e. it monitors either p₁ or p variables (p₁ < p) depending on the last statistic value. To analyze the performance of this chart, we have developed software that finds the best parameters, optimizing the out‐of‐control average run length (ARL) for a shift that the practitioner wishes to detect as quickly as possible, restricted to a fixed value for in‐control ARL. Markov chains and genetic algorithms were used in developing this software. The results show performance improvement compared to the LCP chart. Copyright © 2015 John Wiley & Sons, Ltd.     

Application of the Galerkin and Least-Squares Finite Element Methods in the solution of 3D Poisson and Helmholtz equations

This paper presents the numerical solution, by the Galerkin and Least Squares Finite Element Methods, of the three-dimensional Poisson and Helmholtz equations, representing heat diffusion in solids. For the two applications proposed, the analytical solutions found in the literature review were used to compare with the numerical solutions. The analysis of results was made from the L₂ norm (average error throughout the domain) and L_∞ norm (maximum error in the entire domain). The results of the two applications (Poisson and Helmholtz equations) are presented and discussed for testing of the efficiency of the methods.