Wavelet packet correlation methods in biometrics

We introduce wavelet packet correlation filter classifiers. Correlation filters are traditionally designed in the image domain by minimization of some criterion function of the image training set. Instead, we perform classification in wavelet spaces that have training set representations that provide better solutions to the optimization problem in the filter design. We propose a pruning algorithm to find these wavelet spaces by using a correlation energy cost function, and we describe a match score fusion algorithm for applying the filters trained across the packet tree. The proposed classification algorithm is suitable for any object-recognition task. We present results by implementing a biometric recognition system that uses the NIST 24 fingerprint database, and show that applying correlation filters in the wavelet domain results in considerable improvement of the standard correlation filter algorithm.     

准正交单小波及其数学特性

从构建正交尺度函数与小波的共轭正交滤波器的条件出发,把滤波器的正交条件设计成目标函数,利用共轭正交复滤波器的参数化算式进行参数优化使目标函数极小,得到紧支、对称、准正交的滤波器及其小波.进而分析了准正交小波的数学特性,尤其是正交性;通过与诸多常用小波的比较,表明本文的准正交小波具有很好的性能.     

Acoustic behavior design with simulated annealing

The present work extends the matrix method formalism, by using a supplementary computational method based on a simulated annealing algorithm, with the aim to design acoustical structures, especially acoustic filters. The algorithm introduces a cost function, which is minimized by the simulated annealing algorithm. Also, some numerical computations have been carried out to design some special acoustic filters and an experimental analysis of the designed acoustic filters is provided to test the validity of the method.     

Deformation-Space Method for the Design of Biplanar Transverse Gradient Coils in Open MRI Systems

We propose an efficient real-space algorithm for the design of biplanar transverse gradient coils for use in open magnetic resonance imaging (MRI) systems. In our method, each wire arc is represented by a closed contour (LimaÇon). Using parametric equations, we deform/reshape an ensemble of closed contours in a simple manner, controllable by just a few parameters. These parameters are used to define system rearrangements in the design procedure. We use an iterative optimization procedure to adjust the control parameters in order to minimize cost functions such as gradient homogeneity and inductance. Here, we comapare the coil pattern designed by our deformation-space method with a pattern designed by the conventional stream function approach, and we discuss the merit of the new method.      

二元正交小波滤波器的构造

本文提出了一种基于余弦函数的二元紧支撑正交小波滤波器的构造方法。这种构造方法简单易行,能够通过选取不同的参数而设计出不同的小波滤波器。最后,给出了算例。     

Signal matching wavelet for ultrasonic flaw detection in high background noise

The wavelet transform (WT) is widely used in ultrasonic flaw detection (UFD) systems because of its property of multiresolution time-frequency analysis. Those traditional WT-based methods for UFD use a wavelet basis with limited types to match various echo signals (called wavelet matching signals), so it is difficult for those methods to achieve the optimal match between echo signal and wavelet basis. This results in limited detection ability in high background noise for those WT-based methods. In this paper, we propose a signal matching wavelet (SMW) method for UFD to solve this problem. Unlike traditional UFD systems, in the proposed SMW, the transmitted signal is designed to be a wavelet function for matching a wavelet basis. This makes it possible to obtain the optimal match between the echo signal and the wavelet basis. To achieve the optimal match from the aspect of energy, we derive three rules for designing the transmitted signal and selecting the wavelet basis. Further, the parameter selection in applying the proposed SMW method to a practical UFD system is analyzed. In addition, a low-rate discrete WT structure is designed to decrease the hardware cost, which facilitates the practical application of the proposed SMW. The simulation results show that the proposed SMW can efficiently detect flaws in high background noise even with SNR lower than -20 dB, outperforming the existing methods by 5 dB.     

Min–max dynamic response optimization of mechanical systems using approximate augmented Lagrangian

A globally convergent and efficient algorithm for min–max dynamic response optimization using the ALM method is presented. This algorithm employs an approximate augmented Lagrangian for line searches, and an exact augmented Lagrangian for finding search directions. This approximate augmented Lagrangian is composed of the linearized cost and constraint functions projected on the search direction. It is noted that an approximate penalty term has the same approximate Hessian as that of the Gauss–Newton method. This makes the approximate augmented Lagrangian to have almost second-order accuracy near the optimum. In the unconstrained optimization process of the proposed method, some modifications are also suggested to remove the possible distortion of optimization trajectory when the side constraints on design variables are separately handled. Also, the efficiencies of two treatments for handling a max-value cost function are discussed in the context of the proposed method. The numerical performance of the proposed method is investigated by solving three min–max dynamic response optimization problems and comparing the results with those in the literature. This comparison shows that the suggested algorithm is more efficient than those in the literature. Especially, it is found that the direct treatment for a max-value cost function is more efficient than the transformation treatment for all the design cases. © 1998 John Wiley & Sons, Ltd.     

一种强噪声背景下的微弱信号检测的新方法

基于自适应滤波算法对小波滤波器的构造方法进行了研究,重点在于解决对强噪声环境下微弱信号提取所需要的小波变换的子带自适应滤波器的构造,把小波变换技术和自适应滤波技术应用于微弱信号的检测。提出基于自适应小波变换的心电信号的检测,利用小波变换的子带编码理论,通过在多个子带权值的自适应匹配,回复后拟合微弱信号。仿真结果表明,该方法可进一步改善信号的检测能力,在检测微弱信号的特征和改善信噪比方面是一种十分有效的方法。     

基于钢丝绳传动的自动抹灰机的轻量化设计

针对上一代自动抹灰机“头重脚轻”的问题,基于轻量化设计的理念,设计了一种基于钢丝绳传动的自动抹灰机。该装置主要分为横纵移模块、小车模块和喷涂模块,通过一根封闭的钢丝绳的传动快速高效地完成整个墙面的抹灰工作。对自动抹灰机中的主要承载件——钢丝绳进行了受力分析和计算,计算结果表明,所选择的6*7+IWS钢丝绳符合工况要求。对自动抹灰机的作业成本进行分析并与人工抹灰成本进行比较,表明自动抹灰机作业成本较低,具有良好的市场前景。轻量化的自动抹灰机工作性能好,工作效率高,环保性强,在现代建筑施工中具有很高的应用和推广价值。     

一种非一致小波基的超光谱图像压缩方法

传统的三维小波变换在不同维采用相同的小波基且频谱分辨能力也是相同的,这不能与超光谱图像的特性相匹配.本文提出了一种新的采用非一致小波基的去偶结构的三维小波变换的超光谱压缩方法.由于超光谱图像光谱维和空间维具有明显不同的特性而设计的,本文采用一种非一致小波基设计思路,对不同维使用不同的小波基并与去偶的小波变换结构结合在一起进行小波变换.为了获得符合不同维特性的最优的小波基组,本文通过评估指标来测试各种小波基组合的性能.实验结果表明,本文提出的方法能够明显提高超光谱图像的压缩比,且不需牺牲计算复杂度、可扩展性等额外代价.     

Optimized damage detection of steel plates from noisy impact test

Model‐based non‐destructive evaluation proceeds measuring the response after an excitation on an accessible area of the structure. The basis for processing this information has been established in recent years as an iterative scheme that minimizes the discrepancy between this experimental measurement and sequence of measurement trials predicted by a numerical model. The unknown damage that minimizes this discrepancy by means of a cost functional is to be found. The damage location and size is quantified and sought by means of a well‐conditioned parametrization. The design of the magnitude to measure, its filtering for reducing noise effects and calibration, as well as the design of the cost functional and parametrization, determines the robustness of the search to combat noise and other uncertainty factors. These are key open issues to improve the sensitivity and identifiability during the information processing. Among them, a filter for the cost functional is proposed in this study for maximal sensitivity to the damage detection of steel plate under the impact loading. This filter is designed by means of a wavelet decomposition together with a selection of the measuring points, and the optimization criterion is built on an estimate of the probability of detection, using genetic algorithms. Numerical examples show that the use of the optimal filter allows to find damage of a magnitude several times smaller. Copyright © 2006 John Wiley & Sons, Ltd.     

Denoising infrared maritime imagery using tailored dictionaries via modified K-SVD algorithm

Recent work has shown that tailored overcomplete dictionaries can provide a better image model than standard basis functions for a variety of image processing tasks. Here we propose a modified K-SVD dictionary learning algorithm designed to maintain the advantages of the original approach but with a focus on improved convergence. We then use the learned model to denoise infrared maritime imagery and compare the performance to the original K-SVD algorithm, several overcomplete "fixed" dictionaries, and a standard wavelet denoising algorithm. Results indicate the superiority of overcomplete representations and show that our tailored approach provides similar peak signal-to-noise ratios as the traditional K-SVD at roughly half the computational cost.     

Improved global convergence probability using multiple independent optimizations

For some problems global optimization algorithms may have a significant probability of not converging to the global optimum or require an extremely large number of function evaluations to reach it. For such problems, the probability of finding the global optimum may be improved by performing multiple independent short searches rather than using the entire available budget of function evaluations on a single long search. The main difficulty in adopting such a strategy is to decide how many searches to carry out for a given function evaluation budget. The basic premise of this paper is that different searches may have substantially different outcomes, but they all start with rapid initial improvement of the objective function followed by much slower progress later on. Furthermore, we assume that the number of function evaluations to the end of the initial stage of rapid progress does not change drastically from one search to another for a given problem and algorithmic setting. Therefore we propose that the number of function evaluations required for this rapid‐progress stage be estimated with one or two runs, and then the same number of function evaluations be allocated to all subsequent searches. We show that these assumptions work well for the particle swarm optimization algorithm applied to a set of difficult analytical test problems with known global solutions. For these problems we show that the proposed strategy can substantially improve the probability of obtaining the global optimum for a given budget of function evaluations. We also test a Bayesian criterion for estimating the probability of having reached the global optimum at the end of the series of searches and find that it can provide a conservative estimate for most problems. Finally, we demonstrate the approach on a particularly challenging engineering design problem constructed so as to have at least 32 widely separated local optima. Copyright © 2006 John Wiley & Sons, Ltd.     

Rigorous electromagnetic design of finite-aperture diffractive optical elements by use of an iterative optimization algorithm

We propose a rigorous electromagnetic design of two-dimensional and finite-aperture diffractive optical elements (DOEs) that employs an effective iterative optimization algorithm in conjunction with a rigorous electromagnetic computational model: the finite-difference time-domain method. The iterative optimization process, the finite-difference time-domain method, and the angular spectrum propagation method are discussed in detail. Without any approximation based on the scalar theory, the algorithm can produce rigorous design results, both numerical and graphical, with fast convergence, reasonable computational cost, and good design quality. Using our iterative algorithm, we designed a diffractive cylindrical lens and a 1-to-2-beam fanner for normal-incidence TE-mode illumination, thus showing that the optimization algorithm is valid and competent for rigorously designing diffractive optical elements. Concerning the problem of fabrication, we also evaluated the performance of the DOE when the DOE profile is discrete.     

Texture Analysis for Flaw Detection in Ultrasonic Images

In this paper, we present two approaches for flaw detection in TOFD (Time of Flight Diffraction) images based on texture features. Texture is one of the most important features used in recognizing patterns in an image. The paper describes texture features by two methods: Multiresolution analysis such as wavelet transforms and Gabor filters bank. The two-dimensional wavelet transform is used to decompose the input image into a multiresolution framework. The textural statistical parameters are used to allow the choice of the decomposition channel. The Gabor filter is a Gaussian kernel function modulated by a sinusoidal plane wave. All Gabor filters can be generated from one mother wavelet by dilation and rotation. These filters represent an appropriate choice for tasks requiring simultaneous measurement in both space and frequency domains. The most relevant features are optimized by Principal Components Analysis (PCA) and used as input data on a Fuzzy C-Mean clustering classifier. We use two classes: ‘defects’ or ‘no defects’. The proposed approach is tested on the TOFD image achieved in an industrial field.     

Repeat inspection planning using dynamic programming

In this paper we propose a dynamic programming approach to the problem of determination of the inspection sequence of multi-characteristic critical components, and the number of repeat inspection for each characteristic. The model presented here considers the case of several classification of a product by an inspector. An inspector could classify a product as non-defective, to be reworked, or to be scrapped, with respect to a certain characteristic. The model accounts as well for possible misclassification by the inspector. The dynamic programming algorithm searches for a solution that minimizes the total cost of inspection per accepted component. The total cost includes the cost of false rejection of good items, the cost due to false acceptance of an item which is either reworkable or to be scrapped, the cost of inspection, and the cost of rework.     

An effective approach for wavelet lifting based on filter optimization and median operator

In JPEG2000, the Cohen–Daubechies–Feauveau (CDF) 9/7‐tap wavelet filter implemented by using the conventional lifting scheme has two problems. The first problem is that the filter coefficients are remaining complex; second, the conventional lifting scheme ignores image edges in the coding process. In this article, we propose an effective wavelet lifting scheme to solve these problems. For this purpose, we design the optimal 9/7‐tap wavelet filters in two steps. In the first step, we select the appropriate filter coefficients; in the second step, we employ a median operator to consider image edges. Experimental results from using the median lifting scheme and combining filter optimization and median lifting show that our proposed methods outperform the well‐known CDF 9/7‐tap wavelet filter of JPEG2000 on edge‐dominant images. © 2010 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 20, 359–366, 2010     

Enlarging the depth of focus by filtering in the phase-space domain

The ambiguity function was employed as a merit function to design an optical system with a high depth of focus. The ambiguity function with the desired enlarged-depth-of-focus characteristics was obtained by using a properly designed joint filter to modify the ambiguity function of the original pupil in the phase-space domain. From the viewpoint of the filter theory, we roughly propose that the constraints of the spatial filters that are used to enlarge the focal depth must be satisfied. These constraints coincide with those that appeared in the previous literature on this topic. Following our design procedure, several sets of apodizers were synthesized, and their performances in the defocused imagery were compared with each other and with other previous designs.     

Mammographic Images Enhancement and Denoising for Breast Cancer Detection Using Dyadic Wavelet Processing

Mammography is the most effective method for the early detection of breast diseases. However, the typical diagnostic signs such as microcalcifications and masses are difficult to detect because mammograms are low-contrast and noisy images. In this paper, a novel algorithm for image denoising and enhancement based on dyadic wavelet processing is proposed. The denoising phase is based on a local iterative noise variance estimation. Moreover, in the case of microcalcifications, we propose an adaptive tuning of enhancement degree at different wavelet scales, whereas in the case of mass detection, we developed a new segmentation method combining dyadic wavelet information with mathematical morphology. The innovative approach consists of using the same algorithmic core for processing images to detect both microcalcifications and masses. The proposed algorithm has been tested on a large number of clinical images, comparing the results with those obtained by several other algorithms proposed in the literature through both analytical indexes and the opinions of radiologists. Through preliminary tests, the method seems to meaningfully improve the diagnosis in the early breast cancer detection with respect to other approaches.     

Multiresolution correlator analysis and filter design

The concept of multiresolution optical correlators is formally introduced. A mathematical analysis is performed for a generalized multiresolution correlator that emphasizes the roles of both input and filter spatial light modulator resolutions. Conditions are derived for overlapping and nonoverlapping correlation orders. A simulation is performed in which it is shown that the predicted performance of composite binary-phase-only filters designed by the conventional design procedure is different from the actual performance when they are implemented in a real optical correlator. The training of filters on multiresolution approximations of high-resolution discrete Fourier transforms generated by multiresolution wavelet analysis (MWA) techniques is proposed. An analysis is performed that shows that training on MWA approximations results in filters whose performance is the same in a real correlator as that predicted by the design procedure. This analysis is confirmed by simulation. Further simulations show that the performance of reduced-resolution filters designed by MWA techniques is markedly superior to the performance of those designed by conventional means. Finally, an analysis is performed that explains why the ratio of zero- to higher-order correlation peak intensities is much greater for the former than the latter.