A moment-based approach to registration of images with affinegeometric distortion

A new method is described for automatic control point selection and matching. First, reference and sensed images are segmented and closed-boundary regions are extracted. Each region is represented by a set of affine-invariant moment-based features. Correspondence between the regions is then established by a two-stage matching algorithm that works both in the feature space and in the image space. Centers of gravity of corresponding regions are used as control points. A practical use of the proposed method is demonstrated by registration of SPOT and Landsat TM images. It is shown that the authors' method can produce subpixel registration accuracy     

Detection of composite edges

The paper presents a new parametric model-based approach to high-precision composite edge detection using orthogonal Zernike moment-based operators. It deals with two types of composite edges: (a) generalized step and (b) pulse/staircase edges. A 2-D generalized step edge is modeled in terms of five parameters: two gradients on two sides of the edge, the distance from the center of the candidate pixel, the orientation of the edge and the step size at the location of the edge. A 2-D pulse/staircase edge is modeled in terms of two steps located at two positions within the mask, and the edge orientation. A pulse edge is formed if the steps are of opposite polarities whereas a staircase edge results from two steps having the same polarity. Two complex and two real Zernike moment-based masks are designed to determine parameters of both the 2-D edge models. For a given edge model, estimated parameter values at a point are used to detect the presence or absence of that type of edge. Extensive noise analysis is performed to demonstrate the robustness of the proposed operators. Experimental results with intensity and range images are included to demonstrate the efficacy of the proposed edge detection technique as well as to compare its performance with the geometric moment-based step edge detection technique and Canny's (1986) edge detector.     

Adaptive TDOA estimation in presence of impulsive noise

A fractional lower-order, moment-based adaptive algorithm for estimating the time difference of arrival between signals received at two spatially separated sensors in the presence of impulsive noise modelled as a stable process is proposed. The method is computationally efficient and is a generalisation of the simplified explicit time delay estimator. Convergence of the algorithm is analysed and simulation results are included to evaluate its estimation performance for both static and nonstationary delays     

一种掩模与硅片的底面自动对准方法

硅片对准标记中心位置的求解是掩模与硅片底面自动对准的重要环节.对于对称标记图像,提出了基于矩的中心位置求解方法;对于非对称标记图像,采用Hough变换和聚类分析的方法求解标记中心位置.在此基础上,提出了掩模与硅片底面自动对准的方法.仿真实验证明了该对准方法的有效性.     

Analytic termination metrics for pin-to-pin lossy transmissionlines with nonlinear drivers

A significant percentage of the critical nets in high-performance systems are of the pin-to-pin type. To optimally design these nets such that signal integrity is preserved, efficient analytical metrics for transmission line termination are a valuable part of a system-level designer's toolset. Using the symbolic moment-based expressions in this paper, proper termination can be determined via a single-step procedure, without any preprocessing steps and/or time-domain simulations. Driver nonlinearities and effects of nonzero rise-time are also considered in the proposed termination methodology     

Estimators Using Noisy Channel Samples for Fading Distribution Parameters

The problem of estimating parameters of two main fading distributions, Ricean and Nakagami-$m$, is considered. Unlike most previous estimators which are designed to use samples from a noiseless channel, new estimators which use noise-corrupted samples are proposed. Both maximum-likelihood designs and moment-based designs are considered. The performances of the new estimators are examined and compared with those of previous estimators derived in the literature. Numerical results show the superiority of the new estimators for operation in noisy channels.     

Blind channel estimation using the second-order statistics:algorithms

Most second-order moment-based blind channel estimators belong to two categories: (i) optimal correlation/spectral fitting techniques and (ii) eigenstructure-based techniques. These two classes of algorithms have complementary advantages and disadvantages. A new optimization criterion referred to as the joint optimization with subspace constraints (JOSC) is proposed to unify the two types of approaches. Based on this criterion, a new algorithm is developed to combine the strength of the two classes of blind channel estimators. Among a number of attractive features, the JOSC algorithm does not require the accurate detection of the channel order. When compared with existing eigenstructure-based techniques, the JOSC performs better, especially when the channel is close to being unidentifiable. When compared with correlation/spectral fitting schemes, the JOSC is less affected by the presence of local minima     

基于几何矩的抵抗RST攻击的数字图像水印

目前大多数的数字图像水印方案不能有效抵抗几何形变的攻击,这一弱点已成为数字水印技术走上商用的瓶颈。在各种几何形变中,RST(旋转、缩放、平移)是最为常见的攻击方式。该文提出了一种具有普适性的能够抵抗RST攻击的多比特数字图像水印方案,采用的主要措施有:(1)提出一种基于几何矩的图像标准化方案以抵抗几何攻击;(2)采用扩谱方法构造二维CDMA水印信号,实现多比特水印嵌入;(3)根据HVS特性自适应调整水印的嵌入强度,在鲁棒性和不可见性之间达到平衡;(4)利用MAP和相关方法估计和检测水印信号。实验表明该方案对RST具有很高的鲁棒性,对压缩、滤波等常见的图像处理攻击同样具有良好的鲁棒性。     

A moment-based unified approach to image feature detection

In this paper, a novel model-based approach is proposed for generating a set of image feature maps (or primal sketches). For each type of feature, a piecewise smooth parametric model is developed to characterize the local intensity function in an image. Projections of the intensity profile onto a set of orthogonal Zernike-moment-generating polynomials are used to estimate model-parameters and, in turn, generate the desired feature map. A small set of moment-based detectors is identified that can extract various kinds of primal sketches from intensity as well as range images. One main advantage of using parametric model-based techniques is that it is possible to extract complete information (i.e., model parameters) about the underlying image feature, which is desirable in many high-level vision tasks. Experimental results are included to demonstrate the effectiveness of proposed feature detectors.     

一种冲击噪声环境中的二维DOA估计新方法

该文提出了一种新的在冲击噪声环境中基于阵列输出信号分数低阶矩的二维测向方法稳健的协变异波达方向矩阵法。该方法利用冲击噪声和SS过程的特点,扩展了原波达方向矩阵法的信号模型和应用环境,对冲击噪声有较好的抑制作用,增强了算法的通用性和稳健性,弥补了传统的基于二阶或高阶统计量的子空间测向算法不能应用于冲击噪声环境的不足,计算机仿真验证了该算法的可行性和有效性。     

A CAD-suitable approach for the analysis of nonuniform MMIC andMHMIC transmission lines

A new method of moment-based formulation for the solution of the telegraphist's equations in nonuniform transmission lines is presented. Entire domain basis functions that build in a frequency variation are used to cover wider frequency and physical dimension ranges. The results obtained using the proposed formulation are validated by comparison to those obtained by a CAD package and to measured data. Different nonuniform lines in microstrip and coplanar technologies on monolithic microwave/millimeter wave integrated circuit (MMIC) and miniaturized hybrid microwave integrated circuit (MHMIC) substrates are investigated with an application to the design a matched taper transition in a MMIC coplanar line     

一个高效的有向传递签名方案

传递签名是由Micali和Rivest在2002年首先提出的,主要用于对二元传递关系进行签名.已有的传递签名方案都是无向的,只适用于对等价关系签名,提出有向传递签名方案是个留待解决的公开问题.该文提出一个高效的全序有向传递签名方案,并证明该方案在选择明文攻击下是安全的.在方案中,签名的β_uv部分被限定在0和q/2之间,以防止敌手由(u,v)的签名伪造(v,u)的签名,从而保证签名的有向性.将该方案与无向传递签名方案结合,提出一个可对任何有向二元传递关系进行签名的方案.     

On the orientability of shapes.

The orientation of a shape is a useful quantity, and has been shown to affect performance of object recognition in the human visual system. Shape orientation has also been used in computer vision to provide a properly oriented frame of reference, which can aid recognition. However, for certain shapes, the standard moment-based method of orientation estimation fails. We introduce as a new shape feature shape orientability, which defines the degree to which a shape has distinct (but not necessarily unique) orientation. A new method is described for measuring shape orientability, and has several desirable properties. In particular, unlike the standard moment-based measure of elongation, it is able to differentiate between the varying levels of orientability of n-fold rotationally symmetric shapes. Moreover, the new orientability measure is simple and efficient to compute (for an n-gon we describe an O(n) algorithm).     

A moment-based blind method for identification of FIR down-linkDS-CDMA channels

In order to achieve lower bit error rates (BERs), multiuser detection techniques have been proposed. Generally, multiuser detectors can provide excellent performance only when channel parameters are precisely known. In this paper, we propose a moment-based blind method to estimate down-link channels precisely. The mean square error (MSE) expression of the channel vector estimate has been derived. Through simulations, we show the effect of the channel estimation error on the performance of a multiuser detector. In this paper, we also show that finite impulse response (FIR) channels can be blindly identified by using the proposed method and the spreading operation. Since the spreading operation of the code division multiple access (CDMA) can induce cyclostationarity, any FIR channel can be identified by the proposed method. Of course, in order to guarantee identifiability, some conditions on the spreading codes will be satisfied. In this paper, these conditions are also found     

A moment-based three-dimensional edge operator

A three-dimensional edge operator for detecting anatomical structures in medical imaging is presented. It uses the spatial moments of the gray-level surface, and operates in three dimensions with any window size. It allows the location and the contrast surface, as well as the surface orientation, to be estimated. The computation of the discrete version is reported. Bias and errors due to the spatial sampling and noise are analyzed at both a theoretical and experimental level. The moment-based operator is compared with other well-known edge operators using simple shaped primitives for which the analytical solution is known. The 3-D rendering of real data is then provided by merging the operator in a ray-tracing framework     

Robust photometric invariant features from the color tensor.

Luminance-based features are widely used as low-level input for computer vision applications, even when color data is available. The extension of feature detection to the color domain prevents information loss due to isoluminance and allows us to exploit the photometric information. To fully exploit the extra information in the color data, the vector nature of color data has to be taken into account and a sound framework is needed to combine feature and photometric invariance theory. In this paper, we focus on the structure tensor, or color tensor, which adequately handles the vector nature of color images. Further, we combine the features based on the color tensor with photometric invariant derivatives to arrive at photometric invariant features. We circumvent the drawback of unstable photometric invariants by deriving an uncertainty measure to accompany the photometric invariant derivatives. The uncertainty is incorporated in the color tensor, hereby allowing the computation of robust photometric invariant features. The combination of the photometric invariance theory and tensor-based features allows for detection of a variety of features such as photometric invariant edges, corners, optical flow, and curvature. The proposed features are tested for noise characteristics and robustness to photometric changes. Experiments show that the proposed features are robust to scene incidental events and that the proposed uncertainty measure improves the applicability of full invariants.     

A Simplified Control Method for the Grid-Connected Inverter With the Function of Islanding Detection

In this paper, a novel method for the voltage-controlled grid-connected inverter with the function of islanding detection is proposed for the distribution power generation system. The salient features of the proposed voltage-controlled grid-connected inverter are simple control circuit and fast transient response. Besides, an islanding detection method is proposed and incorporated into the controller of a voltage-controlled grid-connected inverter. The proposed islanding detection method will cause variation in amplitude and frequency of the load voltage when the utility is interrupted so as to immediately detect the islanding operation. A prototype is developed and tested to demonstrate the performance of the proposed voltage-controlled grid-connected inverter. The experimental results show that the performance of the proposed voltage-controlled grid-connected inverter is as expected.      

Thresholding based on histogram approximation

The authors propose two automatic threshold-selection schemes, based on functional approximation of the histogram. The first method is based on minimising the sum of square errors, and the second one is based on minimising the variance of the approximated histogram. Experimental results show that, on average, the latter scheme gives better results than the former one, at a small extra computational cost. A `goodness' measure is proposed to measure the effectiveness of the two schemes, and to compare them against the entropy-based approach and the moment-based approach     

在离子阱中实现量子SWAP门的方案

提出了一个利用处在线性阱中的两个全同的三能级离子与两个不同频率的激光脉冲共振相互作用来实现两比特量子SWAP门的方案,该方案是根据Haffner H.和 Riebe M等人的实验方法与结果选择 离子的 基态的一个塞曼能级作为基态,以亚稳态 的两个塞曼能级作为两个激发态来实现的,选择适当的参数如质心模的频率 ,拉比频率 以及Lamb-Dicke参数 ,计算出实现该方案所用的总时间为 ,该时间远小于亚稳态 的寿命 ,并且在这个方案里消相干是可以被忽略的。在目前的离子阱技术条件下,该方案是可以实现的。