Point pattern matching by relaxation

Let $\text{P}\text{= P}{}_1\text{, …, P}{}_{\mathrm{m}}$ and $\text{Q}\text{= Q}{}_1\text{, …, Q}{}_{\mathrm{n}}$ be two patterns of points. Each pairing (P_i, Q_j) of a point of $\text{P}$ with a point of $\text{Q}$ defines a relative displacement δ_ij of the two patterns. We can define a figure of merit for δ_ij according to how closely other point pairs coincide under δ_ij. If there exists a displacement δ₀ for which $\text{P}$ and $\text{Q}$ match reasonably well, the pairings for which δ_ij ? δ₀ will have high merit scores, while other pairings will not. The scores can then be recomputed, giving weights to the other point pairs based on their own scores; and this process can be iterated. When this is done, the scores of pairs that correspond under δ₀ remain relatively high, while those of other pairs become low. Examples of this method of point pattern matching are given, and its possible advantages relative to other methods are discussed.     

Some experiments in relaxation image matching using corner features

A relaxation method based on patterns of local features is used to find matches between pairs of images or subimages that differ in position or orientation. A local operator is applied to the two images to detect two sets of “corners” C₁ …, C_m and D₁, …, D_n, each of them characterized by position, orientation, contrast and “sharpness” (of the angle). For each pair (C_i, D_j), a figure of merit is computed and a relaxation process is used to iteratively adjust these figures of merit, based on the merits of other pairs in approximately corresponding positions. After a few iterations of this process, “good” matches (pairs having much better merit than their next best choices) are clustered, yielding sets of transformation parameters (shift vectors or rotation angles) under which many corners correspond. This method has yielded good results for TV images of objects such as tools and industrial parts, as well as for aerial images of terrain.     

基于拟Laplacian谱和点对拓扑特征的点模式匹配算法

针对谱匹配方法对噪声和出格点的鲁棒性较差的问题,提出了一种基于拟Laplacian谱和点对拓扑特征的点模式匹配算法。首先,用赋权图的最小生成树构造无符号Laplacian矩阵,通过对矩阵谱分解得到的特征值和特征向量表示点的特征,进而计算点的初始匹配概率;其次,利用点对拓扑特征的相似性测度来定义点对间的局部相容性,然后借助概率松弛的方法更新由拟Laplacian谱得到的匹配概率,得出匹配结果。对比实验结果表明,该方法在处理存在噪声和出格点的点集匹配上具有较高的鲁棒性。     

Robust matching of 3D contours using iterative closest point algorithm improved by M-estimation

An extension of the iterative closest point matching by M-estimation is proposed for realization of robustness to non-overlapping data or outlying data in two sets of contour data or depth images for rigid bodies. An objective function which includes independent residual components for each of x, y and z coordinates is originally defined and proposed to evaluate the fitness, simultaneously dealing with a distribution of outlying gross noise. The proposed procedure is based on modified M-estimation iterations with bi-weighting coefficients for selecting corresponding points for optimization of estimating the transforms for matching. The transforms can be represented by ‘quaternions’ in the procedure to eliminate redundancy in representation of rotational degree of freedom by linear matrices. Optimization steps are performed by the simplex method because it does not need computation of differentiation. Some fundamental experiments utilizing real data of 2D and 3D measurement show effectiveness of the proposed method. When reasonable initial positions are given, the unique solution of position could be provided in spite of surplus point data in the objects. And then the outlying data could be filtered out from the normal ones by the proposed method.     

Spectral correspondence for point pattern matching

This paper investigates the correspondence matching of point-sets using spectral graph analysis. In particular, we are interested in the problem of how the modal analysis of point-sets can be rendered robust to contamination and drop-out. We make three contributions. First, we show how the modal structure of point-sets can be embedded within the framework of the EM algorithm. Second, we present several methods for computing the probabilities of point correspondences from the modes of the point proximity matrix. Third, we consider alternatives to the Gaussian proximity matrix. We evaluate the new method on both synthetic and real-world data. Here we show that the method can be used to compute useful correspondences even when the level of point contamination is as large as 50%. We also provide some examples on deformed point-set tracking.     

Development of fuzzy process control charts and fuzzy unnatural pattern analyses

Many problems in scientific investigation generate nonprecise data incorporating nonstatistical uncertainty. A nonprecise observation of a quantitative variable can be described by a special type of membership function defined on the set of all real numbers called a fuzzy number or a fuzzy interval. A methodology for constructing control charts is proposed when the quality characteristics are vague, uncertain, incomplete or linguistically defined. Fuzzy set theory is an inevitable tool for fuzzy control charts as well as other applications subjected to uncertainty in any form. The vagueness can be handled by transforming incomplete or nonprecise quantities to their representative scalar values such as fuzzy mode, fuzzy midrange, fuzzy median, or fuzzy average. Then crisp methods may be applied to those representative values for control chart decisions as “in control” or “out of control”. Transforming the vague data by using one of the transformation methods may result in biased decisions since the information given by the vague data is lost by the transformation. Such data needs to be investigated as fuzzy sets without transformation, and the decisions based on the vague data should not be concluded with an exact decision. A “direct fuzzy approach (DFA)” to fuzzy control charts for attributes under vague data is proposed without using any transformation method. Then, the unnatural patterns for the proposed fuzzy control charts are defined using the probabilities of fuzzy events.     

Versatile spectral methods for point set matching

This work is concerned with the problem of point set matching over features extracted from images. A novel approach to the problem is proposed which leverages different techniques from the literature. It combines a number of similarity metrics that quantify measures of correspondence between the two sets of features and introduces a non-iterative algorithm for feature matching based on spectral methods. The flexibility of the technique allows its straightforward application in a number of diverse scenarios, thus overcoming domain-specific limitations of known techniques. The proposed approach is tested in a number of heterogeneous case studies: of synthetic nature; drawn from experimental biological data; and taken from known benchmarks in computer vision.     

Inexact Bayesian point pattern matching for linear transformations

We introduce a novel Bayesian inexact point pattern matching model that assumes that a linear transformation relates the two sets of points. The matching problem is inexact due to the lack of one-to-one correspondence between the point sets and the presence of noise. The algorithm is itself inexact; we use variational Bayesian approximation to estimate the posterior distributions in the face of a problematic evidence term. The method turns out to be similar in structure to the iterative closest point algorithm.     

A fast expected time algorithm for the 2-D point pattern matching problem

Point set pattern matching is an integral part of many pattern recognition problems. We study a randomized algorithm for the alignment approach to model-based recognition.Under certain mild assumptions we show that if our scene is a set of n points and our model is a set of m<n points our algorithm has expected running time for finding an occurrence of the model in the scene. This is significantly faster than any existing algorithms in the literature. We then describe some experimental results on randomly generated data using a practical version of our algorithm. These results agree well with the theoretical analysis.     

Graph matching by relaxation of fuzzy assignments

Graphs are very powerful and widely used representational tools in computer applications. We present a relaxation approach to (sub)graph matching based on a fuzzy assignment matrix. The algorithm has a computational complexity of O(n²m²) where n and m are the number of nodes in the two graphs being matched, and can perform both exact and inexact matching. To illustrate the performance of the algorithm, we summarize the results obtained for more than 12 000 pairs of graphs of varying types (weighted graphs, attributed graphs, and noisy graphs). We also compare our results with those obtained using the graduated assignment algorithm     

Simple algorithms for partial point set pattern matching under rigid motion

This paper presents simple and deterministic algorithms for partial point set pattern matching in 2D. Given a set P of n points, called sample set, and a query set Q of k points (n?k), the problem is to find a matching of Q with a subset of P under rigid motion. The match may be of two types: exact and approximate. If an exact matching exists, then each point in Q coincides with the corresponding point in P under some translation and/or rotation. For an approximate match, some translation and/or rotation may be allowed such that each point in Q lies in a predefined ε-neighborhood region around some point in P. The proposed algorithm for the exact matching needs O(n²) space and preprocessing time. The existence of a match for a given query set Q can be checked in time in the worst-case, where α is the maximum number of equidistant pairs of point in P. For a set of n points, α may be O(n^4/3) in the worst-case. Some applications of the partial point set pattern matching are then illustrated. Experimental results on random point sets and some fingerprint databases show that, in practice, the computation time is much smaller than the worst-case requirement. The algorithm is then extended for checking the exact match of a set of k line segments in the query set with a k-subset of n line segments in the sample set under rigid motion in time. Next, a simple version of the approximate matching problem is studied where one point of Q exactly matches with a point of P, and each of the other points of Q lie in the ε-neighborhood of some point of P. The worst-case time and space complexities of the proposed algorithm are and O(n), respectively. The proposed algorithms will find many applications to fingerprint matching, image registration, and object recognition.     

Interactive image enhancement by fuzzy relaxation

In this paper,an interactive image enhancement(IIE)technique based on fuzzy relaxation is presented,which allows the user to select different intensity levels for enhancement and intermit the enhancement process according to his/her preference in applications.First,based on an analysis of the convergence of a fuzzy relaxation algorithm for image contrast enhancement,an improved version of this algorithm,which is called FuzzIIE Method 1,is suggested by deriving a relationship between the convergence regions and the parameters in the transformations defined in the algorithm.Then a method called FuzzIIE Method 2 is introduced by using a different fuzzy relaxation function,in which there is no need to re-select the parameter values for interactive image enhancement. Experimental results are presented demonstrating the enhancement capabilities of the proposed methods under different conditions.     

太阳能电动车最大功率点跟踪模糊控制器设计

采用模糊控制进行太阳能电动车最大功率点的跟踪,根据太阳能电动车能量控制系统的要求,为提高系统的稳态性和鲁棒性设计了适合于太阳能电动车的带修正因子自调整MPPT模糊控制器,在变化的外界环境下,应用Matlab/Simulink仿真软件包对MPPT模糊控制器控制的能源系统进行了仿真研究,结果表明该控制器对环境的变化有较强的自适应能力,具有优越的控制性能,为太阳能电动车的应用提供了参考。     

Automatic seal identification by using point matching and fake detection

An automatic seal identification algorithm is proposed. The algorithm uses the point matching technique to register the seals quickly and accurately. To increase the identification rate, the fake detection algorithm is proposed to remove the over-ink areas and detect fake areas in the registered images. Experiments provide the identification ability for the proposed approach. The processing speed for identification is less than 2 seconds on Sun-4 workstation.     

模式匹配和协议分析方法的比较

入侵检测系统分析数据的方法很多,早期应用比较广泛的是模式匹配方法,目前人们普遍提倡协议分析的方法。本文在研究和比较模式匹配和协议分析的逻辑结构、分析过程的基础上,从理论上证明了协议分析的决定性优势,并提出了这两种数据分析方法将来必定结合运用的发展趋势。     

一种面向入侵检测系统的模式匹配算法的改进

分析引擎是入侵检测系统的核心部分,一个好的模式匹配算法直接决定了入侵检测系统分析引擎的效率。本文对几种经典的模式匹配算法如:BM算法,BMH算法以及BMHS算法等经典算法进行了研究和分析,比较了几种算法的优劣。最后在BMHS算法的基础上提出一种改进的算法,该算法可以有效提高入侵检测系统的检测速度。     

Fixed point theorems on fuzzy normed linear spaces

In this paper, definitions of strongly fuzzy convergent sequence, l-fuzzy weakly convergent sequence and l-fuzzy weakly compact set are given in a fuzzy normed linear space. The concepts of fuzzy normal structure, fuzzy non-expansive mapping, uniformly convex fuzzy normed linear space are introduced and fixed point theorems for fuzzy non-expansive mappings are proved.     

A new point symmetry based fuzzy genetic clustering technique for automatic evolution of clusters

In this paper a fuzzy point symmetry based genetic clustering technique (Fuzzy-VGAPS) is proposed which can automatically determine the number of clusters present in a data set as well as a good fuzzy partitioning of the data. The clusters can be of any size, shape or convexity as long as they possess the property of symmetry. Here the membership values of points to different clusters are computed using the newly proposed point symmetry based distance. A variable number of cluster centers are encoded in the chromosomes. A new fuzzy symmetry based cluster validity index, FSym-index is first proposed here and thereafter it is utilized to measure the fitness of the chromosomes. The proposed index can detect non-convex, as well as convex-non-hyperspherical partitioning with variable number of clusters. It is mathematically justified via its relationship to a well-defined hard cluster validity function: the Dunn’s index, for which the condition of uniqueness has already been established. The results of the Fuzzy-VGAPS are compared with those obtained by seven other algorithms including both fuzzy and crisp methods on four artificial and four real-life data sets. Some real-life applications of Fuzzy-VGAPS to automatically cluster the gene expression data as well as segmenting the magnetic resonance brain image with multiple sclerosis lesions are also demonstrated.     

Assessment of micro turning machine stiffness response and material characteristics by fuzzy rule based pattern matching of cutting force plots

In micro-nano systems technology (MNST), application of mechanical based machining operations such as micro turning, micro milling, micro EDM have shown promising trends to produce micro parts in batch scale. In order to ensure reproducibility better understanding on micro cutting process dynamics and sensitivity of machine stiffness and material characteristics becomes critical. In this paper, a methodology has been developed to assess machine stiffness and material dependent characteristics and demonstrated for micro turning operations conducted on DT-110 micro machining center. In this method, authors incorporate pattern matching algorithm to compare run data image of cutting force plots with that of reference plot. The reference plots of cutting forces v/s time were drawn from simulation run data computed from the micro turning process models. The run data plots of cutting force v/s time were drawn from the processed signal data obtained from the dynamometer during machining operation. The plots were fragmented into patterns and Euclidean distance computed between pair patterns of reference and measured cutting forces v/s time plot image represents the changes happened in machining conditions. This has been used to perform backward calculation to assess the machine stiffness response and material characteristic constants variations over machining time. In order to perform these comparative pattern error adjustments between reference and measured cutting force plots a fuzzy rule based algorithm has been developed.