A simple algorithm for detection of significant vertices for polygonal approximation of chain-coded curves

A simple but efficient method is proposed for detection of significant points of chain-coded curves. The polygonal approximation is achieved by joining successive significant vertices. The algorithm is based on manipulation with chain codes only.     

A new measurement for assessing polygonal approximation of curves

This paper presents a novel method for assessing the accuracy of unsupervised polygonal approximation algorithms. This measurement relies on a polygonal approximation called the “reference approximation”. The reference approximation is obtained using the method of Perez and Vidal [11] by an iterative method that optimizes an objective function. Then, the proposed measurement is calculated by comparing the reference approximation with the approximation to be evaluated, taking into account the similarity between the polygonal approximation and the original contour, and penalizing polygonal approximations with an excessive number of points. A comparative experiment by using polygonal approximations obtained with commonly used algorithms showed that the proposed measurement is more efficient than other proposed measurements at comparing polygonal approximations with different number of points.     

An algorithm for detection of dominant points and polygonal approximation of digitized curves

A new technique for the detection of dominant points and polygonal approximation of digitized curves is proposed. The procedure needs no input parameter and remains reliable even when features of multiple size are present. Unlike the existing algorithms, the present technique introduces the concept of an asymmetric region of support and k-l-cosine. The dominant points are the local maxima of k-l-cosine. The polygon is obtained joining the dominant points successively.     

Genetic particle swarm optimization for polygonal approximation of digital curves

Polygonal approximation is an important technique in image representation which directly impacts on the accuracy and efficacy of the subsequent image analysis tasks. This paper presents a new polygonal approximation approach based on particle swarm optimization (PSO). The original PSO is customized to continuous function value optimization. To facilitate the applicability of PSO to combinatorial optimization involving the problem in question, genetic reproduction mechanisms, namely crossover and mutation, are incorporated into PSO. We also propose a hybrid strategy embedding a segment-adjusting-and-merging optimizer into the genetic PSO evolutionary iterations to enhance its performance. The experimental results show that the proposed genetic PSO significantly improves the search efficacy of PSO for the polygonal approximation problem, and the hybrid strategy can accelerate the convergence speed but still with good-quality results. The performance of the proposed method is compared to existing approaches on both synthesized and real image curves. It is shown that the proposed hybrid genetic PSO outperforms the polygonal approximation approaches based on genetic algorithms and ant colony algorithms. The text was submitted by the author in English. Peng-Yeng Yin was born in 1966 and received his B.S., M.S. and Ph.D. degrees in Computer Science from National Chiao Tung University, Hsinchu, Taiwan, in 1989, 1991 and 1994, respectively. From 1993 to 1994, he was a visiting scholar at the Department of Electrical Engineering, University of Maryland, and the Department of Radiology, Georgetown University. In 2000, he was a visiting Associate Professor in the Visualization and Intelligent Systems Lab (VISLab) at the Department of Electrical Engineering, University of California, Riverside (UCR). He is currently a Professor at the Department of Information Management, National Chi Nan University, Nantou, Taiwan. His current research interests include image processing, pattern recognition, machine learning, computational biology, and evolutionary computation. He has published more than 70 articles in refereed journals and conferences. Dr. Yin received the Overseas Research Fellowship from the Ministry of Education in 1993 and Overseas Research Fellowship from the National Science Council in 2000. He is a member of the Phi Tau Phi Scholastic Honor Society and listed in Who’s Who in the World.     

一种轮廓曲线的多边形近似算法

首先基于相邻像素间的欧氏距离计算出轮廓曲线上每一点的支持区域及支持半径,用线性插值得到支持区域的端点;然后求得支持区域的质心,以曲线上的点和其相应的支持区域质心之间的距离作为特征响应筛选出候选特征点;最后将具有局部极大特征强度的点作为多边形的顶点。实验表明这种方法能降低曲线数字化所带来的影响,对旋转也具有较高的不变性。     

一种GIS拓扑多边形链搜索的改进算法

针对GIS拓扑多边形链搜索中悬挂弧段的处理问题,提出了一种改进算法。该算法利用在一趟搜索中,非悬挂弧段仅经过一次,而悬挂弧段会经过两次这一规律来识别并标记悬挂弧段;在进行多边形链搜索时,通过避让悬挂弧段以避免将其对应的关联弧段加入多边形链,从而保证搜索结果的正确性。测试结果表明,该算法能明显提高多边形链搜索的效率。     

Reconstruction of B-spline surface by interpolating boundary curves and approximating inner points

In this paper,we present an algorithm for reconstruction of B-spline surface such that it interpolates the four given boundary curves and simultaneously approximates some given inner points.The main idea of our method is:first,we construct an initial surface which interpolates the four given boundary curves;then,while keeping the boundary control points of the initial surface unchanged,we reposition the inner control points of the surface with energy optimization method.Examples show that our algorithm is practicable and effective.     

基于多边形近似的图像纹理全局特性研究

使用传统的MRF模型进行纹理合成时存在无法把握纹理全局特性的缺陷,对具有大规模结构特性的纹理进行合成时,容易造成纹元周期性混乱。将特征匹配的方法引入传统MRF模型中可改良图像合成效果。详细分析了特征点识别与定位对整个纹理合成的作用。首次提出了一种用基于二进制具有量子行为的粒子群算法的多边形近似来分析纹理图像中特征点分布的结构模式分析方法。该方法可以提取结构性及半结构性半随机性纹理中的特征点分布规律,采用对特征点分级的方法定位纹理的大规模乃至全局特性。     

具有轮盘反转算子的多Agent算法用于线性系统逼近

针对John Holland的反转算子在数值优化中的不合理性, 提出了一种轮盘反转算子来克服这种不合理性,并结合该算子提出了一种多Agent进化算(RAER), 证明了算法的全局收敛性. 无约束优化仿真实验表明, 该算法性能好于其他算法. 在求解线性系统逼近工程优化问题时, 无论在固定区域还是动态扩展区域搜索, 算法都能得到更好的模型, 较其他算法能够对搜索区域进行更为充分的探索和求精. RAER算法是实际有效的.     

源于业务的CIM模型实现通用方法框架

在电力行业,IEC61970/61968 CIM因为可以解决信息孤岛问题而成为当前电力企业进行信息交互的标准并被广泛使用。众所周知IEC CIM模型是一个比较庞大的体系,在应用中都是采取相应范围的裁剪和按照需求进行相应的扩充,我们称之为定制化。由于各个人或厂商对于CIM模型的理解不一致,在裁剪或扩充的时候难免出现诸如实用性、与前版本的一致性和可扩充性等的差异问题。特别是在实践中发现在支持接入不同时期、由不同厂商开发的正在运行的应用系统基于CIM标准的实例化有各自的方式和方法,所以电力企业将面临着不同应用系统采用不同CIM标准版本进行的实例化情况,非常难以管理。为了解决同一个CIM模型标准落地存在差异的问题,介绍一种通过实践融合了业务建模方法（BPMN 2.0）、智能电网系统的需求开发方法论（IEC62559）和IEC通用方法框架CMF的方法框架,从方法论的角度约束或指导CIM模型落地。     

Moment-based methods for polygonal approximation of digitized curves

Object shape representation plays an important role in the area of image processing, pattern recognition and computer vision. In the past two decades, many algorithms have been suggested for creating approximated polygons. In this study, two new polygonal approximation methods based on the geometric moments and the orthogonal moments defined in terms of Legendre polynomials are proposed. The difference between the moments defined by the initial contour and those of the approximated polygon is taken as the objective function. Each algorithm provides various polygonal approximation results with different number of line segments for different application situations. For a given error bound, we can determine the optimal polygon with a minimum number of line segments. The procedures are applied to some digital curves and better results are obtained in comparison with some known methods.     

Fast polygonal approximation of digitized curves

We describe a new technique for fast “scan-along” computation of piecewise linear approximations of digital curves in 2-space. Our method is derived from earlier work on the theory of minimum-perimeter polygonal approximations of digitized closed curves.We demonstrate the specialization of this technique to the case where the error is measured as the largest Hausdorff-Euclidean distance between the approximation and the given digitized curve. We illustrate the application of this procedure to the boundaries of the images of a lung and a rib in chest radiographs.     

Relaxation algorithm for shape matching of two-dimensional objects

This paper describes a relaxation algorithm without a parameter for shape matching of partially occluded two-dimensional objects. This technique is based on a relaxation labelling process of Rosenfeld et al. for reducing or eliminating the ambiguity. The shapes are represented by polygonal approximation. The proposed relaxation method is used to find acceptable line segment pairs of polygons.     

一种改进的多边形近似算法

多边形近似是曲线矢量数据压缩技术中的一种,其实质是多边形信息压缩问题,目的在于减少多边形曲线数据的冗余信息,释放所占用的空间,达到高效、快速地显示图形。通过分析基于显著点删除的多边形近似算法的特性,发现基于显著点删除算法由于没有考虑多边形与多边形之间的联系以及多边形中特殊点的问题,以至于在处理具有孤立点等情况时的多边形近似效果不理想。为了更好地解决上述缺陷,提出了一种改进的多边形近似算法。通过分析现有算法,发现在处理特殊孤立点、边界处裂缝、多点处于同一直线时处理效果不理想,针对这些问题,通过孤立点单独处理、边界点建立索引以及根据多边形形状忽略处于同一直线上的多点方法,对算法进行改进。同时利用数据集对改进算法性能进行分析,实验结果表明,改进的算法在多边形近似处理效率和效果上更加明显。     

流程CIM与离散CIM之比较

本文首先从物流、工艺和生产控制自动化等方面分析了流程生产的特点并与离散制造进行了比较。研究了流程ＣＩＭ的体系结构、系统构成，指出流程ＣＩＭＳ通常只包括生产实施（过程控制）与管理信息两个应用系统。过程控制在流程ＣＩＭＳ中占有特殊重要地位。集散控制系统是过程控制与信息集成的基础。     

Robust adaptive polygonal approximation of implicit curves

We present an algorithm for computing a robust adaptive polygonal approximation of an implicit curve in the plane. The approximation is adapted to the geometry of the curve because the length of the edges varies with the curvature of the curve. Robustness is achieved by combining interval arithmetic and automatic differentiation.     

基于Freeman链码的自由曲线直线逼近算法

提出一种简单而有效的直线逼近自由曲线算法.自由曲线轮廓采用Freeman链码描述,提出快速分割链码算法,得出逼近节点,从而准确地实现对曲线的逼近.此外,该方法不仅适用于直线、圆弧和非圆曲线,而且还适用于形状复杂,不能用初等解析函数直接表示的自由曲线.实验结果表明,该算法简单、快速、准确,并对自由曲线具有较好的逼近效果.     

An algorithm for polygonal approximation of a digital object

A fast and simple heuristic algorithm for polygonal approximation is presented. The algorithm is based on a mark and sweep technique. Results of computer implementation with various images are reported.