针对铺丝轨迹规划设计的复杂数模缺陷修补技术

为了使铺丝轨迹设计软件具有更强的适应性,提出针对破损数模进行破损区域的网格重塑技术.首先通过对比三点定面和曲率定点2种切片环取点方法,提出采用曲率定点的方法确定切片环离散点;然后根据插入的离散点和破损区域周边网格边实现破损区域的修补,再光顺破损区域并确定切片环离散点;最后提出法向量的光顺算法,以保证切片环上离散点法向量的精度,获取完整的切片环信息.通过光学球面对比基于完整数模和破损数模的切片环分布情况,分析破损处的离散点及其法向量的误差,并进行实际的铺放实验,验证了文中算法的可行性和正确性.     

基于离散曲率的点云光顺算法

通过对三维激光扫描仪扫描测量数据的误差来源进行分析,设计了一种基于离散曲率的点云光顺处理的快速算法,该算法以曲率特征为索引,能够快速判别点云数据的特征点,对非特征点采用[w]邻域内[X,Y]两个方向拟合三次B样条曲线做光顺处理。最后通过实例证明了所提方法的有效性。     

一种参数三次样条曲线光顺优化算法

论文给出了一种基于修改因子和修改角度的平面参数三次样条曲线的优化 光顺算法,该算法通过求解一个带有修改因子 和修改角度 的目标函数得到光顺后的型值 点,插值光顺后的型值点得到光顺曲线。目的是使曲线的曲率变化均匀的同时,使光顺后的 曲线与原曲线的偏差尽量小,此算法简单易行,计算量较小。     

基于法矢控制的B样条曲面逼近的PIA方法

提出了一种基于法矢控制的 B 样条曲面逼近的渐进迭代逼近(PIA)算法。一方面该方法将离散数据点的切失、曲率、法矢等几何特征充分应用到离散数据点的逼近问题上,利用数据点两个方向的切矢构造出数据点的法矢约束来控制逼近曲面形状,相比于无法矢控制的 B 样条曲面逼近的渐进迭代逼近(PIA)方法,逼近曲面更光顺,可获得更好的逼近效果。另一方面由于该算法选取主特征点作为控制顶点,所以允许在曲面拟合中控制顶点的数目小于数据点的数目。而且PIA算法的每次迭代过程中的各个步骤都是独立的,很容易被应用到并行计算上,可提高计算效率。本文还给出了一些实例来验证该算法的有效性。     

C-B样条曲线的光顺逼近算法研究

基于弹性均匀细梁的应力能和扰动能的光顺优化,提出了一种光顺C-B样条曲线的算法。该算法的基本思想是：通过调整控制参数和控制顶点使得曲线的能量最小,得到最优的光顺逼近曲线。通过最小二乘法和非线性泛函的极小值优化计算,对平面数据点进行光顺逼近,达到了光顺的目的。最后,给出了由数据拟合的C-B样条曲线光顺的实例。实例结果表明,该算法为C-B样条曲线的光顺问题提供了一种有效的新方法。     

基于节点矢量优化的复合材料序列轮廓逼近及重构

针对采用边缘检测方法获得的复合材料第二相颗粒轮廓不规则且光顺性差的特点,利用周期非均匀三次B样条曲线逼近颗粒轮廓.将节点作为变量,提出了一种基于群体增量学习算法的节点矢量优化算法,得到预定控制点条件下误差最小的颗粒轮廓曲线;基于逼近的序列轮廓,采用柔性间距插入节点的方法定义公共节点矢量,根据公共节点矢量对序列轮廓进行相容性处理,利用三次B样条蒙皮算法生成了一张C2连续的张量积B样条曲面来描述复合材料的第二相颗粒.实验结果表明,与遗传算法相比,文中算法在轮廓逼近方面具有更好的鲁棒性和更高的精度,重构出的第二相颗粒光顺性好,效果理想.     

C-Bezier曲线的光顺逼近算法

基于弹性均匀细梁的应力能和扰动能的光顺优化,提出了一种光顺C-Bezier曲线的新方法。该方法综合考虑曲线的应力、应力能和扰动能,建立了一种新的曲线光顺准则。在新准则下通过调整控制参数α和控制顶点使得曲线的能量最小,得到最优的光顺逼近曲线。利用最小二乘法和非线性泛函的极小值优化计算,对平面数据点进行光顺逼近,达到光顺的目的。最后,给出了由数据拟合的C-Bezier曲线光顺的实例。     

最大比率圆弧逼近轮廓的匹配方法

提出了一种新的圆孤逼近轮廓曲线进行目标匹配的方法-最大比率法。曲线上两点之间的圆弧和曲线夹成的面积与对应扇形的比值随曲线上点的曲率的变化而变化。通过设置一个阈值算法可以检测曲率的较大的特征点用于圆弧逼近匹配。     

基于高斯曲率的曲面光顺方法研究

在交互设计系统中曲率(包括高斯曲率和平均曲率)评价是分析曲线曲面质量的重要工具。对于B样条曲线的光顺算法已经比较成熟。但对于如何基于曲率（包括高斯曲率和平均曲率）的曲面光顺算法则还有许多工作要做。该文提出了一种基于最小二乘的曲面优化算法，可以得到比较好的结果。该光顺算法主要包括两个步骤：依据曲率光顺准则修改曲面的曲率和修改后的曲率基于原曲面优化反向求出新的控制顶点。     

最大比率圆弧逼近轮廓的匹配方法

本文提出了一种新的圆孤逼近轮廓曲线进行目标匹配的方法—最大比率法。曲线上两点之间的圆弧和曲线夹成的面积与对应扇形的比值随曲线上点的曲率的变化而变化。通过设置一个阈值,算法可以检测曲率较大的特征点,用于圆弧逼近匹配。     

Adaptive knot placement in B-spline curve approximation

An adaptive knot placement algorithm for B-spline curve approximation to dense and noisy data points is presented in this paper. In this algorithm, the discrete curvature of the points is smoothed to expose the characteristics of the underlying curve. With respect to the integration of the smoothed curvature, knots are placed adaptively to satisfy a heuristic rule. Several experimental results are included to demonstrate the validity of this algorithm.     

Fast computation of optimal polygonal approximations of digital planar closed curves

We face the problem of obtaining the optimal polygonal approximation of a digital planar curve. Given an ordered set of points on the Euclidean plane, an efficient method to obtain a polygonal approximation with the minimum number of segments, such that, the distortion error does not excess a threshold, is proposed. We present a novel algorithm to determine the optimal solution for the min-# polygonal approximation problem using the sum of square deviations criterion on closed curves.Our proposal, which is based on Mixed Integer Programming, has been tested using a set of contours of real images, obtaining significant differences in the computation time needed in comparison to the state-of-the-art methods.     

Cubic Bézier approximation of a digitized curve

In this paper we present an efficient technique for piecewise cubic Bézier approximation of digitized curve. An adaptive breakpoint detection method divides a digital curve into a number of segments and each segment is approximated by a cubic Bézier curve so that the approximation error is minimized. Initial approximated Bézier control points for each of the segments are obtained by interpolation technique i.e. by the reverse recursion of De Castaljau's algorithm. Two methods, two-dimensional logarithmic search algorithm (TDLSA) and an evolutionary search algorithm (ESA), are introduced to find the best-fit Bézier control points from the approximate interpolated control points. ESA based refinement is proved to be better experimentally. Experimental results show that Bézier approximation of a digitized curve is much more accurate and uses less number of points compared to other approximation techniques.     

基于遗传算法的B样条曲线拟合改进算法

B样条曲线拟合应用于绘制离散数据点的变化趋势,一般采用数据逼近或者迭代的方法得到,是图像处理和逆向工程中的重要内容。针对待拟合曲线存在多峰值、尖点、间断等问题,提出一种基于遗传算法的B样条曲线拟合算法。首先利用惩罚函数将带约束的曲线优化问题转换为无约束问题,然后利用改进的遗传算法来选择合适的适应度函数,再结合模拟退火算法自适应调整节点的数量和位置,在寻优的过程中找到最优的节点向量,持续迭代直到产生最终的优良重建曲线为止。实验结果表明,该算法有效地提高了精度并加快了收敛速度。     

关键点选取的最小二乘渐进迭代逼近

目的 最小二乘渐进迭代逼近（LSPIA）方法多以均匀参数化或弦长参数化的形式均匀地确定初始控制点,虽然取得了良好效果,但在处理复杂曲线时,迭代速度相对较慢且误差精度不一定能达到预期设定值。为了进一步提高迭代效率和误差精度,本文提出了基于关键点（局部曲率最大点和极端曲率点）的最小二乘渐进迭代逼近方法。方法 首先计算所有数据点的离散曲率,筛选出局部曲率最大点;接着设定初始的曲率下限,筛选出极端曲率点;然后将关键点与均匀选取的控制点按参数顺序化,并将其作为迭代的初始控制点;最后利用LSPIA方法对数据点进行拟合。结果 对同一组数据点,分别采用LSPIA方法和基于关键点的LSPIA方法,本文方法较好地提高了收敛速度;在相同的控制点数目下,与LSPIA算法相比,本文方法的误差精度较小。结论 本文方法适合于比较复杂的曲线,基于曲率分布的关键点的选取,可以更好地反映曲线的几何信息。数值实例表明,结合关键点筛选策略的LSPIA算法提高了计算效率,取得了更好的拟合效果。     

基于代价敏感的粗糙集近似集与粒度寻优算法

粗糙集的近似集用已有知识粒对不确定性目标概念进行近似描述,但在构建近似集时并没有考虑数据的代价信息这一实际因素.对此,首先分析在构建粗糙集的近似集时考虑代价信息的必要性;然后,从代价敏感角度构建误分类代价的粗糙集近似集模型,并分析该模型下求得的近似集的相关性质.为了在多粒度空间中寻找一个合适的粒度空间来对不确定性目标概念进行近似描述,使误分类代价与测试代价之和尽可能小,给出属性代价贡献率的定义,并提出一种代价敏感的粒度寻优算法.实验结果表明,所提出算法能适用于现有代价认知场景,并在给定代价场景下求出合理的层次粒度空间结构以及不确定性目标概念的近似集.     

Approximating the Medial Axis from the Voronoi Diagram with a Convergence Guarantee

The medial axis of a surface in 3D is the closure of all points that have two or more closest points on the surface. It is an essential geometric structure in a number of applications involving 3D geometric shapes. Since exact computation of the medial axis is difficult in general, efforts continue to improve their approximations. Voronoi diagrams turn out to be useful for this approximation. Although it is known that Voronoi vertices for a sample of points from a curve in 2D approximate its medial axis, a similar result does not hold in 3D. Recently, it has been discovered that only a subset of Voronoi vertices converge to the medial axis as sample density approaches infinity. However, most applications need a nondiscrete approximation as opposed to a discrete one. To date no known algorithm can compute this approximation straight from the Voronoi diagram with a guarantee of convergence. We present such an algorithm and its convergence analysis in this paper. One salient feature of the algorithm is that it is scale and density independent. Experimental results corroborate our theoretical claims.     

Discrete contours in multiple views: approximation and recognition

Recognition of discrete planar contours under similarity transformations has received a lot of attention but little work has been reported on recognizing them under more general transformations. Planar object boundaries undergo projective or affine transformations across multiple views. We present two methods to recognize discrete curves in this paper. The first method computes a piecewise parametric approximation of the discrete curve that is projectively invariant. A polygon approximation scheme and a piecewise conic approximation scheme are presented here. The second method computes an invariant sequence directly from the sequence of discrete points on the curve in a Fourier transform space. The sequence is shown to be identical up to a scale factor in all affine related views of the curve. We present the theory and demonstrate its applications to several problems including numeral recognition, aircraft recognition, and homography computation.     

Approximating the Medial Axis from the Voronoi Diagram with a Convergence Guarantee

The medial axis of a surface in 3D is the closure of all points that have two or more closest points on the surface. It is an essential geometric structure in a number of applications involving 3D geometric shapes. Since exact computation of the medial axis is difficult in general, efforts continue to improve their approximations. Voronoi diagrams turn out to be useful for this approximation. Although it is known that Voronoi vertices for a sample of points from a curve in 2D approximate its medial axis, a similar result does not hold in 3D. Recently, it has been discovered that only a subset of Voronoi vertices converge to the medial axis as sample density approaches infinity. However, most applications need a nondiscrete approximation as opposed to a discrete one. To date no known algorithm can compute this approximation straight from the Voronoi diagram with a guarantee of convergence. We present such an algorithm and its convergence analysis in this paper. One salient feature of the algorithm is that it is scale and density independent. Experimental results corroborate our theoretical claims.     

手绘线矢量化技术的研究与实现

手绘是人类思维外化和表达意图的一种有效方式,如何有效地对手绘线进行矢量化是正确理解绘图者意图的关键。本文提出一种采用组合贝塞尔曲线拟合稠密的二维手绘线数据点列的算法。采用平均弧长对数据点列进行滤波,剔除点列中的冗余点,利用相邻弧长间的夹角及弧长间的比值来估计各弧长中点的离散曲率值,采用平均曲率对各弧长中点进行过滤,识别出手绘线的绝大多数特征点,并分段构造插值于特征点的组合贝塞尔曲线。实验结果表明,所构造的曲线能够很好地反映手绘线的细小特征部分。该算法具有速度较快、拟合精度高等特点,可广泛应用于二维手绘线的矢量化过程。