基于正则渐进迭代逼近的自适应B 样条曲线拟合

基于渐进迭代逼近(PIA)的数据拟合方法以其简单和灵活的特性获得了广泛的关 注。为了获得高保真度的拟合曲线,提出了一种基于主导点选取和正则渐进迭代逼近(RPIA)的 自适应B 样条曲线拟合算法。首先根据数据点的曲率估计选取初始主导点并生成初始PIA 曲线。 然后,借助于拟合误差和数据点集的曲率分布选取加细的主导点及实现PIA 曲线的更新。得益 于基于曲率分布的主导点选取,使得拟合曲线在复杂区域分布较多的控制顶点,而在平坦区域 则较少。通过正则参数的引入构造了一种RPIA 格式,提升了渐进迭代控制的灵活性。最后, 数值算例表明相比于传统最小二乘曲线拟合该算法在使用较少数量的控制顶点时可实现较高的 拟合精度。     

基于B样条隶属函数的模糊推理系统

隶属函数和推理规则的确定是模糊推理的难点。通过研究模糊推理过程和B样条函数的特性,对应用B样条函数拟合模糊隶属函数进行推理的方法进行改进。通过对误差极值点、曲率极值点的计算和筛选,得到B样条函数的型值点。反算求得控制点之后,通过自适应增加控制点对曲线进行调整,增加曲线对隶属函数的拟合度,解决了B样条函数对隶属函数的拟合问题。建立B样条推理规则,构造实现了B样条推理系统,并求出该系统的最终结果为B样条超曲面。最后,通过实验验证了该方法的有效性和可行性。     

空间曲线基于内在几何量的高质量采样和B样条拟合

为解决均匀参数采样在许多情况下得到质量不高的采样点,进而生成不理想的B样条拟合曲线,提出空间曲线基于内在几何量的均匀采样方法,以获得给定总数且具有代表性的采样点.首先定义基于弧长、曲率和挠率加权组合的特征函数,通过调整组合参数更好匹配不同的曲线形状;然后提出空间曲线基于内在几何量的自适应采样方法,迭代生成满足给定距离阈值的采样点.采用最大绝对误差和均方根误差作为评价指标,与均匀弧长采样方法和基于弧长和曲率平均的均匀采样方法进行对比,并通过实例进行验证.结果表明,文中方法在采样质量和B样条拟合结果上获得明显改善.     

两种带形状参数的曲线

本文构造了两种带参数的三角样条基,基于这两组基定义了两种三角样条曲线。与二次B样条曲线类似,这两种曲线的每一段都由相继的三个控制顶点生成。这两种曲线具有许多与二次B样条曲线类似的性质,但它们的连续性都比二次B样条曲线更好。对于等距节点,在一般情况下,这两种曲线都整体C3连续,在特殊条件下,它们都可达C5连续。两种曲线中的形状参数均有明确的几何意义,参数越大,曲线越靠近控制多边形。另外,当形状参数满足一定条件时,这两种曲线都具有比二次B样条曲线更好的对控制多边形的逼近性。运用张量积方法,将这两种曲线推广后所得到的曲面也具有较好的连续性。     

Contour curve reconstruction from cloud data for rapid prototyping

In this study, a method for generation of sectional contour curves directly from cloud point data is given. This method computes contour curves for rapid prototyping model generation via adaptive slicing, data points reducing and B-spline curve fitting. In this approach, first a cloud point data set is segmented along the component building direction to a number of layers. The points are projected to the mid-plane of the layer to form a 2-dimensional (2D) band of scattered points. These points are then utilized to construct a boundary curve. A number of points are picked up along the band and a B-spline curve is fitted. Then points are selected on the B-spline curve based on its discrete curvature. These are the points used as centers for generation of circles with a user-define radius to capture a piece of the scattered band. The geometric center of the points lying within these circles is treated as a control point for a B-spline curve fitting that represents a boundary contour curve. The advantage of this method is simplicity and insensitivity to common small inaccuracies. Two experimental results are included to demonstrate the effectiveness and applicability of the proposed method.     

Global G3 continuity toolpath smoothing for a 5-DoF machining robot with parallel kinematics

Toolpath smoothing is an important approach to improve robots’ operational stability and machining quality. Nowadays, the corner rounding smoothing and curve fitting smoothing algorithms are usually adopted to process the linear toolpath segments to improve its continuity. But the high order continuity between the fitted curve and its adjacent curves is difficult to be guaranteed. For parallel machining robots (PMRs), the tangential, curvature and curvature derivative discontinuities at the junction may lead to the self-excited vibration of mechanical structure, consequently the machining efficiency and quality are decreased. Under this consideration, a global G³ continuity toolpath smoothing method for five degrees of freedom (5-DoF) PMRs is proposed. The linear segments toolpath generated by the Computer-Aided Manufacturing (CAM) system is first divided into long linear segments (LLSs) and short linear segments groups (SLSGs) through breakpoint searching. At the junction point, a B-spline transition curve is inserted to blend adjacent toolpaths. For the SLSG, the quintic B-spline is adopted to fit the discrete data points, constraint equations about the derivatives at the start and end points are established to achieve G³ continuity with the adjacent transition curves. Based on the proposed method, the smoothing for two test toolpaths is carried out, and experiments on a 5-DoF PMR are conducted to show the validity of the method in motion smoothness.     

B-spline surface fitting based on adaptive knot placement using dominant columns

By expanding the idea of B-spline curve fitting using dominant points (Park and Lee 2007 [13]), we propose a new approach to B-spline surface fitting to rectangular grid points, which is based on adaptive knot placement using dominant columns along u- and v-directions. The approach basically takes approximate B-spline surface lofting which performs adaptive multiple B-spline curve fitting along and across rows of the grid points to construct a resulting B-spline surface. In multiple B-spline curve fitting, rows of points are fitted by compatible B-spline curves with a common knot vector whose knots are computed by averaging the parameter values of dominant columns selected from the points. We address how to select dominant columns which play a key role in realizing adaptive knot placement and thereby yielding better surface fitting. Some examples demonstrate the usefulness and quality of the proposed approach.     

隐式B-样条曲线重建的直接Greville纵标法

提出了一种以隐式B-样条曲线为表达形式,基于直接Greville纵标的曲线重建方法。根据点云建立有向距离场,并作为B-样条函数的Greville纵标,然后根据高影响区内的平均代数误差优化Greville纵标;得到一个隐式B-样条函数,该函数的零点集即为重建曲线。该方法具有模型简单,重建速度快,无多余分支,无需手工调节任何参数的优点。实验结果证实了该直接法的效率明显高于点拟合法和普通场拟合法,以几何误差为准则的精度亦优于普通场拟合方法。     

基于Freeman链码的B样条曲线轮廓拟合

提出了一种Freeman链码与B样条曲线误差控制相结合实现轮廓拟合的算法,首先利用Freeman链码法进行边界跟踪,根据相邻像素点间的不同的链码变化关系,排除伪特征点,提取出轮廓中绝大多数特征点,然后结合基于误差控制的B样条曲线法,取得能够精确表示轮廓信息的特征点。本文算法即避免了使用曲率来进行求取特征点的复杂计算,提高了特征点检测速度,又提取出能够精确拟合轮廓的局部支撑点,实现了基于误差控制的轮廓曲线拟合。实验结果证明了本文算法的正确性。     

Data reduction using cubic rational B-splines

A geometric method for fitting rational cubic B-spline curves to data representing smooth curves, such as intersection curves or silhouette lines, is presented. The algorithm relies on the convex hull and on the variation diminishing properties of Bezier/B-spline curves. It is shown that the algorithm delivers fitting curves that approximate the data with high accuracy even in cases with large tolerances. The ways in which the algorithm computes the end tangent magnitudes and inner control points, fits cubic curves through intermediate points, checks the approximate error, obtains optimal segmentation using binary search, and obtains appropriate final curve form are discussed     

一种类四次三角样条曲线

针对B样条曲线相对于其控制多边形形状固定,以及不能描述除抛物线以外的圆锥曲线的不足进行改进。将形状参数与三角函数进行有机结合,构造了一组含参数的三角基,由这组基定义了带形状参数的三角样条曲线,其每一段由相继的5个控制顶点生成。新曲线在继承B样条曲线主要优点的同时,既具有形状可调性,又能精确表示椭圆,对于等距节点,在一般情况下曲线C³连续,当形状参数取特殊值时曲线可达C⁵连续。采用张量积方法,将曲线推广后所得到的曲面具有与曲线类似的性质,给出了用曲面表示椭球面的方法。     

带法向约束的隐式T样条曲线重构

目的 隐式曲线能够描述复杂的几何形状和拓扑结构,而传统的隐式B样条曲线的控制网格需要大量多余的控制点满足拓扑约束。有些情况下,获取的数据点不仅包含坐标信息,还包含相应的法向约束条件。针对这个问题,提出了一种带法向约束的隐式T样条曲线重建算法。方法 结合曲率自适应地调整采样点的疏密,利用二叉树及其细分过程从散乱数据点集构造2维T网格;基于隐式T样条函数提出了一种有效的曲线拟合模型。通过加入偏移数据点和光滑项消除额外零水平集,同时加入法向项减小曲线的法向误差,并依据最优化原理将问题转化为线性方程组求解得到控制系数,从而实现隐式曲线的重构。在误差较大的区域进行T网格局部细分,提高重建隐式曲线的精度。结果 实验在3个数据集上与两种方法进行比较,实验结果表明,本文算法的法向误差显著减小,法向平均误差由10^-3数量级缩小为10^-4数量级,法向最大误差由10^-2数量级缩小为10^-3数量级。在重构曲线质量上,消除了额外零水平集。与隐式B样条控制网格相比,3个数据集的T网格的控制点数量只有B样条网格的55.88%、39.80%和47.06%。结论 本文算法能在保证数据点精度的前提下,有效降低法向误差,消除了额外的零水平集。与隐式B样条曲线相比,本文方法减少了控制系数的数量,提高了运算速度。     

带约束的B 样条曲线曲面延伸技术

论文提出了一种带光滑有序点列约束的B 样条曲线延伸方法。该算法能 够根据约束点列的情况对曲线延伸部分所对应的节点值进行优化,通过插值尽量少的约束 点,使得延伸曲线与约束点列之间的最大距离小于预先给定的误差值,并且延伸曲线与原始 曲线之间自然达到最大阶连续。该方法也同样适用于带曲线约束的B 样条曲面延伸。实例 表明,所提出的算法是可行且有效的。     

三种形状可调三角样条曲线

构造了3种带参数的三角样条基,基于这3组基定义了3种三角样条曲线。与二次B样条曲线类似,这3种曲线的每一段都由相继的3个控制顶点生成,且这3种曲线具有许多与二次B样条曲线类似的性质。但这3种曲线的连续性都比二次B样条曲线要好。对于等距节点,在一般情况下,这3种曲线都是整体C²连续的,在特殊条件下它们都可以达到C³连续。另外,这3种曲线都具有比二次B样条曲线更好的对控制多边形的逼近性。     

B-样条曲线升阶的几何收敛性

B-样条曲线的升阶算法是CAD系统相互沟通必不可少的手段之一。B-样条曲线的控制多边形经过不断升阶以后,和Bézier曲线一样都会收敛到初始B-样条曲线。根据双次数B-样条的升阶算法,得到了B-样条曲线升阶的收敛性证明。与以往升阶算法不同的是,双次数B-样条的升阶算法具有割角的性质,这就使B-样条曲线升阶有了鲜明的几何意义。得到的结论可以使B-样条曲线像Bézier曲线一样,通过几何割角法生成。     

二次双曲Bézier曲线曲面

为了简化构造组合曲线时,相邻曲线的控制顶点间应满足的光滑拼接条件,构造了一种结构类似于二次Bézier曲线的含参数的双曲型曲线,称之为H-Bézier曲线。该曲线具有Bézier曲线的许多基本性质,如凸包性、对称性、几何不变性、端点插值和端边相切性。另外,该曲线具备形状可调性,可以精确表示双曲线。此外,若取特殊的参数,则当相邻H-Bézier曲线的控制顶点间满足普通Bézier曲线的G1光滑拼接条件时,曲线在公共连接点处可以达到G3光滑拼接。另外,给出了构造与给定多边形相切的H-Bézier曲线的方法,该方法简单有效,而且整条曲线对给定的切线多边形是保形的。运用张量积方法,将H-Bézier曲线推广后得到的曲面同样具有很多良好的性质。     

Least square geometric iterative fitting method for generalized B-spline curves with two different kinds of weights

Generalized B-spline bases are generated by monotone increasing and continuous “core” functions; thus generalized B-spline curves and surfaces not only hold almost the same perfect properties which classical B-splines hold but also show more flexibility in practical applications. Geometric iterative method (also known as progressive iterative approximation method) has good adaptability and stability and is popular due to its straight geometric meaning. However, in classical geometric iterative method, the number of control points is the same as that of data points. It is not suitable when large numbers of data points need to be fitted. In order to combine the advantages of generalized B-splines with those of geometric iterative method, a fresh least square geometric iterative fitting method for generalized B-splines is given, and two different kinds of weights are also introduced. The fitting method develops a series of fitting curves by adjusting control points iteratively, and the limit curve is weighted least square fitting result to the given large data points. Detailed discussion about choosing of core functions and two kinds of weights are also given. Plentiful numerical examples are also presented to show the effectiveness of the method.     

渐进迭代逼近方法在曲线变形上的应用

目的 随着几何造型、计算机动画等领域的快速发展,曲线的自由变形技术在近年来受到了广泛的关注。为了获得更多有趣、逼真的变形效果,提出基于渐进迭代逼近与主顶点方法的曲线局部变形算法。方法 给定数据点集,首先采用渐进迭代逼近方法或是基于最小二乘的渐进迭代逼近方法产生待变形曲线;其次对待变形区域使用延拓准则,基于主顶点方法与待变形曲线的形状信息选取控制顶点进行调整;最后对调整后的控制顶点运用局部渐进迭代逼近方法生成逼近曲线,得到期望的变形效果。结果 此变形操作借助于局部渐进迭代逼近方法,具有较好的灵活性。通过茶壶、面部轮廓、手等数值实例,表明了该方法可以得到良好的变形效果。进一步地,借助于叠加变形还可以得到整体的、周期的、伸缩的等各类更加丰富的变形效果。结论 本文研究渐进迭代逼近在曲线变形上的应用,将主顶点方法引入曲线的变形之中,把两者相结合提出了基于渐进迭代逼近与主顶点方法的曲线局部变形算法。该算法不仅具备渐进迭代逼近方法的收敛稳定性,且借助于主顶点方法,可以得到较好的变形效果。该方法适用于曲线的局部变形,丰富了曲线的变形效果。     

曲线曲面逼近与插值的统一表示

为了用一种模型实现从逼近到插值的转换,在多项式空间上构造了含一个参数的调配函数,由之定义了基于4点分段的曲线,该曲线可以理解为由相同的一组控制顶点定义的逼近曲线和插值曲线的线性组合,其中的逼近曲线为3次均匀B样条曲线,插值曲线经过除首末点以外的所有控制点。在均匀参数分割下,曲线具有C2连续性,取特殊参数时可达C3连续。在参数变化过程中,曲线各段起点、终点的位置发生改变,但这些点处的一阶、二阶导矢始终保持不变,即始终与3次B样条曲线相同。曲线形状与端点条件密切相关,而B样条曲线具有良好的保形性,这些综合因素使得曲线在形状变化的过程中始终可以较好地保持控制多边形的特征。采用张量积方法将曲线推广至曲面,曲线曲面图例显示了该方法在造型设计中的有效性。     

Global methods for stroke segmentation

Two methods for stroke segmentation from a global point of view are presented and compared. One is based on thinning methods and the other is based on contour curve fitting. For both cases an input image is binarized. For the former, Hilditch's method is used, then crossing points are sought, around which a domain is constructed. Outside the domain, a set of line segments are identified. These lines are connected and approximated by cubic B-spline curves. Smoothly connected lines are selected as segmented curves. This method works well for a limited class of crossing lines, which are shown experimentally. In the latter, a contour line is approximated by cubic B-spline curve, along which curvature is measured. According to the extreme points of the curvature graph, the contour line is segmented, based on which the line segment is obtained. Experimental results are shown for some difficult cases. Received October 31, 1998 / Revised January 12, 1999