Three-dimensional illusory contours and surfaces.

Under general viewing conditions, objects are often partially camouflaged, obscured or occluded, thereby limiting information about their three-dimensional position, orientation and shape to incomplete and variable image cues. When presented with such partial cues, observers report perceiving 'illusory' contours and surfaces (forms) in regions having no physical image contrast. Here we report that three-dimensional illusory forms share three fundamental properties with 'real' forms: (1) the same forms are perceived using either stereo or motion parallax cues (cue invariance); (2) they retain their shape over changes in position and orientation relative to an observer (view stability); and (3) they can take the shape of general contours and surfaces in three dimensions (morphic generality). We hypothesize that illusory contours and surfaces are manifestations of a previously unnoticed visual process which constructs a representation of three-dimensional position, orientation and shape of objects from available image cues.     

断层轮廓的双三次非均匀B样条曲面重构

针对断层图像数据,提出了一种曲面重构的方法.依据曲率特征首先提取各层特征点,对其重采样使每行(列)获得统一的采样点数;再对采样点插值得到非均匀双三次B样条曲面;最后,在一定控制精度下对曲面依据距离特征进行节点插入,通过最小二乘逼近法算出新的控制顶点,从而得到误差在容许范围内的逼近曲面.根据断层轮廓的特点,本算法综合运用了周期B样条和非周期B样条,讨论了封闭曲面和非封闭曲面的计算方法.另外插值和逼近的结合应用使该算法更快速、实用.     

利用弹簧模型提取物体轮廓

复杂背景下的物体轮廓提取是一个实际的图象处理系统必须面对的问题,而传统的轮廓提取方法在此情况下往往因为大量的噪声而失效,本文所处理的胃部的SDC图象中物体的边缘就处在与边缘的斜率和灰度梯度极为相近的噪声中,所以较难提取,我们利用UBF图象已提取的轮廓建立弹簧模型,根据两种图象中胃部的形变关系,较好的提取了SDC图象中的胃部轮廓,该方法对其它复杂前景下的图象处理有较好的参考价值。     

A new algorithm of brain volume contours segmentation

This paper explores brain CT slices segmentation technique and some related problems, including contours segmentation algorithms, edge detector, algorithm evaluation and experimental results. This article describes a method for contour-based segmentation of anatomical structures in 3D medical data sets. With this method, the user manually traces one or more 2D contours of an anatomical structure of interest on parallel planes arbitrarily cutting the data set. The experimental results showes the segmentation based on 3D brain volume and 2D CT slices. The main creative contributions in this paper are: (1) contours segmentation algorithm; (2) edge detector; (3) algorithm evaluation.     

刀具半径补偿在平面轮廓铣削中的应用

本文介绍刀具补偿原理,针对实际轮廓加工过程中刀具半径补偿的执行过程(建立、执行、撤消,)结合所用数控机床及系统和刀具说明其中的注意事项和零件加工程序。实践证明刀具半径补偿在粗、半精和精加工中切实可行,且符合零件加工尺寸精度要求,同时还可以完成零件上毛刺的清除。     

变形曲线曲率内外力作用下的轮廓提取

文章对变形轮廓曲线的几何特征进行分析,提出了一种以曲率内外力为驱动力的主动轮廓边缘提取方法,对传统方法作了改进.首先经过比较,采用当前结点的八邻域点来计算变形曲线轮廓局部区域的曲率,并经过正则化处理,既保证了计算的精度要求,又降低了计算的复杂性,同时部分避免了后期的微分方程求解;根据进化轮廓的凹凸性以及它和目标轮廓的相...     

基于主动轮廓技术的植物叶图像提取方法

叶是植物的重要特征信息,叶片图像提取是植物器官建模和生鲜植物识别的关键步骤。在植物自动识别和叶建模领域具有重要价值。笔者提出了一种基于主动轮廓技术和细胞神经网络的叶图像提取方法,实践表明基于细胞神经网络的可变模板技术实现了对植物叶片轮廓的灵活控制,同时结合了隐含模型和参数模型的特征,提高了提取的精度和鲁棒性。提取结果表明,采用该算法可以有效提取叶脉络。     

用序列二维轮廓线重建三维形体表面的方法

针对以往重建表面算法的复杂、计算量大以及存在误连而导致走样等不利因素,提出一种基于角度的三角面片联结方法。该方法主要是在面片联结之前对轮廓线上的点按角度进行取舍,不仅减少了要处理的数据点,而且也使三角面片的联结简易化。实验表明,该方法简单易行,重建速度快,计算量小,适合于由序列单轮廓线重建三维表面形体。     

复杂轮廓激光切割路径优化算法的研究

激光切割的加工路径优化问题实质上是如何缩短激光头在轮廓间移动的空行程距离.复杂轮廓的切割顺序的生成必须考虑轮廓的嵌套问题.本文以轮廓位置关系为约束条件,根据图论原理将加工路径优化问题归结为广义旅行商问题(GTSP).提出了先按照轮廓位置关系构造树形结构,然后以加工起点为基准点按照从内向外的顺序遍历树形结构的优化算法,并给出应用实例.实验统计表明,使用该算法可将激光头空行程距离减少10%以上,明显的提高了激光切割的效率和质量.     

RBF neural network and active circles based algorithm for contours extraction

For the contours extraction from the images, active contour model and self-organizing map based approach are popular nowadays. But they are still confronted with the problems that the optimization of energy function will trap in local minimums and the contour evolutions greatly depend on the initial contour selection. Addressing to these problems, a contours extraction algorithm based on RBF neural network is proposed here. A series of circles with adaptive radius and center is firstly used to search image feature points that are scattered enough. After the feature points are clustered, a group of radial basis functions are constructed. Using the pixels’ intensities and gradients as the input vector, the final object contour can be obtained by the predicting ability of the neural network. The RBF neural network based algorithm is tested on three kinds of images, such as changing topology, complicated background, and blurring or noisy boundary. Simulation results show that the proposed algorithm performs contours extraction greatly.     

基于最小负曲率点搜索的快速人体肢体提取算法

人体肢体分割涉及两类最小负曲率点,利用人们对人体肢体划分的主观意识,提出最小负曲率点分析法,搜索分割手臂和腿部的最小负曲率点.跟踪目标前景区域的边缘,得到前景区域的外轮廓.采用傅里叶算子对人体轮廓实现平滑处理,消除局部噪声对最小负曲率点的影响.采用移动向量法求取轮廓曲线的数字曲率.在划分出的各个肢体部分内部进行轴线搜索,确定肢体关节点,完成人体肢体的提取.实验结果表明:算法可有效搜索最小负曲率点,实现人体肢体分割.     

认知语境论

认知结果是由认知对象、认知主体和认知条件三方面决定,并用数学方法对影响认知结果的原因进行了解释.     

基于变形模板的复杂截面轮廓重构方法研究

常规的B样条曲线重构存在散乱数据点的序化、参数化等步骤,采用变形模板的曲线重构方法可有效避免这些繁琐的操作.针对给定的复杂曲面零件的设计轮廓和实测截面数据点,提出了一种基于变形模板的复杂截面轮廓重构新方法,建立了最小模板变形条件下的截面轮廓配准与重构模型.提出的模板与实测点的精确配准与模板约束变形的迭代优化策略,以及基于递归细分的快速距离算法,保证了截面轮廓的重构精度与效率,建立起了设计模板与实际截形的解析关系.最后的实例验证了所提方法的有效性和实用性.     

一种基于初始化Snake轮廓线的混合舌图像分割算法

Snake模型是一种常用的舌图像分割方法,但Snake对初始轮廓的定位准确度要求较高,且对噪声敏感.为此提出一种基于双层极坐标边缘检测的算法以获取舌体的粗略边缘,再使用Snake模型根据局部细节对舌体粗略边缘进行修正得到准确的舌体边缘.基于500幅舌图像进行的实验结果表明,该方法的分割正确率达到95.6%,是一种较有效的分割方法.