微（小）型物体视觉测量与重构方法研究

发布时间：2018-03-09 19:07

  本文选题：视觉测量　切入点：三维重构　出处：《武汉大学》2013年博士论文　论文类型：学位论文

【摘要】：随着计算机技术的迅速发展和视觉传感器成本的降低,视觉测量和重构技术依靠其非接触、高精度、准实时化的优点在制造和装备业的产品品质管控(Quality Control,QC)中发挥着越来越重要的作用。近些年来,加工制造方法和工艺的改进,带来了微(小)型产品(尺寸为2mm～100mm)的数量不断增加,相对应的视觉测量任务也逐渐增多并且提出了一些新的要求,如检测精度高、速度快、误判率低等。本文针对微(小)型物体视觉测量与重构中的难点,以几种微(小)型物体(电子连接器、医学牙齿模型、医用注射器、珠宝、小型非标零件)为研究对象,从二维和三维视觉测量两个方面出发,对微(小)型物体几何特征提取和识别、精密外形快速重构、三维特征测量、模型简化等具体问题进行了研究。论文的主要工作和创新点包括： 1.针对微(小)型电子产品的二维几何和瑕疵的视觉测量及检测需求,介绍了一种基于最小二乘和权重函数的几何特征(直线、圆、椭圆)鲁棒性提取算法,并以几何特征作为骨架信息完成了对平面瑕疵的定位和识别。 2.针对微(小)型电子产品的表面特征识别需求,提出了一种较为通用的仿射不变特征识别算法。该算法综合利用伪Zernike不变矩及SIFT匹配,能有效地解决发生旋转、缩放、平移等特征的识别和分类。 3.针对纹理缺乏、形状规则的全凸微(小)型物体快速三维重构需求,提出一种基于多视轮廓线的重构算法(Shape from closed contours,SFCC),能在极短的时间内(40sec以内)得到被测目标精密的mesh模型。该算法基于序列轮廓影像,通过初次切割和精密切割两个步骤直接恢复面模型。基于该算法,设计和装配了相应的硬件设备,以钻石和注射器针头为实验目标进行了测试,其中基于SFCC方法恢复的三维钻石模型量测得到的线元素和角元素的精度分别可达到0.3mmm,0.03°,满足钻石切工等级监控的需求。 4.针对复杂的不规则的微(小)型物体表面点云的拼接需求,提出一种基于旋转平台的快速拼接算法,该算法利用空间点云的柱面约束标定旋转平台,进而实现对任意角度点云的自动拼接,无需人工后处理和标志点约束,能很好的同各类三维扫描仪进行结合实现复杂物体的表面点云快速拼接,点云拼接精度同业类领先的拼接算法得到的结果相当(拼接误差为0.3mm)。 5.基于点云数据,推导了三维空间几何特征(平面、球、圆柱体)的拟合公式,针对平面特征以平面度的提取进行了测试,针对球和圆柱体一款非标零件进行测试,完成了该零件上的球、圆柱特征的提取。 6.基于三角网数据,提出了一种利用多方向断面线约束的最优格网简化算法,该算法能高效的对密集三角网数据进行简化,可分别输出四边形和三角形格网数据,通过同原始数据的比对,简化后的误差控制在0.04mm以内。并以口腔学科中牙模应力性分析为测量需求,将本算法生成的牙模格网数据导入三维有限元分析软件,成功的获取到应力性分析数据。
[Abstract]:With the rapid development of computer technology and reduce the cost of the visual sensor, vision measurement and reconstruction technology relies on its non-contact, high accuracy, the advantages of quasi real time in the manufacturing and equipment industry product quality control (Quality, Control, QC) plays an increasingly important role. In recent years, the improved method and manufacturing process processing, bring the micro (small) products (the size of 2mm ~ 100mm) an increase in the number of visual measurement tasks corresponding to increase gradually and put forward some new requirements, such as high precision, fast speed, low false positive rate. In this paper, aiming at the micro (small) difficult objects in vision measurement and reconstruction, with several micro (small) object type (electronic connectors, medical dental model, medical syringe, jewelry, small non-standard parts) as the research object, from the 2D and 3D vision measurement based on two aspects of micro (small) type geometry Specific issues such as feature extraction and recognition, rapid contour reconstruction, 3D feature measurement and model simplification are studied.
1. for the micro (small) visual measurement and testing requirements of electronic products and two-dimensional geometric defects, introduces a kind of geometric features and least squares based on weight function (line, circle, ellipse) algorithm to extract the robustness, and geometric features as the skeleton information to complete the localization and identification of plane flaws.
2., aiming at the requirement of surface feature recognition for micro / small electronic products, a more general affine invariant feature recognition algorithm is proposed. The algorithm takes advantage of pseudo Zernike invariant moments and SIFT matching to effectively solve the recognition and classification of rotation, scaling and translation.
3. due to the lack of texture, the micro convex shape rules (small) object fast 3D reconstruction needs, proposed a multi view reconstruction algorithm based on contour (Shape from closed contours, SFCC), in a very short period of time (less than 40sec) measured mesh model precision. The algorithm is based on image through the initial contour sequence, cutting and precision cutting two step direct recovery models. Based on this algorithm, the design and assembly of the corresponding hardware equipment, diamond and syringe needle as the experimental targets were tested, the measured line elements and angular elements content of 3D diamond model based on SFCC method to restore the accuracy respectively. Can reach 0.3mmm, 0.03 degrees, to meet the diamond cut grade monitoring needs.
4. for the irregular complex micro (small) surface point cloud splicing demand, proposes a fast stitching algorithm based on rotating platform, the algorithm uses the cylindrical constraint space point cloud calibration rotary platform, so as to realize the automatic mosaic of arbitrary angle point cloud, without manual postprocessing and mark point constraint can, 3D scanner with all kinds of good combination of points on the surface of complex objects cloud fast mosaic, mosaic algorithm of point cloud splicing precision industry class leading results (error is 0.3mm).
5., based on the point cloud data, the fitting formula of three-dimensional spatial characteristics (plane, sphere and cylinder) is derived. The flatness extraction is tested for plane characteristics. A ball and cylinder part is tested for a non-standard part, and the extraction of spherical and cylindrical features on the part is completed.
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