基于编码标志点的数码相机三维测量与重构

介绍了利用数码相机作为图像传感器,在物体表面设置编码标志点,通过对编码标志点进行识别和检测,从而确定标志点的空间位置,实现了对物体表面某些特定点三维信息的无接触检测。介绍了其中的关键技术,如标志点的设计与检测、基础矩阵的求解、数码相机参数的标定以及内外参数的捆绑调整等,给出了检测实例并进行了精度验证。实验证明,该方法结构简单,成本低廉,数据采集快,移动方便,检测范围大,可满足三维物体特别是大面积物体空间检测的需求。     

大尺寸工件视觉测量中的图像拼接方法

为提高大尺寸工件机器视觉测量精度,提出一种基于坐标变换的图像拼接方法,并给出该坐标变换方法的解算模型及求解方法,分析了局部测量误差、重叠区域公共点个数等对坐标变换精度的影响,得到了最佳拼接条件,并通过实验对其进行了验证。实验结果表明,该方法简单易行、结果可靠,对存在平移、旋转以及尺度缩放的图像都具有良好的效果,能有效地解决采用机器视觉进行大尺寸工件精确测量时的坐标归一化问题。     

手机屏显靶标用于标定小视场双目三维测量系统

双目结构光三维测量系统在使用之前,需要利用立体靶标或者平面靶标进行系统标定.为了获得良好的精度,通常选择定制高精度靶标,然而定制的标准靶标价格较高,且一旦定制完成,既定的特征参数使得可对应标定的双目系统也相对固定,此类靶标的使用灵活性受到限制.当三维测量系统测量视场较小时,为了降低标定的成本,同时希望标定靶的特征图案灵...     

基于单应性矩阵的大尺寸零件视觉测量图像拼接方法

针对视觉检测技术对大尺寸复杂零件测量精度低的问题,提出一种基于单应性矩阵的大尺寸零件视觉测量图像拼接方法。首先建立世界坐标系→相机坐标系→投影坐标系→图像坐标系之间的归一化模型,提炼出简单易懂的坐标变换表达式H;然后对摄像机进行多次标定,确定像素当量、拍摄视场及焦距;再获取零件图像,利用前面得到的最简坐标表达式H得到拼接图像之间的配准,最后完成若干副图像的拼接,把拼接结果和SURF特征点方法及向后映射模型归一化的拼接结果进行比较。结果表明,该方法可以大大减少大尺寸零件拼接的时间,较SURF特征点方法和向后映射拼接用时分别降低86.55%和67.30%,拼接精度远高于SURF特征点方法和向后映射方法,分别提高了50.95%和25.08%,测量精度满足大尺寸零件检测精度要求。     

用条纹图形拼接法测量三维大物体面形

三维物体面形的测量在各个领域中有着广泛的应用，用莫尔法、调制光场分析法测量具有非接触性、高精度、快速的特点，但对于大物体的测量却存在着许多困难，诸如阴影噪声难以消除、条纹对比度低。考虑到图形的相关性，本文提出了一种基于多孔径拼接原理的测量三维大物体面形的方法：条纹图形拼接法，给出了数学模型、计算机模拟结果和实验结果。     

单相机立体视觉测量技术的研究

基于双目视觉理论,提出一种摆动式单目立体视觉测量方法,并搭建了相应测量系统。建立了精度分析模型,确定了系统各部分的视场范围,相机在摆动臂的带动下可以完成两个不同位置的拍摄。通过2D平面靶标定法对系统进行标定,采用Canny算子和Hough算子相结合的方式完成轮廓检测,并得到待测工件的匹配点图像。利用最小二乘法进行曲线拟合求取长方体的轮廓交点坐标及空间圆最优化拟合法求取圆的直径,实现对实验样品的三维测量,结果显示该系统相对检测精度达0.6%。     

基于机器视觉的表面粗糙度测量与三维评定

表面粗糙度的测量与评定一直是机械行业的重要课题。提出了一种基于机器视觉检测工件表面粗糙度的方法。首先利用显微镜获取端铣、刨、车不同等级下工件表面的序列图像,采用方差聚焦测度算子对序列图像中的每一个点进行高度计算;然后再利用高斯插值法计算出微观物体表面的准确高度,重构其表面微观形貌;最后计算出各个工件表面的三维粗糙度。通过对实验数据的分析和讨论,可以确定出表面均方根偏差Sq、表面偏斜度Ssk和表面峰密度Sds这三个参数,它们是常用地对工件表面粗糙度进行评价的可靠参数,可为以后三维粗糙度体系的科学建立提供依据。     

基于虚拟圆柱的曲面拼接方法

圆柱坐标下的多视角(孔径)扫描拼接方法主要针对类似回转物体面形的拼接测量,用该方法在对非单一回转轴,或者近似回转轴位置远离坐标轴形式的一类物体面形的拼接测量时遇到了困难,把拼接方法推广到基于虚拟圆柱可以解决这一难题。为此提出了基于虚拟圆柱原理的曲面拼接方法,给出了如何估计虚拟圆柱的半径,以及轴心坐标的计算方法,推导了基于虚拟圆柱的坐标转换方程,通过计算机模拟验证了其精确性,并通过实验证明这种方法对解决三维复杂物体表面特别是多视角测量获得面形的拼接测量问题是十分有效的。     

面向结构光三维测量的高稳定映射拼接方法

基于自由视角测量的三维拼接大大提高了测量的便捷性,为了提高视角间三维映射的稳健性,提出了一种改进的高稳定映射拼接方法。根据图像间匹配的特征点实现视角重合,利用结构光相位信息完成特征点三维映射和空间定位。针对特征点相位缺失无法重建的普遍问题,提出利用邻域点插值恢复特征点方法,虚拟重建视角间有效映射点,通过四元数法实现视角间点云的刚性变换和拼接。实验表明,相较传统的方法,该方法平均能将有效特征点数量提升20%,有效提高了映射拼接的稳定性。     

Novel calibration method for non-overlapping multiple vision sensors based on 1D target

The global calibration of multiple vision sensors (MVS) with non-overlapping views has been widely studied. In this paper, a novel calibration method for MVS with non-overlapping fields of view based on 1D target is presented. First, two neighboring vision sensors are selected. The rotation matrix between the two vision sensors is computed using the co-linearity property of the feature points on 1D target. Then the translation vector is computed according to the known distances between feature points on 1D target. The global calibration of all vision sensors is realized by repeating the above pair-wise calibration on different pairs of vision sensors. Due to the small volume and mobility of 1D target, the proposed global calibration method can be applied to vision sensors distributed in a large area or narrow space. Experiment results show that the RMS error of global calibration is within 0.060 mm.     

A self-recalibration method based on scale-invariant registration for structured light measurement systems

The accuracy of structured light measurement depends on delicate offline calibration. However, in some practical applications, the system is supposed to be reconfigured so frequently to track the target that an online calibration is required. To this end, this paper proposes a rapid and autonomous self-recalibration method. For the proposed method, first, the rotation matrix and the normalized translation vector are attained from the fundamental matrix; second, the scale factor is acquired based on scale-invariant registration such that the actual translation vector is obtained. Experiments have been conducted to verify the effectiveness of our proposed method and the results indicate a high degree of accuracy.     

基于数码相机的闪光灯投射系统照度分布测试

数码相机通过将景物取样成一系列像素来记录景物,而且每个像素的亮度取决于景物接收的光通量———照度。基于这一原理进行了闪光灯投影系统照度分布测试实验。首先通过数码相机采集被照物面的灰度图,然后用Photoshop图像处理软件和Matlab软件对图片进行量化分析处理,最终得到了闪光灯投射系统的照度分布情况。该测试方法简单、新颖,测试精度可满足工程应用需要。     

Interpolation algorithm for recovering the missing phase values in 3D measurement

In the three-dimensional (3D) phase measurement, some marks are usually adhered to the object in order to make the 3D registration process faster and easier. As covered with marks, local phase data are missing and have to be interpolated later. Considering the phase distribution nearby the marks, a gradient estimate (GE) interpolation algorithm is provided here. This algorithm recovers one pixel's missing phase value with the average of the estimated values which is calculated by gradients in eight directions nearby. Since this algorithm is a local processing, the missing phase values should be interpolated from the edge of the marks to the center. In the computer simulation and the practical experiment, compared with the same-size neighborhood mean (NM) algorithm and the Gerchberg-Saxton (GS) algorithm, this new algorithm achieves very good fit results with the least time. So it can be used as a practical tool for automatic missing phase interpolation.     

基于光流分层方法的平面3D运动估测

无人机自主着舰末端视觉导引中舰机间相对位姿的估测,可以看作机载摄像机对甲板平面3D运动的估测。提出了一种光流分层方法:首先利用已知焦距的机载摄像机拍摄着舰靶标区域的图像序列,并采用Lucas方法计算相邻两帧图像的光流场;而后通过分层模型,将由光流场进行3D运动检测的非线性问题转化为了两个线性问题。该方法无需图像间的特征匹配,可线性解算出着舰靶标区域相对于无人机的三维运动参数,进而得到舰机间的相对位姿信息。计算机合成图和摄像机实拍图像的实验结果验证了该算法的正确性和有效性。     

Precise perimeter measurement for 3D object with a binocular stereo vision measurement system

A novel measurement scheme for a three dimensional (3D) object's surface boundary perimeter is proposed. This scheme consists of three steps. First, a binocular stereo vision measurement system with two CCD cameras is devised to obtain the two images of a detected object's 3D surface boundary. Second, two B-spline active contours are applied to converge to the object's contour edges accurately in the two CCD images to perform the stereo matching. Finally, for the reconstructed 3D active contour, its true contour length is computed as the detected object's true boundary perimeter. An experiment on a bent surface's perimeter measurement indicates that this scheme's measurement repetition error decreases to 0.6%.     

A calibration method for stereo vision sensor with large FOV based on 1D targets

Large FOV (field of view) stereo vision sensor is of great importance in the measurement of large free-form surface. Before using it, the intrinsic and structure parameters of cameras should be calibrated. Traditional methods are mainly based on planar or 3D targets, which are usually expensive and difficult to manufacture especially for large dimension ones. Compared to that the method proposed in this paper is based on 1D (one dimensional) targets, which are easy to operate and with high efficiency. First two 1D targets with multiple feature points are placed randomly, and the cameras acquire multiple images of the targets from different angles of view. With the fixed angle between vectors defined by the two 1D targets we can establish the objective function with intrinsic parameters, which can be later solved by the optimization method. Then the stereo vision sensor with two calibrated cameras is set up, which acquire multiple images of another 1D target with two feature points in unrestrained motion. The initial values of the structure parameters are estimated by the linear method for the known distance between two feature points on the 1D target, while the optimal ones and intrinsic parameters of the stereo vision sensor are estimated with non-linear optimization method by establishing the minimizing function involving all the parameters. The experimental results show that the measurement precision of the stereo vision sensor is 0.046 mm with the working distance of about 3500 mm and the measurement scale of about 4000 mm×3000 mm. The method in this paper is proved suitable for calibration of stereo vision sensor of large-scale measurement field for its easy operation and high efficiency.     

用数码相机实现未琅禾费衍射测量细丝直径

介绍利用激光获得丝夫琅禾费衍射图样，并采用数码相机实现计算机辅助非接触自动测量细丝直径的方法，以及将其用于设计性实验的尝试。