金相显微镜图像测量示值误差不确定度的评定方法

本文介绍了一种金相显微镜图像测量示值误差的校准方法。按照此方法对某金相显微镜图像测量的示值误差进行校准。通过校准结果分析,证明了该校准方法对测量点选择的有效性。通过对示值误差的校准结果及符合性判断的分析,确认该金相显微镜图像测量的示值误差满足MPEV为2%的要求,因此可利用此金相显微镜对人工缺陷这类微小尺寸样品进行图像测量。     

芯片载带缺陷的机器视觉检测方法

目的 针对芯片包装载带在生产过程中经常出现的型腔底部和边缘变形、穿孔等缺陷的检测问题,提出一种机器视觉检测方法。方法 首先离线准备配准模板及标准模板图像,然后根据模板在生产过程中进行在线检测。在检测过程中由传感器触发采集待检测型腔图像,然后通过模板匹配方法配准模板图像和待检测图像,并进行异或运算检测两图像差异从而定位缺陷。结果 实验证明边缘变形检测最大错误率为0.45%,底部变形检测最大错误率为0.50%,穿孔检测最大错误率为0.35%,每帧图像检测平均耗时为0.22 s,满足用户错误率不超过1%和每帧耗时不超过0.5 s的要求。结论 该方法能够实时检测芯片载带边缘变形、穿孔等缺陷,有效地实现载带加工生产过程中的质量监控。     

利用图像拼接实现微结构的大视场测量

为实现基于图像的飞秒激光烧蚀硅晶片光斑阵列的完整测量,对采集的多幅光斑阵列图像拼接,得到完整的飞秒激光烧蚀光斑阵列图像。首先,对飞秒激光烧蚀光斑图像进行增强处理,对光斑进行方形拟合提取中心点,获取每两个中心点间的像素值,运用线纹对微视觉测量系统标定,获得像素尺寸与几何尺寸之间的比例系数,根据比例系数对像素尺寸与几何尺寸进行换算,得到对光斑阵列的视觉测量值;最后,用拼接后的光斑阵列进行图像测量,得到测量尺寸与实际尺寸间的误差平均值为3.00%。经实验验证,利用图像拼接对微视觉系统大视场微结构进行图像测量是可行的。     

基于面阵CCD的药型在线检测仪图像采集的误差分析

设计了一套基于面阵CCD技术的药型在线检测仪。在此基础上,介绍了药型在线检测系统的基本原理。本文从透视误差、光照误差、定位误差三个方面,通过理论分析和实验研究,发现了在图像采集过程中误差产生的原因。针对误差产生的原因,提出了相应的解决方法,从而大大提高了药型在线检测仪的测量精度。     

一种基于轮廓配准的包装缺陷检测方法

提出了一种基于包装图像轮廓配准的包装缺陷检测方法.该方法先对包装图像进行轮廓提取,计算目标轮廓的质心,从而得到配准平移参量.围绕目标质心每隔一定角度抽得质心到轮廓的距离值,得到一个距离值的序列.通过计算标准图像和待配准图像的距离值序列的圆周相关的最大值来确定旋转的角度.然后对已配准的包装图像进行缺陷检测,实验证明,本方法对包装缺陷的检测是快速的,有效的.     

卷筒纸印刷纸张变形测量方法的研究

对卷筒纸印刷过程中的纸张变形测量方法进行了分析,利用CCD成像和图像处理技术进行了信号采集、图像检测、数据分析等的方法研究和程序设计,并在卷筒纸平版胶印机上进行了实验,检测结果与理论分析基本吻合,方法验证可行,可作为纸张变形研究和生产质量管理的有效手段。     

基于U形阵的多子阵海底检测技术

针对多波束浅海地形测量系统中面临的高精度底检测难题,着重讨论了在u形声基阵下采用分裂孔径相位差法的子阵分配方法以及相应的多子阵海底检测技术。仿真结果表明,由于引入了相位斜率误差曲线及图像变换等方法,使得该技术不仅能同时实现镜像和非镜像区域的海底检测,还提升了系统的检测性能。     

高温结构陶瓷缺陷的激光扫描超声显微检测

本文介绍了激光扫描超声显微镜的工作原理和在陶瓷缺陷检测中的应用。讨论了从缺陷的声图像判断缺陷的大小、位置以及性质的方法。通过对各种陶瓷缺陷的检测实验,证实了利用高频(100 MHz)超声对检测陶瓷中<100μm 缺陷的可能性。     

图像尺寸测量仪示值误差校准方法研究

图像尺寸测量仪是近几年兴起的尺寸测量设备,因其具有检测速度快、测量准确度高、操作简便等特点得到广泛使用。测量设备准确度的高低对提高产品质量有着直接关系,对其准确校准对工业生产、科学研究有着重要的作用。目前对于图像尺寸测量仪示值误差的校准缺乏具体分析,文章以用标准玻璃线纹尺校准图像尺寸测量仪示值误差为目标任务,通过深入分析给出测量方法、测量模型、标准不确定度分量评定以及验证该校准方法的可行性等详细过程,给校准图像尺寸测量仪提供了具体参考。     

一种多重分裂波束相位差海底检测技术

针对多波束浅海地形测量中面临的高精度底检测难题,提出了一种基于多重分裂波束相位差的多波束底检测技术,并着重讨论了在U型声基阵下该检测技术的实现方法。仿真结果表明,由于引入了多重分裂波束、相位斜率误差曲线及图像变换等处理过程,使得该技术不但能同时胜任镜像和非镜像区域的海底检测,而且还提升了系统的检测性能。     

Fabrication of hemispherical nano structure on a curved Al surface using low-temperature and high-voltage anodizing method

A simple method of fabricating hemispherical nanostructures on a curved aluminum rod surface was presented. In conventional methods of fabricating nanopatterns on a curved aluminum surface, mechanical or chemical processes have been widely used for the lens technologies. Such processes are not only expensive with long processing times, however, but they also involve local fabrication and are limited in the dimension size. In this paper, a method of fabricating hemispherical nanostructures on a curved aluminum surface is suggested for a functional three-dimensional (3D) master using a low-temperature and high-voltage (LTHV) anodizing method. By reducing the aluminum reaction rate under a low-temperature environment, the reaction current density can be remarkably reduced even though a high voltage was induced. Using the LTHV anodizing method, the hemispherical pattern size can be easily controlled with respect to voltage variations. The sizes of the hemispherical nanopatterns were about 150-300 nm. Using the LTHV anodizing process, hemispherical nanostructures can be obtained on a curved aluminum surface with controllable pattern sizes of 150-300 nm without defects such as burring from Joule's heat, micro-scratches, and cracks. A curved 3D hemispherical nanostructure may be used as a master in the roll-to-roll process.     

带钢表面缺陷视觉检测系统关键技术研究

为满足钢板表面缺陷在线检测系统宽幅面、高速、高分辨率的检测要求，讨论了基于线阵CCD的钢板表面缺陷视觉检测系统实现的关键技术；优化设计了视觉检测系统的光学照明部分，以检测不同类型的缺陷。通过软件系统的特殊设计，以保证实时在线检测。针对缺陷图像低对比度、高噪声的特点，提出了基于灰度统计特性的图像边缘检测方法，并实现了对缺陷图像的自适应阈值分割。依据图像的缺陷统计特性，定义了缺陷的灰度、几何等特征量，用于缺陷分类。本系统样机已在实验室环境下运行。     

Automatic defect inspection system of colour filters using Taguchi-based neural network

A coloured filter is a critical part of an LCD panel, especially to present a high quality colour display. At present, the defect detection of colour filters is conducted by manual inspection in the final product stage. However, poor detection efficiency and subjective judgment of manual inspection undermine accuracy. Therefore, this study applied image processing technology and the neural network to detect surface defects of colour filters in order to prevent losses arising from incorrect detection, lower production costs, and effectively improve yield. A back-propagation neural network (BPNN) classifier was selected to train the features. The results showed that the proposed method can be successfully applied in defect detection of colour filters to reduce artificial detection errors. In addition, the Taguchi method was used with BPNN to save time searching optimal learning parameters by the trial and error method, which achieves faster convergence, smaller convergent errors and better recognition rate. The results proved that the root-mean-square error (RMSE) of the Taguchi-based BPNN at final convergence is 0.000254, and recognition rate reaches 94%. Therefore, the proposed method has good effects in detecting the micro defects of a colour filter panel.     

玻璃表面缺陷检测系统研究

目的针对玻璃表面存在的划痕、漏点、结石和水印等4种主要缺陷,研究一种基于背光照射的玻璃表面缺陷检测方法,提出一种改进K均值聚类算法用于水印缺陷的检测。方法首先,通过设计的图像采集系统对玻璃图像进行采集,并对采集图像背景估计;然后根据水印缺陷与其他3种缺陷的灰度差异,将含缺陷的玻璃分成2类,完成缺陷粗分类;接着利用边缘检测算法对含划痕、漏点和结石缺陷的玻璃图像进行处理,利用结合了Otsu阈值分割方法和补偿系数f的改进K均值聚类算法对含有水印缺陷的玻璃图像进行处理,最终实现对玻璃表面4种缺陷的识别与标记。结果实验表明,该系统操作方便,算法复杂度低,缺陷识别准确度高,检测速度快。结论通过上述玻璃表面缺陷检测系统,可准确高效地检测出玻璃表面存在的4种主要缺陷。改进的K均值聚类可以准确实现对水印缺陷的检测,且该方法可以克服聚类迭代次数高,聚类结果容易陷入局部最小等缺点。极大地提高了缺陷检测的效率,可用于玻璃生产过程中的实时检测。     

An experimental GPR detection study of environmentally-influenced structural defects in hydraulic engineering

Structural defects such as separation between concrete slab and foundation, and structural voids often occur in hydraulic engineering, which threatens the safety of hydraulic engineering. As the size and internal material of the hydraulic engineering can be queried, ground penetration radar (GPR) detection has the advantage to detect these defects when compared with other nondestructive detection methods. At the same time, when GPR detection is applied to defect these structural defects in hydraulic engineering, complex environmental factors including the uneven structural surface, clutter interference, water reflection, etc. have to be taken into account. In this work, two experimental models are designed to represent two different types of hydraulic structures and the structural defects including separation between concrete slab and its bottom material and void or hole defects are simulated on the two test models, respectively. Through the GPR detection on the two experimental models, the effects of the three environmental factors on the radar images and the signatures of the radar images under the influence of the three environmental factors are studied. Then, different image processing methods are adopted to reduce the influence of the three different environmental factors, and the effects of these methods are verified using the radar images obtained from the experiments. Finally, the GPR detection on a practical hydraulic engineering influenced by the environmental factors and the image processing methods are investigated, which successfully verify the experimental investigation results. It is expected that this study would provide significant technology support for structural defects detection in hydraulic engineering.     

OLED显示屏表面缺陷自动检测方法

目的 为了解决OLED显示屏表面周期性纹理背景和缺陷边界模糊、对比度低的特征导致其表面缺陷检测困难的问题,开展OLED显示屏表面缺陷自动检测方法研究.方法 对OLED显示屏图像进行奇异值分解,选择前2个较大的奇异值重构图像纹理背景,对原图像和重构图像进行差分运算,获得残差图像.将残差图像像素随机赋予初始隶属度值,采用模糊C均值聚类法获得像素最终隶属度值.根据隶属度大小,将残差图像像素聚成2类,并从残差图像中准确地分割缺陷.结果 选取较大的2个奇异值可以有效地重构OLED显示屏的周期性纹理背景;模糊C均值聚类法分割缺陷获得的区域灰度一致性(U)平均值为0.9846.结论 基于奇异值分解的背景重构方法可以有效地检测OLED显示屏表面缺陷;与分水岭法和Otsu方法相比,模糊C均值聚类可以准确地分割模糊边界的缺陷区域.     

精确测量金属镀层工件表面缺陷的图像处理方法

设计了一套自动测量表面缺陷的系统．以面阵CCD采集图像,实现了对金属镀层工件表面图像的双面、高速、高分辨率测量．系统的图像处理采用模块化程序设计,方便实现工件表面精确测量的特定要求．通过两次分别选取闽值,采用经过改进的大津阈值分割法求取特征分割阈值时,能够十分理想地提取工件上的微小缺陷,实现了对金属工件表面的精确测量．该系统针对不同形状、不同镀层的工件表面可以调整LED照明光源的光强,在图像处理中可以调整去光圈和特征检测的灵敏度．通过方便调整系统的技术参数,满足工业现场的具体要求．以钕铁硼小型工件缺陷检测作为应用实例验证了该系统的可行性．     

由序列图像进行三维测量的新方法

目前的三维测量方法都需要专门的测量设备且存在着种种限制,为此提出了一种基于图像序列进行三维测量的新方法。将由数码相机围绕被测物体拍摄的多幅图像导入计算机,利用图像处理知识得到特征的二维信息;采用计算机视觉方法,对特征从射影空间到欧式空间分层逐步重建即可完成三维测量。设计一套特征标志组合,作为辅助测量工具避免了特征匹配难题。确立了一套图像分割与识别策略获得特征标志二维信息,识别率可达到95%以上。采用基于模约束的摄像机分层自标定方法得到特征在欧式空间下的三维信息,并通过多种优化方法减少误差的影响。该方法在硬件上实现简单,对测量条件要求不高。实际试验表明,相对误差可达到1.48%,重投影误差为0.3864像素。     

基于二次曲面拟合的亚象素图象匹配算法

在图象测量系统中，目标的精确定位是一个关键问题，也是应用其它图像处理技术的基础。传统的图象匹配算法只能在象素极定位，本文基于相关函数的二次曲面拟合提出了一种亚象素精度的匹配算法，它对于无噪声图象匹配的绝对误差小于０．０１象素。模拟实验表明，在有噪声的情况下该算法仍具有较小的偏差。     

Illumination compensation methods for automatic fiber connector inspection

Unevenly distributed image illumination is a problem in an automatic machine visual inspection system used for fiber connector defect detection. This unevenly distributed illumination makes it difficult to find an appropriate horizontal threshold to convert a gray-scale image to a binary image to separate surface defects, such as blobs and scratches, from the background of the connector. This paper proposes some effective methods to compensate the unevenly distributed illumination problem so that standard image processing methods can be used effectively to detect the defects of the fiber connectors.