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Digital image distortion and proofreading technology in micro focal spot X-ray inspection

机译:微焦点X射线检查中的数字图像失真和校对技术

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For the sake of the processing errors and constructional offsets of the lens of CCD camera, the digital image gained in micro-focal X-ray inspection has radial and tangential and other non-linear distortion. This paper presents an approach to proofreading the image distortion. First of all, a X-ray inspection image of a PCB with 19×19 BGA pads is taken as a calibration sample image, and is processed by the local adaptive thresholding algorithm. Secondly, corner points which are defined as the gray level change are the biggest points along horizontal and vertical direction within their adjacent fields respectively are collected by using Harris Corner algorithm with Gaussian smoothing coefficients. Thirdly, to reduce the computational complexity, some points are selected in a certain interval from the above corner point collection as the basis sample points of distortion correction model which using the least squares algorithm for two-dimensional N-order polynomial fitting, and the correlation fitting coefficients are calculated. Fourthly, the distorted sample image is corrected by using the distortion correction model. At last, to verify the universality of the correction model an image of X-ray detection is arbitrarily chosen and is corrected. Comparing the two images before and after correction processed it can be found that the presented proofreading approach has not only rather correction precision but also quite universality.
机译:由于CCD相机镜头的加工误差和结构偏移,在微焦点X射线检查中获得的数字图像具有径向和切向以及其他非线性失真。本文提出了一种校正图像失真的方法。首先,将具有19×19 BGA焊盘的PCB的X射线检查图像作为校准样本图像,并通过局部自适应阈值算法进行处理。其次,利用具有高斯平滑系数的Harris Corner算法,收集被定义为灰度变化的角点,分别是它们相邻区域内沿水平和垂直方向的最大点。第三,为降低计算复杂度,从上述角点集合中以一定的间隔选择一些点作为失真校正模型的基础样本点,该模型使用最小二乘算法进行二维N阶多项式拟合,并进行相关处理。计算拟合系数。第四,通过使用畸变校正模型来校正畸变的样本图像。最后,为了验证校正模型的通用性,可以任意选择X射线检测图像并进行校正。比较校正处理前后的两个图像,可以发现,所提供的校对方法不仅具有校正精度,而且具有相当的通用性。

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