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Study on distortion correction for image mosaic of surface defects

机译:表面缺陷图像马赛克变形校正研究

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It is hard to quantitate the micron-scale defects on large aperture (102mm×102mm) optical components by the conventional optical testing methods. This paper proposes a super-smooth surface defects measurement and evaluation system, achieved by using microscopic dark-field scattering imaging device, two-dimensional sub-image scanning mechanism and multi-cycle image mosaic algorithm. The defects detecting system, with a lateral resolution of 0.5μm, applies a large field of view design (largest FOV: 15mm×15mm). In order to test the largest element (430mm×430mm), however, over 1000 sub-pictures are captured. It takes more than 30 minutes to process these sub-pictures by multi-cycle image mosaic algorithm. This paper also presents a distortion correction method to revise the image mosaic mismatch caused by the optical distortion in the defects testing system on the platform of MATLAB. A binary optical grid plate (BOE) is fabricated as standard board to evaluate distortion. The proposed method applies image division multi-steps to build a look-up matrix of distortion parameters. According to the look-up matrix, all pixels on a sub-image are repositioned from the distortion Cartesian coordinates to the ideal Cartesian coordinates. Finally, feasibility of the distortion correction method is demonstrated by comparing the mosaic results of defect images before and after this process. The full field view distortion is reduced from more than 4% to less than 0.1%. After distortion correction, subimages can be directly mosaicked without using multi-cycle image mosaic algorithm, which improves test efficiency significantly. The method mentioned in this paper may also apply to other optical testing systems for image mosaic.
机译:通过传统的光学测试方法难以定量大孔径(102mm×102mm)光学组件上的微米垢缺陷。本文提出了一种超光滑的表面缺陷测量和评估系统,通过使用微观暗场散射成像装置,二维子图像扫描机构和多循环图像拼接算法实现。具有0.5μm的横向分辨率的缺陷检测系统适用于大型视野设计(最大FOV:15mm×15mm)。然而,为了测试最大元素(430mm×430mm),捕获超过1000个子图像。通过多循环图像马赛克算法处理这些子图像需要30多分钟。本文还提出了一种失真校正方法,用于修改由Matlab平台上的缺陷测试系统中的光学变形引起的图像镶嵌失配。二进制光栅板(BOE)制造为标准板以评估失真。该方法应用图像划分多步骤来构建失真参数的查找矩阵。根据查找矩阵,子图像上的所有像素从失真笛卡尔坐标重新定位到理想的笛卡尔坐标。最后,通过比较该过程之前和之后的缺陷图像的马赛克结果来证明失真校正方法的可行性。完整的现场视图失真从超过4%的减少到小于0.1%。在失真校正之后,可以在不使用多循环图像拼接算法的情况下直接拼接的子图像,这显着提高了测试效率。本文提到的方法还可以应用于图像马赛克的其他光学测试系统。

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