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1.陆军工程大学石家庄校区 火炮工程系, 河北 石家庄 050003
2.陆军工程大学石家庄校区 车辆与电气工程系, 河北 石家庄 050003
[ "丁超(1990-), 男, 河北定兴人, 博士研究生, 分别于2009年、2013年在军械工程学院获得学士、硕士学位, 主要从事机器视觉及数字图像处理的研究。E-mail:duncan1119@163.com" ]
[ "唐力伟(1961-), 男, 北京人, 教授, 博士生导师, 分别于1984年、1990年、1996年在天津大学获得学士、硕士、博士学位, 主要从事机械性能检测与故障诊断、机器视觉等方面的研究。E-mail:tom5157@163.com" ]
收稿日期:2017-12-18,
录用日期:2018-3-5,
纸质出版日期:2018-10-25
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丁超, 唐力伟, 曹立军, 等. 深孔内表面结构光图像几何畸变校正[J]. 光学 精密工程, 2018,26(10):2555-2564.
Chao DING, Li-wei TANG, Li-jun CAO, et al. Geometric distortion correction for structured-light image of deep-hole inner-surface[J]. Optics and precision engineering, 2018, 26(10): 2555-2564.
丁超, 唐力伟, 曹立军, 等. 深孔内表面结构光图像几何畸变校正[J]. 光学 精密工程, 2018,26(10):2555-2564. DOI: 10.3788/OPE.20182610.2555.
Chao DING, Li-wei TANG, Li-jun CAO, et al. Geometric distortion correction for structured-light image of deep-hole inner-surface[J]. Optics and precision engineering, 2018, 26(10): 2555-2564. DOI: 10.3788/OPE.20182610.2555.
在针对深孔类零部件内表面检测过程中因曲面特性引起的结构光图像几何畸变校正问题,一直是深孔内表面检测领域的难点。本文提出了一套针对结构光条纹图像的几何校正算法:该算法首先针对无差别建模的深孔内壁模型内表面进行结构光检测;然后基于离散映射理论搭建深孔内壁模型和内壁展开模型内表面之间的几何位置对应关系;最后基于映射关系校正深孔内表面结构光图像存在的几何错位(畸变)。检测结果表明,所提算法能够有效提高几何错位的校正精度,在不考虑图像边缘的基础上,校正偏差达到亚像素水平;并且因条纹斜率不一致造成的对应条纹最大间距(即距离偏差)控制在1.5 pixel范围内,即0.135 mm。
In the detection process for the inner-surface of deep-hole parts
the correction of image geometric distortion caused by the characteristics of a curved plane has proven to be difficult. In this study
a geometric correction algorithm for structured light stripe imaging was proposed. Firstly
the deep-hole inner-surface model (DIM) obtained via undifferentiated modeling was established. Then
the geometric position correspondence relationship between the DIM and the deep-hole inner-surface plane model was established based on discrete mapping. Finally
the geometric distortion of the structured light image was corrected based on the mapping relationship. The test results indicated that the proposed algorithm can effectively improve the correction accuracy of geometric distortion to the sub-pixel level without considering the edge of the image. The maximum distance (i.e.
distance deviation) between the corresponding stripes caused by the inconsistency of the slope is the distance deviation
which was 0.135 mm less than 1.5 pixels.
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