Fast Focal Length Measurement Method based on Infrared Lens Images
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摘要: 如何准确检测镜头的焦距是红外镜头参数检测的一项重要研究内容。本文提出了一种基于刀口靶图像的焦距快速检测方法。该方法先采集红外镜头聚焦状态下的刀口靶图像，再进行刀口靶图像的二值化处理；通过提取目标的边缘轮廓，获得最小外接矩形的顶点坐标信息，从而估算出红外镜头对应焦距。实验结果证实：该检测方法可快速、准确地测量出镜头的焦距，且测量的平均绝对误差百分比小于1.48。该方法为红外镜头重要参数的快速检测奠定基础。Abstract: Accurately measuring the focal length of an infrared lens is a crucial issue in infrared lens parameter measurement. This paper proposes a practical focal length estimation method based on a target knife image. First, the target image is captured in the focused state and a binary image is obtained, then the edge of the target is extracted, the vertex coordinates of the minimum external rectangle are obtained, and the corresponding focal length of the infrared lens is estimated. Experimental results show that the algorithm can measure the focal length of the infrared lens quickly and accurately, and the average absolute error percentage is less than 1.48. This method lays the foundation for the rapid measurement of infrared lens parameters.
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Key words:
- focal length of infrared lens /
- measurement method /
- image binarization /
- edge extraction
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图 1 靶标经光学系统成像后的图像示意图
Figure 1. Schematic diagram of the target image by the optical system
表 1 同批次54 mm红外镜头的焦距检测结果
Table 1. Focal length detection results of 54 mm infrared lenses in the same batch
Serial number Certification agency results/mm Our results /mm Absolute error percentage 1 55.7306 56.1406 0.7 2 55.6084 56.0926 0.8 3 55.6686 56.1487 0.8 4 55.6147 56.1865 1.0 5 55.5730 55.9834 0.7 
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表 2 同批次5只8 mm红外镜头的焦距检测结果
Table 2. Focal length detection results of 8 mm infraredlenses in the same batch
Serial number Certification agency results/mm Our results /mm Absolute error percentage 1 7.8968 7.7614 1.7 2 7.8025 7.7034 1.2 3 7.8450 7.7326 1.4 4 7.9124 7.7805 1.6 5 7.9226 7.8029 1.5
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[1] 许士文. 红外成像系统测试与评价[M]. 北京: 红外与激光工程, 2008: 150-180. [2] Ohtsu N. A threshold selection method from gray-level histograms[J]. IEEE Transactions on Systems Man & Cybernetics, 1979, 9(1): 62-66. http://ieeexplore.ieee.org/document/4310076/citations [3] Imocha Singh, Tejmani Sinam. Local contrast and mean based thresholding technique in image binarization[J]. International Journal of Computer Applications, 2012, 51(6): 5-10. http://connection.ebscohost.com/c/articles/82151094/local-contrast-mean-based-thresholding-technique-image-binarization [4] 赵文涛, 曹昕鸷, 田志勇. 基于自适应阈值区域生长的红外舰船目标分割方法[J]. 红外技术, 2018, 40(2): 158-163. http://hwjs.nvir.cn/article/id/hwjs201802010ZHAO Wentao, CAO Xinzhi, TIAN Zhiyong. An infrared ship target segmentation method based on adaptive threshold region growth[J]. Infrared Technology, 2018, 40(2): 158-163. http://hwjs.nvir.cn/article/id/hwjs201802010 [5] 郝争辉, 张学松, 王高, 等. 基于边缘轮廓线提取的自动对焦评价函数[J]. 红外技术, 2018, 40(2): 170-175. http://hwjs.nvir.cn/article/id/hwjs201802012HAO Zhenghui, ZHANG Xuesong, WANG Gao, et al. Auto focusing evaluation function based on edge contour extraction[J]. Infrared Technology, 2018, 40(2): 170-175. http://hwjs.nvir.cn/article/id/hwjs201802012 [6] Gábor Domokos, Zsolt Lángi, Márk Mezei. A shape evolution model under affine transformations[J/OL][2017-09-18]. arXiv: 1604.07630 (https://arxiv.org/abs/1604.07630v2) -
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