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基于模板匹配的细菌鉴定系统摄像机标定方法研究
引用本文:李梦卓,陈兆学,张奎.基于模板匹配的细菌鉴定系统摄像机标定方法研究[J].上海理工大学学报,2019,41(6):527-532.
作者姓名:李梦卓  陈兆学  张奎
作者单位:上海理工大学 医疗器械与食品学院, 上海 200093,上海理工大学 医疗器械与食品学院, 上海 200093,上海理工大学 医疗器械与食品学院, 上海 200093
摘    要:在研究传统摄像机标定原理及方法的基础上,针对传统方法的不足,提出了基于CCD的细菌自动鉴定系统的一种特殊的基于模板匹配的单目摄像机标定方法。该方法直接将基于CCD细菌鉴定系统中的96孔酶标模板作为辅助标定装置,仅要求全自动微生物鉴定系统中的摄像机摄取任一幅模板图像,即可根据射影几何内秉的约束条件完成对系统中CCD摄像机焦距、摄像机高度等有效参数的标定,计算量小,有一定的实用性。通过对该方法标定结果与基于空间三角形的标定算法所得结果进行实验比较,证明了该方法的有效性。

关 键 词:成像光学  摄像机标定  图像处理  细菌自动鉴定
收稿时间:2018/7/29 0:00:00

Camera Calibration Method of Bacterial Identification System Based on Template Matching
LI Mengzhuo,CHEN Zhaoxue and ZHANG Kui.Camera Calibration Method of Bacterial Identification System Based on Template Matching[J].Journal of University of Shanghai For Science and Technology,2019,41(6):527-532.
Authors:LI Mengzhuo  CHEN Zhaoxue and ZHANG Kui
Institution:School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China,School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China and School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
Abstract:Based on the study of the principle and the method of traditional camera calibration, a special template-matching-based monocular camera calibration method was used in the CCD-based automatic bacteria identification system, trying to improve the shortcomings of the traditional methods. This method directly used the 96-well elisa plate template in the system as a calibration auxiliary device. It only required the camera in the automatic microbiological identification system to capture a certain frame of the template image, and then it could calibrate the effective parameters such as the focal length and the height of the CCD camera in the system according to the constraints of the projective geometry. The whole progress required less calculation and was more practical. This method was proved to be more effective by comparing it with the spatial triangle calibration algorithm.
Keywords:imaging optics  camera calibration  image processing  bacteria automatic identification
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