Calibration Method for Mapping Camera Based on a Precise Grouped Approach Method

被引：4

作者：

Zheng, Lina ^{[1
]}

Yuan, Guoqin ^{[1
]}

Leng, Xue ^{[2
]}

Wu, Yingfeng ^{[3
]}

机构：

[1] Chinese Acad Sci, Changchun Inst Opt Fine Mech & Phys, Key Lab Airborne Opt Imaging & Measurement, Changchun 130033, Jilin, Peoples R China

[2] Changguang Insight Vis Optoelect Co Ltd, Changchun 130033, Jilin, Peoples R China

[3] BMW China Serv Ltd, Shenyang 110000, Liaoning, Peoples R China

来源：

INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE | 2018年 / 32卷 / 11期

关键词：

PGAM; mapping camera; calibration; exact measuring angle method; weighted theory; MACHINE VISION METROLOGY;

D O I：

10.1142/S0218001418550194

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper introduces a new calibration method for the mapping camera called Precise Grouped Approach Method (PGAM). The conventional calibration method for the mapping camera is the exact measuring angle method. The accuracy of this method can be reduced by theoretical uncertainties and the number and distribution of observation points. PGAM is able to overcome these disadvantages and improve the accuracy. Firstly, we reduce the theoretical uncertainties by means of a grouped approach method, which rectifies the high-precision rotation stage to zero position. Secondly, a weighted theory is applied to eliminate the effect of the number and distribution of observation points. Finally, the accuracy of PGAM is analyzed. The experiment result shows that the calibration accuracy is significantly improved when using the proposed PGAM algorithm, compared to the conventional one under the identical experimental condition.

引用

页数：12

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