【摘要】：相機標(biāo)定是計算機視覺領(lǐng)域的一個重要工作,尤其是視覺測量系統(tǒng)的一個重要的技術(shù)環(huán)節(jié)。相機標(biāo)定的準(zhǔn)確性對整個視覺測量系統(tǒng)的測量精度有很大的影響。一般而言,相機標(biāo)定技術(shù)可以分為如下幾種:視覺主動式標(biāo)定技術(shù)、傳統(tǒng)標(biāo)定技術(shù)、相機本身標(biāo)定技術(shù)。方法的選擇往往基于實際的需求。對相機標(biāo)定方法的要求是標(biāo)定操作簡單且精度高。基于此要求,本文的研究重點是傳統(tǒng)方法,即基于合作標(biāo)定物的標(biāo)定技術(shù)。本文從相機標(biāo)定基礎(chǔ)理論出發(fā),著重介紹了三維空間點到計算機幀存圖像點的轉(zhuǎn)換關(guān)系。為提出后續(xù)的相機標(biāo)定方法提供了可靠的理論支撐。三種經(jīng)典方法中的張正友平面標(biāo)定方法因為其標(biāo)定過程相對簡單,標(biāo)定結(jié)果較準(zhǔn)確,在實際視覺測量系統(tǒng)中應(yīng)用廣泛。該方法本身只求解了兩階徑向畸變系數(shù),為了充分研究該方法的性能,通過仿真實驗,探求了高階徑向畸變對該方法的影響。同時,本文在張氏標(biāo)定方法的基礎(chǔ)上提出了一種基于除法模型的相機標(biāo)定方法,該方法巧妙地將畸變系數(shù)與單應(yīng)性矩陣同時求解,使得在不使用非線性優(yōu)化的情況下,得到與張氏方法精度相當(dāng)?shù)臉?biāo)定結(jié)果。同時該方法還考慮了畸變中心與主點不重合的情況,添加了畸變中心這一參數(shù)。通過仿真以及實驗驗證了該方法標(biāo)定結(jié)果的準(zhǔn)確性�；诤献鳂�(biāo)定物的相機標(biāo)定方法中有三種經(jīng)典的方法,其中線性方法是最簡單最快捷的標(biāo)定方法,但因其沒有考慮相機畸變的存在,所以在標(biāo)定精度上有所不足。本文在經(jīng)典線性標(biāo)定方法的基礎(chǔ)上,根據(jù)實際工程需求,提出了一種基于標(biāo)志器的相機標(biāo)定方法。該方法是在線性標(biāo)定方法的基礎(chǔ)上,繼續(xù)估計徑向畸變,利用非線性優(yōu)化對所有參數(shù)進(jìn)行優(yōu)化。通過實際實驗證明了該方法的正確性。最后給出了本文所搭建的相機標(biāo)定系統(tǒng),并進(jìn)行了10次完整的相機標(biāo)定,得到10個標(biāo)定結(jié)果,通過標(biāo)定結(jié)果的分析,證明該系統(tǒng)簡單、實用、功能正確。
[Abstract]:Camera calibration is an important work in the field of computer vision, especially in the vision measurement system. The accuracy of camera calibration has great influence on the measurement accuracy of the whole vision measurement system. Generally speaking, camera calibration technology can be divided into the following: visual active calibration technology, traditional calibration technology, camera itself calibration technology. The choice of methods is often based on actual requirements. The requirement of camera calibration method is that the calibration operation is simple and the precision is high. Based on this requirement, this paper focuses on the traditional method, that is, the calibration technology based on cooperative calibration object. Based on the basic theory of camera calibration, this paper mainly introduces the conversion relationship between three dimensional space points and computer frame memory image points. It provides a reliable theoretical support for the subsequent camera calibration method. Because the calibration process is relatively simple and the calibration results are more accurate, the three classical methods are widely used in the practical vision measurement system. In order to fully study the performance of the method, the influence of higher order radial distortion on the method is investigated by simulation experiments. At the same time, on the basis of Zhang's calibration method, a camera calibration method based on division model is proposed in this paper. In this method, the distortion coefficient is solved simultaneously with the monoclinic matrix, so that the nonlinear optimization is not used. The calibration results are equivalent to those of Zhang's method. At the same time, the distortion center is not coincident with the main point, and the parameter of distortion center is added. The accuracy of the calibration results is verified by simulation and experiments. There are three classical methods for camera calibration based on cooperative calibration object, among which linear method is the simplest and quickest method, but because it does not consider the existence of camera distortion, it has some shortcomings in calibration accuracy. Based on the classical linear calibration method and the practical engineering requirements, a camera calibration method based on marker is proposed in this paper. Based on the linear calibration method, the radial distortion is estimated and all parameters are optimized by nonlinear optimization. The correctness of the method is proved by practical experiments. Finally, the camera calibration system in this paper is presented, and 10 complete camera calibration results are obtained. Through the analysis of calibration results, it is proved that the system is simple, practical and functional.
【學(xué)位授予單位】：中國科學(xué)院研究生院(光電技術(shù)研究所)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：TP391.41

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