【摘要】：本文針對(duì)工業(yè)現(xiàn)場(chǎng)測(cè)量過程中難以快速重構(gòu)出復(fù)雜零件的三維形貌為背景,在結(jié)合雙目立體視覺技術(shù)和結(jié)構(gòu)光測(cè)量技術(shù)的基礎(chǔ)上,深入研究和分析了全視場(chǎng)自定位掃描系統(tǒng)的工作原理及三維重建等問題,提出了一種新的非編碼標(biāo)志圓自定位方法用于重構(gòu)復(fù)雜物體的表面三維輪廓信息,并搭建了硬件系統(tǒng)和測(cè)量軟件驗(yàn)證了該方法的正確性和可靠性。通過對(duì)測(cè)量數(shù)據(jù)進(jìn)行處理和誤差分析,證明了該系統(tǒng)有較高的測(cè)量精度和速度。本文主要研究?jī)?nèi)容和創(chuàng)新成果有:1.提出了一種非編碼標(biāo)志圓自定位技術(shù)。創(chuàng)新性的利用標(biāo)志圓直徑唯一性的特征準(zhǔn)確識(shí)別并區(qū)分出極線方向上的多個(gè)標(biāo)志圓,在二維圓準(zhǔn)確匹配的基礎(chǔ)上,結(jié)合空間圓之間的不變拓?fù)潢P(guān)系,實(shí)現(xiàn)同名點(diǎn)云拼接,解決了不同視角下掃描儀空間坐標(biāo)自標(biāo)定轉(zhuǎn)換和非連續(xù)掃描數(shù)據(jù)點(diǎn)云測(cè)量數(shù)據(jù)自動(dòng)拼接難題。2.十字激光線條細(xì)化提取及區(qū)分。由于線激光光條的高亮特征,可通過自適應(yīng)閾值分割算法提取出激光條。通過分析現(xiàn)有光條中心提取方法,選取灰度平均加權(quán)重心法細(xì)化激光線條。普通的十字激光線條區(qū)分算法在交叉點(diǎn)提取失敗的情況下,將不能做到準(zhǔn)確區(qū)分,本文在雙目系統(tǒng)立體標(biāo)定和立體校正的基礎(chǔ)上,對(duì)十字線條進(jìn)行光平面標(biāo)定,以唯有正確匹配的光點(diǎn)計(jì)算出來的三維點(diǎn)處于光平面上作為區(qū)分依據(jù)。3.采用Pipeline流水線多線程工作模式,將整個(gè)圖像處理過程分為四個(gè)并行階段,分別是圖像采集、十字激光條細(xì)化提取、標(biāo)志圓識(shí)別及匹配、點(diǎn)云重構(gòu),調(diào)整四個(gè)階段圖像處理時(shí)間,使得子線程間負(fù)載均衡,理論上可將處理時(shí)間壓縮至原來的四分之一。
[Abstract]:In this paper, it is difficult to quickly reconstruct the 3D topography of complex parts in the process of industrial field measurement. Based on the binocular stereoscopic vision technology and structural light measurement technology, In this paper, the working principle and 3D reconstruction of the whole field of view self-positioning scanning system are deeply studied and analyzed, and a new non-coded marking circle self-localization method is proposed to reconstruct the 3D contour information of complex objects. The hardware system and measurement software are built to verify the correctness and reliability of the method. Through processing and error analysis of measurement data, it is proved that the system has high measuring precision and speed. The main contents and innovations of this paper are as follows: 1. A non-coding marking circle self-location technique is proposed. Innovatively using the unique characteristics of mark circle diameter to accurately identify and distinguish many mark circles in the direction of polar line. On the basis of the accurate matching of two-dimensional circles and the invariant topological relationship between spatial circles, the point clouds of the same name can be stitched together. The problems of self-calibration and self-calibration of scanner spatial coordinate and point cloud measurement of discontinuous scanning data are solved. 2. Cross laser line refinement extraction and differentiation. Because of the highlight feature of the line laser strip, the laser strip can be extracted by adaptive threshold segmentation algorithm. By analyzing the existing methods of extracting the center of the optical strip, the grayscale average plus weight center method is selected to refine the laser line. The common cross laser line discrimination algorithm will not be able to distinguish accurately in the case of cross point extraction failure. Based on the stereo calibration and stereo correction of binocular system, the cross line is calibrated in optical plane. The three dimensional points calculated by only the correct matching points are located on the optical plane. 3. 3. The whole image processing process is divided into four parallel stages by using Pipeline pipeline multithreading mode, which are image acquisition, cross laser strip thinning extraction, mark circle recognition and matching, point cloud reconstruction, and adjustment of image processing time. This allows for load balancing between child threads, which theoretically compresses processing time to the original 1/4.
【學(xué)位授予單位】：合肥工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP391.41

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