結構光線圖應用在非接觸主動式三維物面掃描之模擬與分析

Analysis and Simulation of Structured Light Patterns in Active Non-contact 3D Surface Scanning

劉盈諄(Ying-Zhun Liu)

指導教授 ： 鄭文凱

國立暨南國際大學/科技學院/資訊工程學系/碩士(2010年)

https://doi.org/10.6837/NCNU.2010.00304

摘要

三維物面掃描系統被廣泛的應用在眾多專業領域之中，而Gray code、Hilbert curve是常被運用在拍攝上的編碼。本論文針對現有的Gray code 和搭配Hilbert curve頻率分散的特性編碼進行不同的量化方式和分析，並建構出初步的模擬系統。
對於頻率變化最密和平均分散，哪一個會影響到整組code的效能比較大，本文嘗試去拍攝各種不同頻率code，門檻值在傳統打全暗全亮9+2張、全互補碼9+9張以及針對高頻打一張互補9+1張下，其實驗數據的分析。但是從實驗數據來看，似乎影響的不只最密的那一張，高頻率並不是影響整組效能的唯一因素。
另外，本論文針對投影系統進行雜訊分析，嘗試著找出會影響到實際拍攝環境的因素，並逐一加入模擬中並產生圖與實際的圖做比較，以期能與實際值接近。

關鍵字

三維物面掃描系統 ； 模擬

並列摘要

The 3D surface scanning technology has been widely applied in computer vision fields. In the technology, Gray code and Hilbert curves are the two major codes conventionally used. In this study, we focus on the comparison and construction of the simulation of Gray code, Hilbert curves, and the codes under Gray Coding Rule proposed in previous studies. The affect on the performance caused by the high frequency terms in the codes has also been examined, and various decoding rules applied on the codes are proposed and compared.
Finally, a group of parameters in a 3D surface scanning system such as noise, mean and standard deviation of the projected images, self- and cross-correlation of the recorded images, jittering, etc., have also been examined. The raw data of the parameters have been offered to a computer programming algorithm in order to build up a simulation environment of the 3D surface scanning system.

並列關鍵字

3D surface scanner ； simulation

參考文獻

[1] G. Sansoni, S. Corini, S. Lazzari, R. Rosedda, F. Docchio, “3D Imaging based on Gray code light projection：Characterization of the measuring algorithm and development of a measuring system for industrial application,” Applied Optics, Vol. 36, pp.4463-4472, 1997.

[2] D. Skocaj, A. Leonardis, “Range image acquisition of objects with non-uniform albedo using structured light range sensor,” in：Proceedings of the 15th International Conference on Pattern Recognition, Vol. 1, 2000, pp. 778--781.

[3] T. G.. Stahs, F. M. Wahl, “Fast and robust range data acquisition in a low-cast environment,” Proceeding of the ISPRS-Conference：Close-Range Photogrammetry meets Machin Vision, 1395, SPIE, pp.496-503, 1990.

[4] G. Sansoni, M Carocci, R Rodella, “3D vision based on the combination of gray code and phase shift light projection：Analysis and compensation of the systematic errors,” Applied Optics, Vol. 36, pp.6565-6573, 1999.

[5] J. Gühring, “Dense 3-D surface acquisition by structured light using off-the-shelf component,” Proceeding of SPIE Photonics West, Videometrics VII, Vol.4309, pp.220-231, 2001.