基于相移轮廓术的三维形貌与颜色纹理的同步捕获

王素珍; 仵苇; 季怡心; 张龙祥; 王建华

doi:10.37188/CO.EN-2025-0014

基于相移轮廓术的三维形貌与颜色纹理的同步捕获

青岛理工大学信息与控制工程学院, 山东青岛 266520

详细信息

中图分类号: TP391.41
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出版历程
- 收稿日期: 2025-03-01
- 录用日期: 2025-07-03
- 网络出版日期: 2025-07-22

Synchronized capture of 3D shape and color texture based on phase-shifting profilometry

doi: 10.37188/CO.EN-2025-0014

School of Information and Control Engineering, Qingdao University of Technology, Qingdao 266520, China

Funds: Supported by Natural Science Foundation of Shandong Province (No. ZR2021MF024)

More Information

Author Bio:
WANG Su-zhen (1975—) received her M.S. degree in environment engineering from Ocean University of China, Qing Dao, China, in 2003 and a Ph.D. degree in environment engineering from Ocean University of China, Qing Dao, China, in 2006. Now she is an associate professor in Qingdao University of Technology. Her research interests include internet of things, intelligent control, digital twin, and machine vision. E-mail: 417322899@qq.com

WANG Jian-hua (1981—) received his B. Sc. degree in 2004 from China University of Geosciences, received his M. Sc. degree in 2011 from China University of Mining and Technology, received his Ph. D. degree in 2019 from Xi’an University of Technology. Now he is an associate professor in Qingdao University of Technology. His research interests include optical 3D measurement and automation control. E-mail: wjh051130@163.com

Corresponding author: wjh051130@163.com

摘要

摘要:
近年来，文化遗产保护、医疗等多个领域对物体三维(3D)形貌与颜色纹理同步获取的需求持续攀升。为响应当前技术需求，本文提出了一种三维形貌与颜色纹理同步捕获的新方法，首先构建了相机曝光时间与灰度值关联的线性模型；随后通过曝光时间校准，使投影红绿蓝(RGB)光与单色相机捕获的白光灰度值趋于一致；接着向物体投射三组彩色条纹，以筛选适用于3D重建的最优像素；同时投射三张纯色图像，通过图像合成获得颜色纹理。实验结果表明，该方法能够有效实现三维形貌与颜色纹理的同步获取，且测量速度快，精度高，同时使用黑白相机避免了彩色物体三维重建过程中常见的颜色串扰等问题的干扰。
- 三维形貌 /
- 黑白相机 /
- RGB光投影
Abstract:
In recent years, the demand for synchronous acquisition of three-dimensional (3D) shape and color texture has surged in fields such as cultural heritage preservation and healthcare. Addressing this need, this paper proposes a novel method for simultaneous 3D shape and color texture capture. First, a linear model correlating camera exposure time with grayscale values is established. Through exposure time calibration, the projected red, green and blue (RGB) light and white-light grayscale values captured by a monochrome camera are aligned. Then, three sets of color fringes are projected onto the object to identify optimal pixels for 3D reconstruction. And, three pure-color patterns are projected to synthesize the color texture. Experimental results show that this method effectively achieves synchronous 3D shape and color texture acquisition, offering high speed and precision. And using a monochrome camera avoids color crosstalk interference common in 3D reconstruction of colored objects.
- three-dimensional shape /
- monochrome camera /
- RGB light projection.

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Figure 1. Schematic diagram of structured light 3D measurement system

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Figure 2. Spectral response curve of the camera

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Figure 3. Principle of three primary colors addition

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Figure 4. Images captured using white light and RGB light projection. (a) Image of a whiteboard under white light projection. (b) Image of a whiteboard under red light projection. (c) Image of a whiteboard under green light projection. (d) Image of a whiteboard under blue light projection. (e) Grayscale values of the rows corresponding to the locations of the red dotted lines in Fig. 4(a)-(d).

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Figure 5. Contrast and brightness of the captured image. (a) The object being measured. (b) The object being measured under white light projection. (c) Grayscale values of the pixels in the row corresponding to the red dashed line in Fig. 5(b).

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Figure 6. Camera characteristics at different exposure times

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Figure 7. Grayscale values and color texture of the image after adjusting the exposure time. (a) Image of the whiteboard captured using white light projection after adjusting the exposure time. (b) Image of the whiteboard captured using red light projection after adjusting the exposure time. (c) Image of the whiteboard captured using green light projection after adjusting the exposure time. (d) Image of the whiteboard captured using blue light projection after adjusting the exposure time. (e) The grayscale values of the rows corresponding to the locations of the red dotted lines in Figs. 7 (a)-(d). (f) The color texture of the captured measured object. (g) The extraction of grayscale values from the row indicated by the red dashed line in Fig. 7(d) under both white light and RGB light projections.

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Figure 8. Selection of the optimal fringe

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Figure 9. Reconstructed object surface. (a) The measured object. (b) Reconstructed object surface under red light projection. (c) Reconstructed object surface under green light projection. (d) Reconstructed object surface under blue light projection. (e) Reconstructed object surface using the proposed method. (f) Reconstructed object surface with color texture.

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Figure 10. Results of 3D reconstruction of the object surface. (a) The measured object. (b) Reconstructed object surface under red light projection. (c) Reconstructed object surface under green light projection. (d) Reconstructed object surface under blue light projection. (e) Reconstructed object surface using the proposed method. (f) Reconstructed object surface with color texture.

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