基于投影强度的快速高动态范围三维形状测量

周国平; 朱文韬; 易传华; 曾龙辉; 黄舒欣; 祝振敏

doi:10.5768/JAO202344.0103009

基于投影强度的快速高动态范围三维形状测量

doi: 10.5768/JAO202344.0103009

1.
江西省水投建设集团有限公司，江西南昌 330029
2.
华东交通大学电气与自动化工程学院，江西南昌 330013

基金项目: 国家自然科学基金项目（52065024）;江西省重点研发计划（20202BBE53022）;江西省03专项（20212ABC03A20）

详细信息

作者简介:
周国平（1970—），男，研究生，工程师，主要从事偏振结构光三维测量等技术研究。E-mail：156185231@qq.com

通讯作者:
祝振敏(1984—)，男，博士，教授，硕、博士生导师，主要从事偏振结构光三维测量等方面的教学与科研工作。E-mail：zhuzhenmin1984@163.com

中图分类号: TN247
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- PDF下载量: 17
- 被引次数: 0
出版历程
- 收稿日期: 2022-04-11
- 修回日期: 2022-08-29
- 网络出版日期: 2022-09-17
- 刊出日期: 2023-01-17

3D shape measurement in fast high dynamic range based on projection intensity

1.
Jiangxi Water Investment Construction Group Co.,Ltd., Nanchang 330029, China
2.
School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang 330013, China

摘要

摘要: 条纹投影轮廓术由于具有速度快、精度高、对环境光照和表面纹理具有鲁棒性等优点，在许多领域得到了广泛应用。但是，它容易受到高动态范围（high dynamic range, HDR）对象的影响。因此提出了一种快速计算最佳投影亮度的方法。通过求解相机与投影仪之间的响应关系，结合所提出的一个简便的投影亮度确定方法，可以得到测量所需要的投影亮度。再基于所提出的图像融合算法融合求得的各个亮度下的原始图片，从而获得高质量的融合图片，实现对HDR物体的高精度的三维重构。相较于传统方法，无需盲目投射和拍摄大量图片或计算复杂的单应性矩阵，仅需要投影一张均匀白光至被测物体，即可快速求解出相机和投影仪之间的响应函数，从而获得所需的投影亮度，使得测量速度有极大的提升。
- 机器视觉 /
- 投影强度 /
- 三维测量 /
- 相机响应函数
Abstract: Fringe projection profilometry is widely used in many fields due to its advantages of high speed, high accuracy, and robustness to ambient lighting and surface textures. However, it is susceptible to high dynamic range (HDR) objects. Therefore, a method to quickly calculate the optimal projected brightness was proposed. By solving the response relationship between camera and projector, and combined with a proposed simple method of projection brightness determination, the required projection brightness could be obtained. Then, based on the proposed image fusion algorithm, the obtained original images under each brightness were fused to obtain high-quality fused images and achieve high-precision three-dimensional reconstruction of HDR objects. Compared with the traditional methods, there was no need to blindly project and take a large number of pictures or calculate complex homography matrices. It only needed to project a uniform white light to the measured object, and the response function between the camera and the projector could be quickly solved, so as to obtain the required projection brightness, which greatly improved the measurement speed.
- machine vision /
- projection intensity /
- 3D measurement /
- camera response function

HTML全文

图 1 进入相机的光线组成

Fig. 1 Composition diagram of light to enter camera

下载: 全尺寸图片幻灯片

图 2 像素分布曲线图

Fig. 2 Curves of pixel distribution

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图 3 测量系统

Fig. 3 Physical picture of measurement system

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图 4 不同投影亮度的图像。

Fig. 4 Images with different projection brightness

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图 5 投影亮度为140的图像

Fig. 5 Image with projection brightness of 140

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图 6 相机与投影仪的响应分布曲线

Fig. 6 Response distribution curves of camera and projector

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图 7 4幅不同投影亮度的图像

Fig. 7 Four images with different projection brightness

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图 8 融合图像及其像素分布直方图

Fig. 8 Fused image and histogram of pixel distribution

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图 9 融合图像及各个投影强度下的图像的频率分布

Fig. 9 Frequency distribution diagram of fused image and images under various projection intensities

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图 10 三维重构结果

Fig. 10 Diagram of 3D reconstruction results

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表 1 多组图像对的信噪比

Table 1 Signal-to-noise ratio of multiple image pairs

图像 SNR

融合图片 15.09
投影亮度255图片 16.53
投影亮度140图片 13.30
投影亮度100图片 2.05

下载: 导出CSV

参考文献(15)

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