基于数字光栅投影的结构光三维测量技术与系统研究
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摘要
相位测量轮廓术是目前使用最为广泛的一种结构光三维形貌测量技术，在工业检测、质量控制、逆向设计、医学、虚拟现实、文物数字化和人体测量等众多领域具有广泛的应用前景。现有的商品化相位测量设备多使用物理光栅作为光栅图像投射装置，开发和使用成本昂贵，限制了该技术在中小企业的推广和应用。为此，本文对基于数字光栅投影的相位测量轮廓术中的相位计算、相位误差补偿、系统参数标定、相位-高度映射和彩色纹理获取等关键问题进行系统研究，力图开发出适合中小企业的低成本、高精度、高稳定性的，可同时获取被测物体三维形貌和彩色纹理的结构光三维测量系统，并扩展其应用范围。
相位计算包括相位主值计算和相位展开两个过程，是相位测量轮廓术的基础内容。本文系统介绍了现有的相位移原理和相位展开算法，并在对比各算法优缺点的基础上，选择使用四步相移算法和多频外差原理进行相位主值计算和相位展开，并通过实验验证了本文所选的算法能够准确的完成复杂物体和表面不连续物体的相位计算。
在相位计算过程中，光栅图像非正弦化是相位误差的主要来源。本文系统阐述了光栅图像的非正弦化过程，通过理论分析、模拟实验和实际测量，分析了非正弦化引起的相位误差的特征，并在此基础上，提出了一种基于相位误差查找表的通用相位误差补偿算法。实验结果表明本文算法能够有效减小相位误差、提高测量精度。
系统参数标定是结构光三维测量技术中的关键问题之一，其标定精度直接决定后续三维重建的精度。为此，本文提出了一种简单、高精度的系统参数标定算法。该算法通过建立精确的相机图像与投影仪图像的对应关系，赋予投影仪间接“拍摄”圆形标定点圆心坐标的能力，从而将复杂的投影仪参数标定问题转化为成熟的摄像机参数标定，并将整个测量系统的参数标定转换为成熟的双目立体视觉系统的参数标定。此算法简单、有效，标定精度高，标定后系统的绝对测量精度可达0．05mm，相对测量精度可达1：5000。
虽然上述系统参数标定算法可以得到较高的测量精度，但是标定过程中很难为系统(尤其是投影仪)找到一种完全合适的投影模型，从而限制了测量精度的进一步提高。为此，本文尝试利用神经网络强大的函数逼近能力来建立系统的相位-高度映射关系。介绍了本算法所使用的神经网络结构和训练原理，并详细说明了样本采集的过程。通过对比误差补偿前后神经网络训练的收敛速度和训练精度，证明了由光栅图像非正弦化引起的相位误差对网络训练精度有明显影响，该对比实验同时也证明了本算法由于在样本采集和后续测量过程中可以方便的对相位误差进行补偿，不受光栅图像非正弦化的影响，稳定性强。最后通过测量实验对比了本算法和系统标定算法的测量精度，实验结果表明基于神经网络的相位-高度映射算法的测量精度更高。
在文物复制、医学图像、虚拟现实等领域，彩色纹理也包含了非常重要的信息，因此在测量被测物体三维形貌的同时还要获取物体表面的彩色纹理。本文在色彩空间定义的启发下，使用三种颜色的图像来合成被测物体的彩色纹理，赋予黑白相机获取彩色纹理的能力，并提出了一种简单的彩色纹理优化算法来改善彩色纹理的质量。
以上研究构成了一套完整的基于数字光栅投影的结构光三维测量技术，为结构光三维测量系统的开发奠定了理论和技术基础。本文在上述技术基础上，开发出两款不同规格的结构光三维测量系统，并在工业检测、人体测量、文物数字化等领域得到推广应用。实际应用效果表明，所开发的结构光三维测量系统性能优越，价格优势明显，市场潜力巨大。
Phase measuring profilometry is one of the most widly used structured light 3D measuring techniques, it has huge potential for applications in many areas, including industrial inspection, product quality control, reverse engineering, medicine, virtual reality, culture heritage and human body measurement etc. Most commercial phase measuring systems employ expensive physical grating to project fringe images. The high production cost limits their application in numerous small and medium-sized enterprises. Therefore, we systematic research the key techniques of the structure lighted system based on digital fringe projection, including phase calculation, phase error compensation, system parameters calibration, phase-heigt mapping and color texture acquisition, and dedicate to develop low cost, high accurate and high stability structured light 3D measuring system, which is suitable for small and medium-sized enterprises, and extent its application ranges.
Phase calculation, including relative phase calculation and phase unwrapping, is the basic of the phase measurement technique. We describe phase-shifting method and phase unwrapping algorithm, and choose four-step phase-shifting method and multi-frequency heterodyne principle as the calculation method. Experimental results demonstrate that the method can accomplish phase calculation of complex and discontinuous objects with high precision.
During the actual phase calculation process, the non-sinusoidal attribute of the captured fringe image, caused by the gamma nonlinear of the DLP projector and the nonlinear response of the CCD camera, is the mainly error source. The non-sinusoidal process is described, and the phase error attributes is analyzed through theoretical analysis, simulation experiment and practical measurement. A general phase error compensation algorithm based on phase error look-up-table is proposed, our experimental results demonstrate that by using the proposed method the phase error is extremely reduced.
System parameters calibration is one of the key issues in the structured light system. We propose a simple and high accurate system calibration method. This method endows the projector capturing capabilities by establishing the correspondence between camera pixels and projector pixels. It treats the projector as a camera to unify the calibration procedures of a structured light system and a classic stereo vision system. This method is simple and effective, the calibration precision can achieve 0.26 pixels, the absolute measurement accuracy is 0.05mm, and relative accuracy is 1:5000.
Though this system calibration method is quite simple and fast, it is difficult to find the best camera model for the system, especially for the projector, thus the calibration precision of this kind of method is still limited. Therefore, a neural network, which has powerful ability of function approximation, is employed to solve the complex nonlinear phase-height mapping issue. The structure of the neural network and the training principle is introduced. By comparing the convergence rate and training precision of the neural network before and after phase error compensation, we indicates that phase error influences the precision of the trained network, so phase error compensation is necessary. On the other hand, as the phase error can be compensated during sample data set collection, this phase-height mapping method is not sensitive to the non-sinusoidal attribute of the fringe image. The 3D measurement experiments demonstrate that the neural network method can achieve higher measurement precision.
In the fields of culture heritage, medical imaging, and virtual reality etc, color textures have important information, so the 3-D measurement systems are required to acquire the 3-D shape and color texture, simultaneously. Inspired by color-space definition, we use three color images to combine the color texture of the target, and a simple white balance algorithm is proposed to optimize the color texture.
Based on above key techniques, we have developed two types of structured light system, and they have been used in industrial inspection, human body measurement and culture heritage etc. The practical applications indicate the developed structured 3D measurement system is characterized with predominant performance, obvious price advantages and great marketing potential.
相位计算包括相位主值计算和相位展开两个过程，是相位测量轮廓术的基础内容。本文系统介绍了现有的相位移原理和相位展开算法，并在对比各算法优缺点的基础上，选择使用四步相移算法和多频外差原理进行相位主值计算和相位展开，并通过实验验证了本文所选的算法能够准确的完成复杂物体和表面不连续物体的相位计算。
在相位计算过程中，光栅图像非正弦化是相位误差的主要来源。本文系统阐述了光栅图像的非正弦化过程，通过理论分析、模拟实验和实际测量，分析了非正弦化引起的相位误差的特征，并在此基础上，提出了一种基于相位误差查找表的通用相位误差补偿算法。实验结果表明本文算法能够有效减小相位误差、提高测量精度。
系统参数标定是结构光三维测量技术中的关键问题之一，其标定精度直接决定后续三维重建的精度。为此，本文提出了一种简单、高精度的系统参数标定算法。该算法通过建立精确的相机图像与投影仪图像的对应关系，赋予投影仪间接“拍摄”圆形标定点圆心坐标的能力，从而将复杂的投影仪参数标定问题转化为成熟的摄像机参数标定，并将整个测量系统的参数标定转换为成熟的双目立体视觉系统的参数标定。此算法简单、有效，标定精度高，标定后系统的绝对测量精度可达0．05mm，相对测量精度可达1：5000。
虽然上述系统参数标定算法可以得到较高的测量精度，但是标定过程中很难为系统(尤其是投影仪)找到一种完全合适的投影模型，从而限制了测量精度的进一步提高。为此，本文尝试利用神经网络强大的函数逼近能力来建立系统的相位-高度映射关系。介绍了本算法所使用的神经网络结构和训练原理，并详细说明了样本采集的过程。通过对比误差补偿前后神经网络训练的收敛速度和训练精度，证明了由光栅图像非正弦化引起的相位误差对网络训练精度有明显影响，该对比实验同时也证明了本算法由于在样本采集和后续测量过程中可以方便的对相位误差进行补偿，不受光栅图像非正弦化的影响，稳定性强。最后通过测量实验对比了本算法和系统标定算法的测量精度，实验结果表明基于神经网络的相位-高度映射算法的测量精度更高。
在文物复制、医学图像、虚拟现实等领域，彩色纹理也包含了非常重要的信息，因此在测量被测物体三维形貌的同时还要获取物体表面的彩色纹理。本文在色彩空间定义的启发下，使用三种颜色的图像来合成被测物体的彩色纹理，赋予黑白相机获取彩色纹理的能力，并提出了一种简单的彩色纹理优化算法来改善彩色纹理的质量。
以上研究构成了一套完整的基于数字光栅投影的结构光三维测量技术，为结构光三维测量系统的开发奠定了理论和技术基础。本文在上述技术基础上，开发出两款不同规格的结构光三维测量系统，并在工业检测、人体测量、文物数字化等领域得到推广应用。实际应用效果表明，所开发的结构光三维测量系统性能优越，价格优势明显，市场潜力巨大。
Phase measuring profilometry is one of the most widly used structured light 3D measuring techniques, it has huge potential for applications in many areas, including industrial inspection, product quality control, reverse engineering, medicine, virtual reality, culture heritage and human body measurement etc. Most commercial phase measuring systems employ expensive physical grating to project fringe images. The high production cost limits their application in numerous small and medium-sized enterprises. Therefore, we systematic research the key techniques of the structure lighted system based on digital fringe projection, including phase calculation, phase error compensation, system parameters calibration, phase-heigt mapping and color texture acquisition, and dedicate to develop low cost, high accurate and high stability structured light 3D measuring system, which is suitable for small and medium-sized enterprises, and extent its application ranges.
Phase calculation, including relative phase calculation and phase unwrapping, is the basic of the phase measurement technique. We describe phase-shifting method and phase unwrapping algorithm, and choose four-step phase-shifting method and multi-frequency heterodyne principle as the calculation method. Experimental results demonstrate that the method can accomplish phase calculation of complex and discontinuous objects with high precision.
During the actual phase calculation process, the non-sinusoidal attribute of the captured fringe image, caused by the gamma nonlinear of the DLP projector and the nonlinear response of the CCD camera, is the mainly error source. The non-sinusoidal process is described, and the phase error attributes is analyzed through theoretical analysis, simulation experiment and practical measurement. A general phase error compensation algorithm based on phase error look-up-table is proposed, our experimental results demonstrate that by using the proposed method the phase error is extremely reduced.
System parameters calibration is one of the key issues in the structured light system. We propose a simple and high accurate system calibration method. This method endows the projector capturing capabilities by establishing the correspondence between camera pixels and projector pixels. It treats the projector as a camera to unify the calibration procedures of a structured light system and a classic stereo vision system. This method is simple and effective, the calibration precision can achieve 0.26 pixels, the absolute measurement accuracy is 0.05mm, and relative accuracy is 1:5000.
Though this system calibration method is quite simple and fast, it is difficult to find the best camera model for the system, especially for the projector, thus the calibration precision of this kind of method is still limited. Therefore, a neural network, which has powerful ability of function approximation, is employed to solve the complex nonlinear phase-height mapping issue. The structure of the neural network and the training principle is introduced. By comparing the convergence rate and training precision of the neural network before and after phase error compensation, we indicates that phase error influences the precision of the trained network, so phase error compensation is necessary. On the other hand, as the phase error can be compensated during sample data set collection, this phase-height mapping method is not sensitive to the non-sinusoidal attribute of the fringe image. The 3D measurement experiments demonstrate that the neural network method can achieve higher measurement precision.
In the fields of culture heritage, medical imaging, and virtual reality etc, color textures have important information, so the 3-D measurement systems are required to acquire the 3-D shape and color texture, simultaneously. Inspired by color-space definition, we use three color images to combine the color texture of the target, and a simple white balance algorithm is proposed to optimize the color texture.
Based on above key techniques, we have developed two types of structured light system, and they have been used in industrial inspection, human body measurement and culture heritage etc. The practical applications indicate the developed structured 3D measurement system is characterized with predominant performance, obvious price advantages and great marketing potential.
引文
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