基于计算机微视觉的微运动测量关键技术研究
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摘要
现代科学技术正迅速向微小、超精密领域发展,由微米级、亚微米级进入到纳米级阶段。随着微纳制造、微电子、生物医学工程等技术的高速发展,对微运动测量技术提出了更高的要求。研制高精度的新测量手段已经成为微纳制造及生物医学等技术发展的迫切需要。计算机微视觉方法以其柔性、快速、非接触、精确、自动化程度高等特点,在精密测量领域受到了越来越高的重视。本文研究利用计算机微视觉方法进行高精度的微运动测量,主要研究内容如下：
首先,深入研究计算机微视觉测量系统方案及硬件组成,系统分析了光源对成像质量的影响,讨论了计算机微视觉系统采集的图像信号和噪声的特性,并分析了减少微视觉图像噪声的主要方法。
其次,针对光照变化、噪声及大位移量等严重影响基于计算机微视觉的微运动测量精度的问题,提出了三种高精度的鲁棒运动估计算法：
(1)根据微视觉的成像模型,提出一种基于同态滤波的鲁棒多尺度微运动测量算法。首先采用同态滤波增强方法对显微视觉图像亮度不均匀进行了校正,并增强对比度,然后利用双权重函数,自动调节不同残差数据点的权重,去除残差过大的数据点,并采用多尺度金字塔由粗到精逐层迭代,精确地估计运动矢量。实验模拟表明提出的算法鲁棒性好,能有效地减弱在基于计算机微视觉的微运动测量中光照非一致分布的影响,同时减少噪声引起的界外值的干扰,提高了运动估计的精度。
(2)根据基于图像结构的模型,提出一种用于光照变化和低信噪比条件下的基于单演相位的鲁棒运动估计算法。在该算法中,传统的亮度不变假设将被单演相位不变的假设所代替。单演信号是首个旋转不变的二维解析信号。通过单演信号,图像的多尺度局部相位能够以旋转不变的方式获得。由于单演相位包含了图像的结构信息,具有对光照变化及噪声干扰都非常鲁棒的优点,所以该方法结合多尺度金字塔迭代方法和鲁棒估计方法用于运动估计,进一步提高了光照变化和低信噪比条件下的运动估计精度。实验模拟验证了该算法的良好性能。
(3)采用相关方法,设计一种基于单演曲率张量与数字图像相关的运动估计算法。在该算法中,先用单演曲率张量来提取图像的1维和2维结构信息,利用图像结构在光照变化下保持不变的优点,提高在光照不均匀条件下的运动估计精度。然后采用相关方法获得整像素的运动位移,在此基础上,将基于梯度的亚像素位移算法结合鲁棒估计方法,以减少噪声对运动估计精度的影响,并获得亚像素的位移矢量。实验模拟测试验证了该算法不但适于在光照不均匀和噪声环境下进行刚体的运动估计,也适于变形物体的位移场估计。
最后,以精密定位平台为测量对象,采用提出的运动估计算法对其平移微运动和旋转微运动进行了测量,实验验证了本文所提出的理论和方法是可行的,有效地实现了在光照变化及噪声环境下的高精度运动估计。
Modern science and technology is rapidly developing to tiny, ultra-precision field from micron, submicron into the nanoscale stage. With the fast development of the technologies such as micro/nano manufacturing, microelectronics and biomedicine, micro-motion measurement is strongly demanded. Novel high-precision measurement methods are hence in urgent need for micro/nano manufacturing and biomedicine. Computer micro-vision method has been increasing attention in the field of precision measurement for its flexible, rapid, non-contact, precision and high degree of automation. This thesis focuses on micro-motion measurement with high accuracy using computer micro-vision approach. The main contributions of this thesis are listed as follows:
First, the computer micro-vision measurement system scheme and its hardware components are in-depth studied, the effects of light source on the imaging quality are systematically analyzed, the properties of the acquired images and the noises introduced by the computer microvision system are explored, and the main approaches to attenuating these noises are analyzed.
Second, Aiming at the problem of illumination variation, noise and large displacement that may badly influence motion estimation precision in micro-motion measurement based on computer microvision. Three kinds of high-precision robust motion estimation algorithm are proposed:
(1) According to the imaging model of micro-vision, a robust multi-scale micro-motion measurement algorithm based on homomorphic filtering is proposed. First, a method of homomorphic filtering for image enhancement is used to correct the uneven brightness of micro-vision image and enhance contrast. Then biweight function is used to automatically adjust the weight of data with different residual error and to remove those data with excessive residual errors, and a multi-scale pyramid is employed to accurately estimate the motion vector by an iteration gradually from coarseness to fine. Experimental simulation show the new algorithm has good robustness, it can effectively weaken the influence of uneven illumination in micro-motion measurement based on computer micro-vision and reduce the interference of outliers caused by noises, and the accuracy of micro-motion measurement is improved.
(2) According to the model based on image structure, an integrated approach of robust motion estimation based on constancy assumption of monogenic phase was proposed, which use for illumination changes and low SNR. The monogenic signal is the first rotation invariant two-dimensional analytic signal. Its phase information includes structural information and has the advantage of being robust to illumination changes and noise interferences. Therefore, the method combines multi-scale pyramid iterative methods and robust estimation methods for motion estimation would further improve the motion estimation accuracy under illumination changes and low SNR conditions. Experimental simulations verify the good performance of the algorithm.
(3)A motion estimation algorithm based on monogenic curvature tensor and digital image correlation is designed by using correlation method. In the algorithm, first 1D and 2D structural information of the image is extracted by monogenic curvature tensor to improve motion estimation accuracy under uneven illumination by using the advantage of image structure being invariant to illumination change. Then, motion displacement of integer pixel is obtained by correlation method. On this basis, the gradient-based sub-pixel displacement estimation algorithm combined with robust methods to reduce the effect of noise on the accuracy of motion estimation and obtain sub-pixel displacement vector. Experimental simulations verify that the algorithm can not only be suitable for rigid body motion estimation in uneven illumination and noise conditions, but also be suitable for displacement field estimation of deformation objects.
Finally, using the precision positioning stage as measurement objects, translation and rotation micro-motions are measured using the proposed methods. Experiment results verify the theory and methods in this thesis are feasible and effectively achieve the high-precision motion estimation in illumination variation and noise conditions.
首先,深入研究计算机微视觉测量系统方案及硬件组成,系统分析了光源对成像质量的影响,讨论了计算机微视觉系统采集的图像信号和噪声的特性,并分析了减少微视觉图像噪声的主要方法。
其次,针对光照变化、噪声及大位移量等严重影响基于计算机微视觉的微运动测量精度的问题,提出了三种高精度的鲁棒运动估计算法：
(1)根据微视觉的成像模型,提出一种基于同态滤波的鲁棒多尺度微运动测量算法。首先采用同态滤波增强方法对显微视觉图像亮度不均匀进行了校正,并增强对比度,然后利用双权重函数,自动调节不同残差数据点的权重,去除残差过大的数据点,并采用多尺度金字塔由粗到精逐层迭代,精确地估计运动矢量。实验模拟表明提出的算法鲁棒性好,能有效地减弱在基于计算机微视觉的微运动测量中光照非一致分布的影响,同时减少噪声引起的界外值的干扰,提高了运动估计的精度。
(2)根据基于图像结构的模型,提出一种用于光照变化和低信噪比条件下的基于单演相位的鲁棒运动估计算法。在该算法中,传统的亮度不变假设将被单演相位不变的假设所代替。单演信号是首个旋转不变的二维解析信号。通过单演信号,图像的多尺度局部相位能够以旋转不变的方式获得。由于单演相位包含了图像的结构信息,具有对光照变化及噪声干扰都非常鲁棒的优点,所以该方法结合多尺度金字塔迭代方法和鲁棒估计方法用于运动估计,进一步提高了光照变化和低信噪比条件下的运动估计精度。实验模拟验证了该算法的良好性能。
(3)采用相关方法,设计一种基于单演曲率张量与数字图像相关的运动估计算法。在该算法中,先用单演曲率张量来提取图像的1维和2维结构信息,利用图像结构在光照变化下保持不变的优点,提高在光照不均匀条件下的运动估计精度。然后采用相关方法获得整像素的运动位移,在此基础上,将基于梯度的亚像素位移算法结合鲁棒估计方法,以减少噪声对运动估计精度的影响,并获得亚像素的位移矢量。实验模拟测试验证了该算法不但适于在光照不均匀和噪声环境下进行刚体的运动估计,也适于变形物体的位移场估计。
最后,以精密定位平台为测量对象,采用提出的运动估计算法对其平移微运动和旋转微运动进行了测量,实验验证了本文所提出的理论和方法是可行的,有效地实现了在光照变化及噪声环境下的高精度运动估计。
Modern science and technology is rapidly developing to tiny, ultra-precision field from micron, submicron into the nanoscale stage. With the fast development of the technologies such as micro/nano manufacturing, microelectronics and biomedicine, micro-motion measurement is strongly demanded. Novel high-precision measurement methods are hence in urgent need for micro/nano manufacturing and biomedicine. Computer micro-vision method has been increasing attention in the field of precision measurement for its flexible, rapid, non-contact, precision and high degree of automation. This thesis focuses on micro-motion measurement with high accuracy using computer micro-vision approach. The main contributions of this thesis are listed as follows:
First, the computer micro-vision measurement system scheme and its hardware components are in-depth studied, the effects of light source on the imaging quality are systematically analyzed, the properties of the acquired images and the noises introduced by the computer microvision system are explored, and the main approaches to attenuating these noises are analyzed.
Second, Aiming at the problem of illumination variation, noise and large displacement that may badly influence motion estimation precision in micro-motion measurement based on computer microvision. Three kinds of high-precision robust motion estimation algorithm are proposed:
(1) According to the imaging model of micro-vision, a robust multi-scale micro-motion measurement algorithm based on homomorphic filtering is proposed. First, a method of homomorphic filtering for image enhancement is used to correct the uneven brightness of micro-vision image and enhance contrast. Then biweight function is used to automatically adjust the weight of data with different residual error and to remove those data with excessive residual errors, and a multi-scale pyramid is employed to accurately estimate the motion vector by an iteration gradually from coarseness to fine. Experimental simulation show the new algorithm has good robustness, it can effectively weaken the influence of uneven illumination in micro-motion measurement based on computer micro-vision and reduce the interference of outliers caused by noises, and the accuracy of micro-motion measurement is improved.
(2) According to the model based on image structure, an integrated approach of robust motion estimation based on constancy assumption of monogenic phase was proposed, which use for illumination changes and low SNR. The monogenic signal is the first rotation invariant two-dimensional analytic signal. Its phase information includes structural information and has the advantage of being robust to illumination changes and noise interferences. Therefore, the method combines multi-scale pyramid iterative methods and robust estimation methods for motion estimation would further improve the motion estimation accuracy under illumination changes and low SNR conditions. Experimental simulations verify the good performance of the algorithm.
(3)A motion estimation algorithm based on monogenic curvature tensor and digital image correlation is designed by using correlation method. In the algorithm, first 1D and 2D structural information of the image is extracted by monogenic curvature tensor to improve motion estimation accuracy under uneven illumination by using the advantage of image structure being invariant to illumination change. Then, motion displacement of integer pixel is obtained by correlation method. On this basis, the gradient-based sub-pixel displacement estimation algorithm combined with robust methods to reduce the effect of noise on the accuracy of motion estimation and obtain sub-pixel displacement vector. Experimental simulations verify that the algorithm can not only be suitable for rigid body motion estimation in uneven illumination and noise conditions, but also be suitable for displacement field estimation of deformation objects.
Finally, using the precision positioning stage as measurement objects, translation and rotation micro-motions are measured using the proposed methods. Experiment results verify the theory and methods in this thesis are feasible and effectively achieve the high-precision motion estimation in illumination variation and noise conditions.
引文
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