基于标记约束的三维曲面拼接方法研究
摘要
大型物体数字化采用视觉测量的手段来实现,为获得较高的测量精度,往往需要分块测量,利用三维曲面拼接技术将区域数据进行整合拼接,实现物体整体形貌测量。测量回转体时,因回转体各部分相互遮挡,从任何测量角度都无法实现一次完成整个回转体的三维测量工作。因此,三维曲面拼接技术是实现物体形貌测量的关键技术。
本课题组前期工作提出了基于符号M阵列结构光的三维检测方法,实现了二值光源投射下动态场景的检测与三维重建。为了将该三维检测方法应用于三维拼接,本文对三维拼接方法进行研究。同时为满足对不具有明显表面特征、不宜采用自由拼接的物体的测量和拼接,本文提出了一种基于标记约束的三维曲面拼接方法。该方法在检测对象上设置1组标记,通过提取标记,获得标记的图像坐标,进而求解标记的世界坐标,由标记的世界坐标解出变换矩阵,实现两个三维曲面的拼接。本文主要工作包括以下几个方面:
(1)改进三维标定和检测方法。为提高前期三维检测方法的精度,本文首先对三维检测方法进行改进。通过对标定数据的正确性进行检查,采用去极值求均值法矫正异常标定数据,解决因标定数据误差造成重建曲面噪声的问题。针对解码符号误匹配现象,提出窗口扩展匹配法,采用3×3窗口,降低因符号误识别破坏窗口唯一性的可能性,有效地解决符号误匹配问题。研究了适合面结构光三维检测重建曲面的平滑方法,根据检测对象表面平缓的特征,过滤曲率较大的尖锐噪声点,解决重建曲面上较大噪声无法平滑的问题,为后续拼接工作奠定基础。
(2)标记提取和匹配方法研究。考虑到标记在三维拼接中起决定性作用,为了确保标记被正确识别,研究了通过黄金分割搜索阈值方法对标记图像进行合理的阈值分割,通过扫描标记的白色连通域及其包含的黑色内连通域识别标记,该方法稳定性强。通过与提取出的标记图像坐标邻近的关键点世界坐标,按标记与这些关键点间图像距离比例进行估计标记的世界坐标。标记设置制约着标记匹配和变换矩阵求解,本文从便于标记匹配角度研究标记设置方法,且兼顾变换矩阵求解,使得标记匹配和变换矩阵求解工作变得容易。
(3)拼接方法研究。介绍变换矩阵求解过程,通过变换矩阵将待拼接曲面坐标系统一到参考曲面坐标系上。研究了在参考曲面坐标系下提取两个曲面的公共区域方法。并根据公共区域内检测点的世界坐标,提出了评判两个曲面是否配准方法。针对曲面未配准情况,研究了估计两个曲面夹角和位移的方法,通过多次对待拼接曲面旋转和平移,最终实现两曲面近似配准。
(4)三维曲面拼接实验。进行曲面拼接实验,并对实验结果及误差进行分析。
Digital morphology of large objects and closed surface can be realized by means of vision measurement, and it often needs to block measurement, the regional data is integrated by using three-dimensional image mosaic technique, realizing the overall morphology measurement of objects. Therefore, the three-dimensional image mosaic technique is a key technology to realize the object morphology measurement.
According to whether there have constraints, image mosaic technique can be divided into free mosaic and constraint-based mosaic. Free mosaic extracts the characteristic information to realize the image mosaic through the common part of the adjacent detection area, suitable for checking the obvious characteristics objects due to its flexible. However, several times of mosaic prone to cause cumulative errors. Constraint-based mosaic can be divided into sensor location constraint and image control point constraint according to the different ways of constraint. The sensor views the object from a different perspective, the relationship between two adjacent sensors’location is known, this approach often requires ancillary equipment to calibrate the relationship of sensor location, and the operation is more complicated. Image control point constraint can realize the integration of image data by using the tag information, which was added to the measurement object, it just depends on the tag information to carry out the space image mosaic, but the extraction of tag information is very complex, and the mosaic errors are larger, so it’s suitable for applications of less demanding to the mosaic accuracy.
As a foundation of three-dimensional image mosaic technique, the accuracy and robustness of the three-dimensional detection restricts the precision and success rate of the three-dimensional mosaic. The three-dimensional detection method based on the structure light of symbols M array was put forward by the research group, the detection of dynamic scene and three-dimensional reconstruction was realized under the projection of binary light. This method is used in certain occasions, it can measure the object for a single color, and the surface curvature must small, the angle among the detection objects, the projection devices and CCD must small, and the light must weak. Due to the characteristics of detection objects, which have the small surface curvature, free mosaic is not suitable.
Subject to the three-dimensional detection method based on the structure light of symbols M array that was put forward by the research group, a novel approach for three-dimensional image mosaic based on the mark constraint is put forward in this paper, which is based on the improvements of three-dimensional detection method. The method is set a group of markers on the detective object in order to get the marked image coordinate through extracting the markers, and then the marked world coordinate can be got, the transformation matrix can be solved by the world coordinates of markers, and then the three-dimensional image mosaic can be realized. This paper includes the following aspects:
(1) Improve the three-dimensional detection method. The correctness of the calibration data is inspected, and the correction calibration data method is proposed. The windowing extension matching method is proposed according to the phenomenon of the decoding symbol mismatch, which effectively solves the problem of symbol mismatching. A smooth method which is suitable for the reconstruction surfaces of structured light three-dimensional detection is studied, and the problem of large burr can not be smooth in the reconstruction surfaces is solved, so has laid the foundation for the following mosaic work.
(2) Study on marker extraction and matching method. Considering the marker plays a decisive role in three-dimensional mosaic, the marker extraction through the Golden Section methods to search threshold is studied in order to ensure there is no marker loss. Although this method’s efficiency is not high, it’s very stable. The world coordinates of the markers can be solved through the extracted markers image coordinates. Marker setting restricts marker matching and the transformation matrix solution, Marker setting is studied from the point of view of symbol matching, and the transformation matrix solution is also considered.
(3) Study on mosaic method. The solving process of transformation matrix is introduced; the coordinate system of the mosaic image is integrated into the reference image coordinate system through the transformation matrix. The method of extract the common region of two images under the reference image coordinate is studied. Whether the two images registration is proposed according to the world coordinates of the detective points in the common region. According to the image without registration, the method of calculates the angle and displacement between two images is studied; the two images’registration was finally realized through the rotation and translation of the mosaic image many times.
(4) The experiment of three-dimensional image mosaic. Image mosaic experiment was carried out, and the results of the experiment and the errors were analyzed.
本课题组前期工作提出了基于符号M阵列结构光的三维检测方法,实现了二值光源投射下动态场景的检测与三维重建。为了将该三维检测方法应用于三维拼接,本文对三维拼接方法进行研究。同时为满足对不具有明显表面特征、不宜采用自由拼接的物体的测量和拼接,本文提出了一种基于标记约束的三维曲面拼接方法。该方法在检测对象上设置1组标记,通过提取标记,获得标记的图像坐标,进而求解标记的世界坐标,由标记的世界坐标解出变换矩阵,实现两个三维曲面的拼接。本文主要工作包括以下几个方面:
(1)改进三维标定和检测方法。为提高前期三维检测方法的精度,本文首先对三维检测方法进行改进。通过对标定数据的正确性进行检查,采用去极值求均值法矫正异常标定数据,解决因标定数据误差造成重建曲面噪声的问题。针对解码符号误匹配现象,提出窗口扩展匹配法,采用3×3窗口,降低因符号误识别破坏窗口唯一性的可能性,有效地解决符号误匹配问题。研究了适合面结构光三维检测重建曲面的平滑方法,根据检测对象表面平缓的特征,过滤曲率较大的尖锐噪声点,解决重建曲面上较大噪声无法平滑的问题,为后续拼接工作奠定基础。
(2)标记提取和匹配方法研究。考虑到标记在三维拼接中起决定性作用,为了确保标记被正确识别,研究了通过黄金分割搜索阈值方法对标记图像进行合理的阈值分割,通过扫描标记的白色连通域及其包含的黑色内连通域识别标记,该方法稳定性强。通过与提取出的标记图像坐标邻近的关键点世界坐标,按标记与这些关键点间图像距离比例进行估计标记的世界坐标。标记设置制约着标记匹配和变换矩阵求解,本文从便于标记匹配角度研究标记设置方法,且兼顾变换矩阵求解,使得标记匹配和变换矩阵求解工作变得容易。
(3)拼接方法研究。介绍变换矩阵求解过程,通过变换矩阵将待拼接曲面坐标系统一到参考曲面坐标系上。研究了在参考曲面坐标系下提取两个曲面的公共区域方法。并根据公共区域内检测点的世界坐标,提出了评判两个曲面是否配准方法。针对曲面未配准情况,研究了估计两个曲面夹角和位移的方法,通过多次对待拼接曲面旋转和平移,最终实现两曲面近似配准。
(4)三维曲面拼接实验。进行曲面拼接实验,并对实验结果及误差进行分析。
Digital morphology of large objects and closed surface can be realized by means of vision measurement, and it often needs to block measurement, the regional data is integrated by using three-dimensional image mosaic technique, realizing the overall morphology measurement of objects. Therefore, the three-dimensional image mosaic technique is a key technology to realize the object morphology measurement.
According to whether there have constraints, image mosaic technique can be divided into free mosaic and constraint-based mosaic. Free mosaic extracts the characteristic information to realize the image mosaic through the common part of the adjacent detection area, suitable for checking the obvious characteristics objects due to its flexible. However, several times of mosaic prone to cause cumulative errors. Constraint-based mosaic can be divided into sensor location constraint and image control point constraint according to the different ways of constraint. The sensor views the object from a different perspective, the relationship between two adjacent sensors’location is known, this approach often requires ancillary equipment to calibrate the relationship of sensor location, and the operation is more complicated. Image control point constraint can realize the integration of image data by using the tag information, which was added to the measurement object, it just depends on the tag information to carry out the space image mosaic, but the extraction of tag information is very complex, and the mosaic errors are larger, so it’s suitable for applications of less demanding to the mosaic accuracy.
As a foundation of three-dimensional image mosaic technique, the accuracy and robustness of the three-dimensional detection restricts the precision and success rate of the three-dimensional mosaic. The three-dimensional detection method based on the structure light of symbols M array was put forward by the research group, the detection of dynamic scene and three-dimensional reconstruction was realized under the projection of binary light. This method is used in certain occasions, it can measure the object for a single color, and the surface curvature must small, the angle among the detection objects, the projection devices and CCD must small, and the light must weak. Due to the characteristics of detection objects, which have the small surface curvature, free mosaic is not suitable.
Subject to the three-dimensional detection method based on the structure light of symbols M array that was put forward by the research group, a novel approach for three-dimensional image mosaic based on the mark constraint is put forward in this paper, which is based on the improvements of three-dimensional detection method. The method is set a group of markers on the detective object in order to get the marked image coordinate through extracting the markers, and then the marked world coordinate can be got, the transformation matrix can be solved by the world coordinates of markers, and then the three-dimensional image mosaic can be realized. This paper includes the following aspects:
(1) Improve the three-dimensional detection method. The correctness of the calibration data is inspected, and the correction calibration data method is proposed. The windowing extension matching method is proposed according to the phenomenon of the decoding symbol mismatch, which effectively solves the problem of symbol mismatching. A smooth method which is suitable for the reconstruction surfaces of structured light three-dimensional detection is studied, and the problem of large burr can not be smooth in the reconstruction surfaces is solved, so has laid the foundation for the following mosaic work.
(2) Study on marker extraction and matching method. Considering the marker plays a decisive role in three-dimensional mosaic, the marker extraction through the Golden Section methods to search threshold is studied in order to ensure there is no marker loss. Although this method’s efficiency is not high, it’s very stable. The world coordinates of the markers can be solved through the extracted markers image coordinates. Marker setting restricts marker matching and the transformation matrix solution, Marker setting is studied from the point of view of symbol matching, and the transformation matrix solution is also considered.
(3) Study on mosaic method. The solving process of transformation matrix is introduced; the coordinate system of the mosaic image is integrated into the reference image coordinate system through the transformation matrix. The method of extract the common region of two images under the reference image coordinate is studied. Whether the two images registration is proposed according to the world coordinates of the detective points in the common region. According to the image without registration, the method of calculates the angle and displacement between two images is studied; the two images’registration was finally realized through the rotation and translation of the mosaic image many times.
(4) The experiment of three-dimensional image mosaic. Image mosaic experiment was carried out, and the results of the experiment and the errors were analyzed.
引文
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[3]H.J.Pahk, Development of computer aided inspection system with CMM for integrated mold manufacturing, Annals of the CIRP, 1993, (42)p:557-560
[4] A.Limaiem, H.A.Elmaraghy, Automatic path planning for coordinate measuring machines, Proc.of the 1998 IEEE Int.Conf.on Rob.&Auto, 1998(1)p:887-892
[5] Mattos, L., Grant, E.. Passive Sonar Applications: Target Tacking and Navigation of an Autonomous Robot[C]. Robotics and Automation, 2004. Proceedings. ICRA '04. 2004 IEEE International Conference on, Vol.5, April 26-May 1, 2004. p:4265– 4270
[6] Kao-Shing Hwang, Jeng-Yih Chiou, Ming-Yi Ju, Yuan-Sun Chu. Navigation Based on Sonar Sensing in a Partially Structured Environment[C]. Neural Networks and Signal Processing, 2003. Proceedings of the 2003 International Conference on, Vol.1, 14-17 Dec. 2003. p:454– 456
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