基于结构光扫描仪的数据配准关键技术研究

【作者】 刘晓烈；

【导师】 张维忠；

【作者基本信息】 青岛大学 ， 计算机应用技术， 2011， 硕士

【摘要】 逆向工程技术是进行产品设计,研究和创新的一项先进技术。从获取的三维点云数据出发,对三维点云数据进行处理是逆向工程领域中的关键技术之一,其中点云数据配准技术是数据处理中的重要组成部分,配准的精度直接决定着三维重建效果。本文对逆向工程技术中,三维点云数据的配准技术作了深入研究,重要过程主要涉及粗配准和精确配准。本文提出了一种基于标记点的快速点云数据配准技术,包括粗配准和精确配准。测量物体之前,在物体表面上粘贴标记点,利用结构光三维扫描仪对物体进行测量,得到递增式标记点和密集点云三维数据。采用递增式点云数据配准的优点是不要求新测量所得的标记点与前一次之间至少存在3组或3组以上的匹配点对,而是要求与之前所有的测量中所得的标记点存在3组或3组以上的匹配点对即可,此种方法增加了系统测量的灵活性。采用基于标记点的方法估计出坐标变换参数。首先利用基于定位基准点自适应算法查找至少3对对应点,然后采用四元数法估计变换参数,本文研究并实现了基于标记点的粗配准算法,并用实例进行了实验和验证。精确配准中,提出一种改进的ICP算法,将粗配准的结果作为精配准的初值,利用k-d树搜索算法确定初始的对应点,然后采用基于预检验的随机抽样一致性算法剔除误匹配点。通过实验证明,该方法在查找初始对应点时大大提高了计算效率,最后的配准精度也有所提高。更多还原

【Abstract】 As an advanced manufacturing technique, reverse engineering can be applied to product design, development and innovation. Data processing of the point clouds is one of the key technologies in reverse engineering. It’s very significant to study on data registration, because the registration accuracy and the number of 3D data point have vital effect on the quality of 3D model reconstruction.3D point clouds registration in reverse engineering are researched in detail in this thesis, which consists of the coarse registration and fine registration.A rapid method for point clouds registration based on reference points is proposed, which consists of the coarse registration and fine registration. A set of reference points is applied as an assistant utility to measure the object, which is on the surface of the object. The 3D data of the incremental reference points and density point clouds are acquired by a structure light 3D scanner. The advantage of the registration method of incremental point clouds is that the number of corresponding points of the reference points does not be required 3 or above 3 groups between the new measurement and its predecessor, only is required 3 or above 3 groups between the new measurement and before all the times of measurement. This measurement method is very flexible.In coarse registration, the transformation parameters are estimated by using the reference points only. First, the characteristic of the relative distance between arbitrary two points in the locating points set is used in finding at least three corresponding points. Then, quaternion method is utilized to estimate the transformation parameters. A new coarse registration algorithm based on the reference points is presented and realized.In fine registration, taking the coarse registration results as the initial value, the improved Interactive Closest Point (ICP) algorithm is used in fine registration. The original corresponding points are established rapidly by using the k-d tree searching algorithm. Finally, Preview Model Parameters Evaluation Random Sample Consensus (PERANSAC) algorithm is utilized to remove outliers. The experimental result shows that this method in finding original corresponding points can greatly improve the computation efficiency and also improve the registration accuracy.更多还原