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Constructing feature points for calibrating a structured light vision sensor by viewing a planefrom unknown orientations

机译:通过从未知方向查看平面来构建用于校准结构化光学视觉传感器的特征点

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摘要

To calibrate a structured light vision sensor, it is necessary to obtain at least four non-collinear feature points that fall on the light stripe plane. We propose a novel method to construct non-collinear feature points used for calibrating a structured light vision sensor with a planar calibration object. After the planar calibration object is moved freely in the range of measuring of the structured light vision sensor at least twice, all the local world coordinates of the feature points falling on the light stripe plane can be readily obtained in site. The global world coordinates of the non-collinear feature points in the local world coordinate frame can be computed through the three-dimensional (3D) camera coordinate frame. A planar calibration object is designed according to the proposed approach to provide accurate feature points. The experiments conducted on a real structured light vision sensor that consists of a camera and a single-light-stripe-plane laser projector reveal that the proposed approach has high accuracy and is practical in the vision inspection applications. The proposed approach greatly reduces the cost of the calibration equipment and simplifies the calibrating procedure. It advances structured light vision inspection one step from laboratory environments to real world use.
机译:为了校准结构化的视觉传感器,必须获得至少四个落在光条平面上的非共线特征点。我们提出了一种新颖的方法来构造非共线特征点,该特征点用于通过平面校准对象来校准结构化的视觉传感器。在平面校准物体在结构化光学视觉传感器的测量范围内自由移动至少两次之后,可以很容易地在现场获得落在光带平面上的特征点的所有局部世界坐标。可以通过三维(3D)相机坐标系来计算局部世界坐标系中非共线特征点的全局世界坐标。根据所提出的方法来设计平面校准对象以提供准确的特征点。在由照相机和单光条平面激光投影仪组成的真实结构的光视觉传感器上进行的实验表明,该方法具有很高的准确性,在视觉检查应用中很实用。所提出的方法大大降低了校准设备的成本,并简化了校准程序。从实验室环境到现实世界的使用,它使结构化的光学视觉检测前进了一步。

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