EWorldShape::AddPoint
Adds a new point coordinates (in Sensor space) to the set of grid points used for calibration.
Namespace: Euresys::Open_eVision
[C++]
void AddPoint(
const EPoint& sensorPoint
)
Parameters
sensorPoint
Sensor point coordinates.
Remarks
Grid calibration is the process of computing the calibration parameters by means of a set of points known to lie on a rectangular grid. If the grid pitch is known and one of the points is chosen as the origin point, the points can be used as landmarks. By contrast with the landmark calibration functions, the World coordinates of the grid points need not be specified, nor do they have to be given in any specific order. The calibration algorithm is capable of sorting out the points to reconstruct the grid topology. Typically, this function is used in conjunction with blob analysis to extract the dot centers from a grid of dots. Anyway, any other scheme can be used. The grid of points need not be complete, i.e. some of the nodes may be missing, and the points need not completely fill a rectangular area. Landmark calibration is simply achieved by providing a series of point coordinates (in Sensor space only) and then calling the grid reconstruction function followed by the calibration function.
EWorldShape.AddPoint
Adds a new point coordinates (in Sensor space) to the set of grid points used for calibration.
Namespace: Euresys.Open_eVision
[C#]
void AddPoint(
Euresys.Open_eVision.EPoint sensorPoint
)
Parameters
sensorPoint
Sensor point coordinates.
Remarks
Grid calibration is the process of computing the calibration parameters by means of a set of points known to lie on a rectangular grid. If the grid pitch is known and one of the points is chosen as the origin point, the points can be used as landmarks. By contrast with the landmark calibration functions, the World coordinates of the grid points need not be specified, nor do they have to be given in any specific order. The calibration algorithm is capable of sorting out the points to reconstruct the grid topology. Typically, this function is used in conjunction with blob analysis to extract the dot centers from a grid of dots. Anyway, any other scheme can be used. The grid of points need not be complete, i.e. some of the nodes may be missing, and the points need not completely fill a rectangular area. Landmark calibration is simply achieved by providing a series of point coordinates (in Sensor space only) and then calling the grid reconstruction function followed by the calibration function.