Introduction To 3D Matching Using Halcon 10.0

This work builds a system which can easily recognize the pose and determine the x , y and z coordinates of any object in real world with respect to camera position. Using Point Grey Bumble Bee 2 Stereo Vision System stereo images has been captured of the various objects. Estimating the 3D pose of an object is an important task in many application areas, e.g., during completeness checks or for 3D alignment in robot vision applications. For the 3D pose estimation with surface-based matching, a surface model is generated from a 3D object model that was obtained either from a 3D computer aided design (CAD) model or from a 3D reconstruction approach. A typical application area for 3D matching is robot vision, i.e., whenever robots are equipped with cameras that supply information about the parts to manufacture. Such systems are also called “hand-eye systems” because the robotic “hand” is guided by mechanical “eyes”. In order to use the information extracted by the camera, it must be transformed into the coordinate system of the robot.