A study on using image serving technology for high precision mechanical positioning. (15th December 2016) - Lin, Chuen-Horng; Hsiao, Muh-Don; Lai, Kuo-Jung
Abstract: This paper focused on using image server technology for high precision mechanical positioning. Rapid and precise positioning systems depend on the correct positions of CCD (Charge Coupled Device) video cameras, as well as on pattern matching modes. This study deals with four different positions captured by an automatic detection system employing a CCD video camera. According to a variety of hybrid image registration systems, this study proposes an entire set of methods for achieving optimal hybrid pattern matching. First, the four different position detections captured by the CCD video camera in low-resolution were examined. Next, the original position detection was carried out in high-resolution, in order to derive a precise set of CCD video camera positions. The fiducial mark (FM) was then divided into two types in the optimal option for pattern matching: the "fiducial mark" and "non-fiducial mark", which were then used for sampling. The automatic detection method is able to achieve the first pattern matching detection for recognized images. Unrecognized images or images that cannot have an FM were subjected to fine pattern matching detection. When it is not possible to find more than one FM after the proposed detection method, this suggests that the position of the CCD video camera should be reset. In this paper, the results of the experiment regarding the CCD camera precision location and the segmentation of fiducial patterns or insignificant fiducial patterns can detect and segment more unique areas and areas with unique features. Highlights: Using image server technology for precision mechanical positioning in this paper. The systems depend on the positions of CCD cameras and pattern matching modes. The fiducial mark was then divided into the fiducial and non-fiducial mark. The automatic detection is the pattern matching detection for recognized images. Unrecognized images were subjected to fine pattern matching detection.