Enhancement of image recognition in digital close-range photogrammetry using mathematical equations and camera calibration - Thomas, Muhammad Adrian (2020)
The use of close-range photogrammetry technique via mathematical modelling and camera callibration are becoming an interesting area in reverse engineering to describe relationships between spatial objects in various applications. It has been used as an alternative solution to conventional methods for generation of virtual 3D models, which for use in CAD, CAM and CAE studies. However, many studies have revealed that most of the developed algorithms for 3D modelling possess several major challenges due to its tedious task during the image recognition phase. Thus, this research focuses to investigate the model reconstruction process for an enhanced image capturing method using close-range photogrammetry. Mathematical equations are presented to potentially help for an effective modelling operation as they are used to define the appropriate parameters for shooting phase based on the object’s size. This is to obtain as sufficient number of images as possibile to increase the overall overlapping areas between images during the photogrammetric data acquisition period. This research used different types of camera sensors and calibrations to capture the images respect to the reconstructed 3D models are presented. Finally, this research proposed a thorough framework incorporated in data acquisition factors and mathematics equations to capture a set of images using smartphone camera for closerange photogrammetry. The feasibility of the framework for generating a 3D model using photogrammetry was verified with a 3D model generated using ATOS 3D Scanner (high resolution 3D scanner for reverse engineering). Results obtained showed that the photogrammetric model reaches accuracy of 99% with the model scanned using ATOS along with maximum and minimum errors of 0.0003 m and 0.0004 m respectively. With that, using the same photogrammetric settings three case studies of different object sizes were investigated. At the end of this study, the objective of an enhanced image capturing method is successfully achieved.