Morphological Box Classification Framework for supporting 3D scanner selection

ABSTRACT 3-Dimensional (3D) scanning systems are becoming more common in the industry nowadays, for inspection and reverse engineering (RE) purposes. Although technical specifications are provided with commercially available scanners, a question could be raised pertaining to the degree of sufficiency of the technical specifications typically provided, with regard to specific application needs such as the scanning of challenging objects. These challenging objects present a less than ideal working condition for some 3D scanners, and the specified accuracy cannot be achieved. This effect varies across different types of 3D scanning technology. A more intuitive specification with regard to the time taken and ease of use will be beneficial to the user, but often not available. Hence, this paper proposes a Morphological Box Classification Framework based on the functional decomposition of the non-contact 3D scanning technology, in order to help users better understand and compare 3D scanners efficiently, and choose a scanner for their application that is able to perform within their desired accuracy, time taken, and ease of use. A case study of 3D scanners evaluation using the proposed framework for a RE application is conducted, and results presented.