Multi-step approach for automated scaling of photogrammetric micro-measurements

Photogrammetry can be used for the measurement of small objects with micro-features, with good results, low costs, and the possible addition of texture information to the 3D models. The performance of this technique is strongly affected by the scaling method, since it retrieves a model that must be scaled after its elaboration. In this paper, a fully automated multi-step scaling system is presented, which is based on machine vision algorithms for retrieving blurred areas. This method allows researchers to find the correct scale factor for a photogrammetric micro model and is experimentally compared to the existing manual method basing on the German guideline VDI/VDE 2634, Part 3. The experimental tests are performed on millimeter-sized certified workpieces, finding micrometric errors, when referred to reference measurements. As a consequence, the method is candidate to be used for measurements of micro-features. The proposed tool improves the performance of the manual method by eliminating operator-dependent procedures. The software tool is available online as supplementary material and represents a powerful tool to face scaling issues of micro-photogrammetric activities.