<![CDATA[Photogrammetry is a technique for measuring and modeling three-dimensional objects by utilizing digital imagery from various perspectives. In the context of reverse engineering, this technique serves to duplicate, reconstruct, and analyze the dimensions of physical objects with a high degree of accuracy. The main advantage of photogrammetry lies in its ability to capture the details of the shape and texture of objects without the need for physical contact. However, the quality of photogrammetry scan results is greatly influenced by a number of technical factors, especially lighting and camera sensor sensitivity (ISO) settings. Variations in these two parameters can cause deviations or dimensional deviations in the resulting 3D model. This study aims to quantitatively evaluate the influence of lighting intensity and camera ISO setting on dimensional deviation in photogrammetry scan results. The research method used is experimental, where the dimensions of the scanned object are compared to the original dimensions using precision measuring instruments. The results showed that both the lighting level and the ISO setting had a significant influence on the accuracy level of the 3D model. The ideal lighting intensity range was found to be in the range of 125–150 lux, where shadows and light reflections could be minimized. Meanwhile, the use of low ISO (around 200) is able to produce cleaner image textures and minimize noise, resulting in smaller dimensional deviations. Additionally, the interaction between moderate lighting and low ISO is proven to provide the best scanning accuracy. This combination is able to maintain a balance between image quality and surface detail of the object. These findings not only provide practical recommendations regarding the regulation of scanning conditions, but can also serve as a guideline for industry practitioners and academics in improving the quality of reverse engineering results. With a proper understanding of lighting and ISO variables, the photogrammetry process can be optimized to produce more accurate and efficient 3D models.]]>
