Surface color estimation in 3D spatial coordinate remote sensing by a technical vision system

This paper proposes to enhance the capabilities of a Technical Vision System (TVS) based on optical scanning and dynamic triangulation for 3D spatial coordinates measurements to determine and add to the record of its measurements the color of the objects coordinates scanned. Optoelectronics signals output from the TVS scanning aperture contain a huge amount of data that cannot be friendly or obvious to human understanding and interpretation. However, time domain characteristic parameters can be extracted from the optoelectronics signals, which can describe aspects of the optoelectronic signal and the 3D spatial coordinate to whom it belongs; that is, it is specific and punctual information from the area of the object under scanning. In this theoretical and experimental evaluation, the parameters obtained from optoelectronics signals have been used as feature inputs for supervised learning and as an approach to implement artificial intelligence to the TVS signal processing by a model able to predict in real time the color of the 3D spatial coordinates measured.