Abstract: The invention relates to a method for providing a system for assessing a coated surface with respect to a type set containing at least one type of surface defect that can occur on the surface, to such a system for assessing a coated surface, to a measuring device for acquiring an image of a coated surface including such a system, and to a method for assessing a coated surface using such a system. The system can use a convolutional neural network (CNN), in particular the so-called U-Net architecture, to recognize the at least one surface defect in an image provided to the system. Moreover, the system can use a support vector machine algorithm to provide, based on the recognition results, quantitative and/or qualitative information about the depiction of the at least one surface defect in the image provided to the system.

Abstract: A multiple-stage method of determining surface properties, with the steps: determining at least one topographical property of at least one region of a surface to be investigated, determining an optical property of at least this region of the surface to be investigated and emitting at least one value which is characteristic of this optical property. When the value which is characteristic of this optical property is determined, the topographical property of the region is taken into consideration.

Abstract: A multiple-stage method of determining surface properties, with the steps: determining at least one topographical property of at least one region of a surface to be investigated, determining an optical property of at least this region of the surface to be investigated and emitting at least one value which is characteristic of this optical property. When the value which is characteristic of this optical property is determined, the topographical property of the region is taken into consideration.