Abstract: A method and device recognize and analyze surface defects in three-dimensional objects having a reflective surface, in particular motor vehicle bodies. In which method the surface defects are identified by the evaluation of an image, recorded by a camera in the form of a raster image of pixels, of an illumination pattern projected by a first illumination device onto a part of the reflective surface using a two-dimensional raster coordinate system. The surface defects are identified exclusively using two-dimensional image information with the aid of image processing algorithms without the need for “environmental parameters”, and complex geometric calculations can be omitted. The solution is fast and robust and can be carried out using differently configured first illumination devices, which makes it suitable for mobile applications, for example as a hand-held module. It is also made possible for the method to be optimized by a “deep learning” strategy.

Abstract: A method and device recognize and analyze surface defects in three-dimensional objects having a reflective surface, in particular motor vehicle bodies. In which method the surface defects are identified by the evaluation of an image, recorded by a camera in the form of a raster image of pixels, of an illumination pattern projected by a first illumination device onto a part of the reflective surface using a two-dimensional raster coordinate system. The surface defects are identified exclusively using two-dimensional image information with the aid of image processing algorithms without the need for “environmental parameters”, and complex geometric calculations can be omitted. The solution is fast and robust and can be carried out using differently configured first illumination devices, which makes it suitable for mobile applications, for example as a hand-held module. It is also made possible for the method to be optimized by a “deep learning” strategy.