Photometric Stereo is an imaging and image processing technique for contact-free surface measurement. It uses the characteristic surface reflectance of materials under different lighting conditions to separate surface albedo from surface geometry. The surface of a stationary test specimen is successively illuminated by light sources with known positions relative to the test specimen and camera. The varying light intensity of each surface element gives information about its orientation. This information about the surface gradient is used to reconstruct a discrete 3D-representation of the surface, i.e. surface reconstruction from gradient fields. This work describes a fully automated experiment setup for evaluating Photometric Stereo for both ideal and non-ideal Lambertian surfaces. Error sources in the experiment setup were identified and a new calibration method was developed. This method compensates for the inhomogeneous illumination generated by the light sources. For this purpose, the light distribution of each light source was measured and a calibration matrix was derived. The calibration matrix was used to normalize the source data for Photometric Stereo. The error caused by the inhomogeneous light distribution increases with the size of the surveyed specimen. The developed calibration method allows the application of Photometric Stereo on large specimens. It is shown that a square metallic surface with an edge length of 17.5 cm was reconstructed successfully.