1. A method of recognizing deviations in the shape of the surface of an object from a predetermined shape by detecting measurement values and subsequently processing the measurement values in an artificial neuronal net, characterized by the steps of: projecting patterns onto the surface of the object; recording images of the surface and the patterns by a matrix camera which generates a sequence of n images; shifting the projected pattern by predetermined values; defining on the basis of the grey value sequence of individual pixels of the n recorded images at least one number which is characteristic of one of the grey value sequence of a given pixel and of the grey value sequence of the pixel relative to at least one grey value sequence of different pixels; recalling the neuronal net subsequent to inputting one of the data of the recorded images and the matrix of the at least one characteristic number of the recorded object derived from the image data; utilizing as significant data of the deviations the comparison between one of the image data and the matrix of the characteristic number of the recorded object derived from the image data and the recall data of the neuronal net.