Object identification unit for identifying objects that are symmetrical with respect to an axis of symmetry, comprising: an artificial neural network, ANN, having an input layer and an output layer, wherein the ANN is designed to identify objects based on inputs at the input layer; wherein the input layer comprises a plurality of input neurons; wherein the input layer is designed to obtain an input vector, wherein the input vector contains items of object identification information on the object to be identified; wherein the ANN is designed to identify an object that is symmetrical with respect to an axis of symmetry based on the items of object identification information; wherein the items of object identification information correspond to a two-dimensional image of the object to be identified; wherein the object identification unit is configured to divide the two-dimensional image into a plurality of triangles, which are delimited by characteristic points of the object to be identified at their corners; wherein the object identification unit is configured to ascertain a rotational angle of the object to be identified in the two-dimensional image from symmetry properties of the object to be identified and relative area components of the individual triangles in the total sum of the area of the triangles and to multiply the areas of the individual triangles by a correction factor to obtain corrected areas of the triangles, which correspond to a symmetry condition, wherein the symmetry condition is an axial symmetry with respect to an axis of the object to be identified, and wherein the symmetry condition is met when triangles in two halves of the object to be identified and defined by characteristic points corresponding to one another are of equal size; wherein the object identification unit is configured to scale the corrected areas of the triangles to a rotation-invariant dimension of the object to be identified; wherein the object identification unit is configured to supply the scaled areas of the triangles to the ANN as the input vector. an artificial neural network, ANN, having an input layer and an output layer, wherein the ANN is designed to identify objects based on inputs at the input layer; wherein the input layer comprises a plurality of input neurons; wherein the input layer is designed to obtain an input vector, wherein the input vector contains items of object identification information on the object to be identified; wherein the ANN is designed to identify an object that is symmetrical with respect to an axis of symmetry based on the items of object identification information; wherein the items of object identification information correspond to a two-dimensional image of the object to be identified; wherein the object identification unit is configured to divide the two-dimensional image into a plurality of triangles, which are delimited by characteristic points of the object to be identified at their corners; wherein the object identification unit is configured to ascertain a rotational angle of the object to be identified in the two-dimensional image from symmetry properties of the object to be identified and relative area components of the individual triangles in the total sum of the area of the triangles and to multiply the areas of the individual triangles by a correction factor to obtain corrected areas of the triangles, which correspond to a symmetry condition, wherein the symmetry condition is an axial symmetry with respect to an axis of the object to be identified, and wherein the symmetry condition is met when triangles in two halves of the object to be identified and defined by characteristic points corresponding to one another are of equal size; wherein the object identification unit is configured to scale the corrected areas of the triangles to a rotation-invariant dimension of the object to be identified; wherein the object identification unit is configured to supply the scaled areas of the triangles to the ANN as the input vector.