We describe an algorithm for the correspondence of line features between two consecutive images. The algorithm is based on Godel coding of the features and singular value decomposition. First, line segments are extracted by Canny operator followed by the end-point-fit method. Line segments are represented by coordinates of midpoints and the angle of a perpendicular line from a reference point. Then, a proximity matrix is constructed following the minimal mapping theory of Ullman. Thus if two line segments are correlated, the corresponding matrix element is the Godel coded difference of their features; otherwise the element is assigned to a maximum number. Finally, singular value decomposition is applied on the proximity matrix. Godel coded differences strengthens the method due to the fact that not only the norms of the vectors are compared for matching but also their unique Godel numbers are involved. Proposed algorithm is implemented and tested both on calibrated and uncalibrated stereo image pairs and the matching results are promising.