Improvement of the accuracy of an automatic car license plate recognition system is studied. The recognition system has been installed in several ports, factories and national borders around Europe and Middle East. The paper describes the anatomy of a portable version of the recognition system, in which the requirements are different from a fixed installation. For example, the portable system recognizes the license plates with no external triggers (such as inductive loops) and the installation is left to the end-user. The placement of the recognition camera in such systems is often a compromise and cannot be fully controlled. The system learns the characteristics of the setup and tries to correct the imperfections that are due to the installation by a non-expert. One of the main problems is the angle in which the camera is looking at the road, which causes the plate and the characters appear skewed. This paper proposes an algorithm for cancelling the skewness effect. The skewness parameters can be estimated from the earlier
recognition results, and the proposed system learns to correct the skewness resulting in improved recognition results. The improvement of the recognition accuracy is illustrated by experiments with
an annotated database of license plate images.