A robust license-plate extraction method under complex image conditions

A robust approach for extracting car license plate from images with complex background and relatively poor quality is presented. The approach focuses on dealing with images taken under weak lighting condition. The proposed method is divided into two steps: 1) searching candidate areas from the input image using gradient information, and 2) determining the plate area among the candidates and adjusting the boundary of the area by introducing a plate template. A set of experiments has been performed to prove the robustness and accuracy of the approach. For many images collected from a large underground parking place the result shows that 90% of them are correctly segmented.