This paper presents a license plate extraction method for gray-scale images, based on a combination of edge statistics and a two-step seeded region growing algorithm. The proposed region growing algorithm uses a dual criterion based on edge density and gray-scale intensity affinity. The proposed method aims at achieving license plate segmentation that fits to the real plate boundaries better than existing methods. The robustness of the method has been tested with experimental results, including examples of low quality or poor-preserved plates and commercial or freight transport vehicles. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Vargas, M., Toral, S. L., Barrero, F., & Cortés, F. (2009). A license plate extraction algorithm based on edge statistics and region growing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5716 LNCS, pp. 317–326). https://doi.org/10.1007/978-3-642-04146-4_35
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