License Plate Detection based on Genetic Neural Networks, Morphology, and Active Contours

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Author
Olivares Bueno, Joaquín
Palomares Muñoz, José Manuel
Soto Hidalgo, José Manuel
Gámez Granados, Juan Carlos
Date
2010Subject
Active contourLicense plate
Electronic toll collection
License plate recognition
Slope plate
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This paper describes a new method for License Plate Detection based on Genetic Neural Networks, Morphology, and Active Contours. Given an image is divided into several virtual regions sized 10×10 pixels, applying several performance algorithms within each virtual region, algorithms such as edge detection, histograms, and binary thresholding, etc. These results are used as inputs for a Genetic Neural Network, which provides the initial selection for the probable situation of the license plate. Further refinement is applied using active contours to fit the output tightly to the license plate. With a small and well–chosen subset of images, the system is able to deal with a large variety of images with real–world characteristics obtaining great precision in the detection. The effectiveness for the proposed method is very high (97%). This method will be the first stage of a surveillance system which takes into account not only the actual license plate but also the model of the car to determine if a car should be taken as a threat.