A New License Plate Recognition System Based on Probabilistic Neural Networks

A license plate recognition system employs image processing techniques, to help to identify the vehicles through their plates. License plate recognition is a process, where first the license plate region is localized in a car image supplied by one camera or by multiple cameras, and then the characters on the plate are identified by a character recognition system. There are many applications of the license plate recognition systems, both public and private. The algorithms, hardware and the network structure for recognition are designed according to the specific application. Recently, thanks to the advances in science and technology, the algorithms and hardware of higher quality have been designed, and license plate recognition systems are now widely used. The recognition can be done in three major steps: Localization of the plate, extraction of the plate characters, and recognition of the characters using a suitable identification method. In this paper, an algorithm is designed that can recognize plates using the pictures taken at various angles, various distances and different times of the day, thus under various illumination conditions. The plate is localized using Otsu's thresholding method and the plate features. Vertical and horizontal histograms are used for character segmentation. Finally, character recognition is done by Probabilistic Neural Networks. Simulation results are included and performance analyses are tabulated. MATLAB program is used in the simulations.