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An integrated vehicle plate detection and recognition system generally aims to detect the license plate (LP) and recognize its characters. The process basically includes LP detection, LP extraction, character segmentation, feature extraction and recognition. Due to its wide range of applications such as traffic management, security etc., and this topic is intensively researched especially in the field of image processing. Furthermore, the differences in systems, colours, backgrounds, foregrounds, font and style of the license plates from one country to another add more problems and challenges for new researches. Thus, this book presents an integrated approach for detecting and recognizing Libyan license plates based on Radial Basis Function Neural Network (RBFNN). The method begins with the preprocessing of the image using edge detection and morphological operations. In the detection stage, connected component analysis is used to locate unique objects. In the recognition process, for character segmentation, a simple template is derived to extract and differentiate digits and Arabic words. Finally,in the classification process, RBFNN is used to recognize an individual character.

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