Implementation of an Hybrid Approach on FPGA for License Plate Detection Using Genetic Algorithm and Neural Networks

Gökmen Avcı, Muzaffer Köstence, Fuat Karakaya, Halis Altun, Mehmet Ali Çavuşlu
International Symposium on INnovations in Intelligent SysTems and Applications, 392-396, June 29-July 1, 2009, Trabzon

Abstract: In this study, a hardware solution for car plate detection problem is proposed based on softcomputing techniques, namely the genetic algorithm and neural networks which are implemented on Programmable Field Gate Array (FPGA). The proposed plate detection requires a successful integration of image processing and pattern classifier algorithms, which impose a high computation load, such as edge detection, statistical bit-wise feature extraction, neural networks and genetic algorithm. In literature, software based approaches to this problem have already been proposed. In this study, however, a hardware based solution is provided by implementing feature extraction, genetic algorithm and neural networks on FPGA.

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