License plate location based on a dynamic PCNN scheme

This paper describes a new dynamic ATR, automatic target recognition, scheme based on a pulse coupled neural network, PCNN. The PCNN is used to generate candidate regions that may contain a license car plate. Candidate regions are generated from pulsed images, output of the PCNN network. Statistics of the Fourier transform are used to determine if a candidate region contains a license plate. If the license plate is not located in the set of candidate regions, the PCNN network parameters are adjusted to generate a new pulsed image and new candidate regions are extracted and analyzed. The proposed system is robust in the sense that it does not restrict the location of the plate, neither the illumination conditions when the image is acquired. The purpose of no restrictions is to evaluate the proposed system under conditions where a person can succeed. The system performance was 85% on a set of images. One advantage of the proposed scheme is that it may be adapted to solve different ATR problems.