Robust number plate detector based on stroke width transform and neural network

The number plate detection is a key step affecting the overall performance of the number plate recognition system. In the paper a novel algorithm for this purpose is proposed. The approach is based on the detection of text areas using the stroke width transform. More plate candidates are detected using the specifically developed image preprocessing scheme based on set of morphological operators and contour analysis. The final number plate candidates are properly classified using the neural network which is learned from the training dataset. Experiment results indicate on the high performance of the developed methodology.