Wavelet And Neural Net Pattern Recognition Technology And The Application To Recognition Of Vehicle's License Plates

Wavelet transform has been widely used in image process and pattern recognition because its "micro - scope" feature and similar-human vision feature. Neural net pattern recognition is an important research direction in pattern recognition field because of the strong self-learning, application feature.VLP is an important application and the core technology of computer vision and pattern recognition in the intelligent traffic field. So apply these two tools in VLPR has biggish theory meaning and practice value.This paper has finished some tasks as follows:1) image pretreatment. This phase research image de_noise and image inclination rectification. Based on the wavelet high frequency coefficient, we bring forward a wavelet part thresholding method. While in image inclination rectification, a modified Hough transform is used in VLP inclination detection and rectification.2) character segmentation. This phase bring forward a new applied method in VLP character segmentation. Based on predeterminate knowledge of VLP and wavelet nulti-scale analysis feature, segmentation position is located self-adaptively.3) character feature extraction. According to wavlet's directive characteristic,we bring forward a new wavelet part grid feature.4) character recognition. Study the integration method of many inputs and many neural net. Therefore we bring forward a multi-layer serial classifiers with neural network.The research in this article shows that the wavelet part thresholding method is effective; character segmentation method has little limitation for the VLP inclination; the wavelet grid feature has good stability and satisfactory distinction; compared with the single classifier, the multi-layer serial classifiers can efficiently improve resistance to interaction and recognition rate of the system.