A Naive Bayesian approach for color recognition of license plates

Color recognition of license plates is an important step to License Plate Recognition (LPR) system. In order to perform color recognition more effectively, an algorithm based on Naive Bayesian approach is proposed in this paper. To improve the efficiency of color recognition, the multiclass problem is converted into two binary problems based on the reverse color information of plate images. Color features of license plates are extracted in the HSV (hue-saturation-value) color space. Statistical information about color features for each type of license plates are obtained from training samples. And color classifier is built according to the Naive Bayesian rule. Comparison experiments were conducted on three different test sets. And the experimental results show that the proposed algorithm achieves good recognition performances.