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In this paper, an improved system which can detect multiple license plates in high resolution applications is proposed. First, the Symmetric Mask-based Discrete Wavelet Transform (SMDWT) is utilized to speed up the license plates detection. Later on, the proposed Hierarchical AdaBoost (HA) realizes the detection for multiple targets, in which the classifiers simply require 10 minutes off-line training. In the character segmentation phrase, a projection-based approach considering the relationship among characters is also established. Finally, 13 structural/directional features with the Naïve Bayes are applied for character recognition. Experimental results conclusively ensure that the proposed technique is effective for freeway's multiple toll station and transportation management applications contributed from excellent reliability and processing efficiency in big frame size.