A novel license plate location method based on neural network and saturation information

Authors:
Yinghua Lu;Lijie Yu;Jun Kong;Canghua Tang
Affiliations:
Computer School, Northeast Normal University, Changchun, Jilin Province, China;Computer School, Northeast Normal University, Changchun, Jilin Province, China;Computer School, Northeast Normal University, Changchun, Jilin Province, China;Computer School, Northeast Normal University, Changchun, Jilin Province, China
Venue:
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Year:
2005

Citing 2
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Abstract

In this paper, a novel license plate location algorithm for color image is presented. Firstly the neural networks are used as filters for analyzing within small windows for an image and deciding whether each window contains a license plate or not coarsely. And then we use the information which the license plate’s saturation value is different from the background’s, so it can be used to locate license plate finely. At last, color pairs method is presented to prove whether the region we found is the license plate region or not. The experimental results show that proposed algorithms are robust in dealing with the license plate location in complex background.