An algorithm combined with color differential models for license-plate location

Abstract

Vehicle license plate positioning is the first and most important step in license plate recognition systems. Existing license plate location algorithms are sensitive to light conditions and prone to be influenced by the background interference. To solve these problems, this paper presents an adaboost algorithm combined with color differential model. The proposed algorithm is composed of a coarse location step and a precise location step. In the coarse location step, a binary image is obtained to select the candidate plate regions using the color differential model. Then in the precise location step, the features obtained above together with other features are used by the adaboost algorithm to train the classifiers and precisely locate the license plates. The experimental results show that the proposed algorithm is more robust to the light conditions and background interference. In particular, during nighttime the precision rate can attain above 95.0%.