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An Algorithm for License Plate Recognition Applied to ITS
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1953k
资源说明：An algorithm for license plate recognition (LPR)
applied to the intelligent transportation system is proposed on
the basis of a novel shadow removal technique and character
recognition algorithms. This paper has two major contributions.
One contribution is a new binary method, i.e., the shadow re-
moval method, which is based on the improved Bernsen algorithm
combined with the Gaussian filter. Our second contribution is a
character recognition algorithm known as support vector machine
(SVM) integration. In SVM integration, character features are
extracted from the elastic mesh, and the entire address character
string is taken as the object of study, as opposed to a single
character. This paper also presents improved techniques for im-
age tilt correction and image gray enhancement. Our algorithm
is robust to the variance of illumination, view angle, position,
size, and color of the license plates when working in a complex
environment. The algorithm was tested with 9026 images, such
as natural-scene vehicle images using different backgrounds and
ambient illumination particularly for low-resolution images. The
license plates were properly located and segmented as 97.16%and
98.34%, respectively. The optical character recognition system
is the SVM integration with different character features, whose
performance for numerals, Kana, and address recognition reached
99.5%, 98.6%, and 97.8%, respectively. Combining the preceding
tests, the overall performance of success for the license plate
achieves 93.54% when the system is used for LPR in various
complex conditions
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