Abstract
Automatic vehicle identification is a very crucial and inevitable task in intelligent traffic systems. In this paper, initially, a Hue-Saturation-Intensity (HSI) color model is adopted to select automatically statistical threshold value for detecting candidate regions. The proposed method focuses are on the implementation of a method to detect candidate regions when vehicle bodies and license plate (LP) have similar color based on characteristics of color. Tilt correction in horizontal direction by the least square fitting with perpendicular offsets (LSFPO) is proposed and implemented for estimating rotation angle of the LP region. Then the whole image is rotated for tilt correction in horizontal direction by this angle. Tilt correction in vertical direction by reorientation of the titled LP candidate through inverse affine transformation is proposed and implemented for removing shear from the LP candidates. Finally, statistical based template matching technique is used for recognition of Korean plate characters. Various LP images are used with a variety of conditions to test the proposed method and results are presented to prove its effectiveness.
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© 2011 Springer-Verlag Berlin Heidelberg
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Deb, K., Le, M.H., Woo, BS., Jo, KH. (2011). Automatic Vehicle Identification by Plate Recognition for Intelligent Transportation System Applications. In: Mehrotra, K.G., Mohan, C.K., Oh, J.C., Varshney, P.K., Ali, M. (eds) Modern Approaches in Applied Intelligence. IEA/AIE 2011. Lecture Notes in Computer Science(), vol 6704. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21827-9_17
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DOI: https://doi.org/10.1007/978-3-642-21827-9_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21826-2
Online ISBN: 978-3-642-21827-9
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