Abstract
This paper proposes new real time license plate recognition (LPR) system that is capable of motion tracking and recognition of license plate. The best frame taken from the video has been chosen which is found to be about 4 m apart from camera position. For further processing, lower half section of vehicle image has been cropped of sized (450 × 140) while tracking. Local Binary Pattern (LBP) and histogram matching technique are used to detect license plate. Due to the robustness of LBP features, this method can adaptively deal with various changes such as rotation, scaling, and illumination in the license plate. Segmentation of the plate region into disjoint characters has been done with bounding box technique with some modifications. Recognition has been done by calculating histogram features. Minimum distance classifier has been used for features matching. The system is tested on more than 300 images and it gives 96.14% detection and 89.35% of recognition accuracy. This system is designed to recognize license plate of small, medium as well as large vehicles. It is also capable to detect single line and two line license plates format.
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Bachchan, A.K., Gorai, A., Gupta, P. (2017). Automatic License Plate Recognition Using Local Binary Pattern and Histogram Matching. In: Huang, DS., Jo, KH., Figueroa-García, J. (eds) Intelligent Computing Theories and Application. ICIC 2017. Lecture Notes in Computer Science(), vol 10362. Springer, Cham. https://doi.org/10.1007/978-3-319-63312-1_3
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