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Although Automatic License Plate Recognition (ALPR) systems have achieved high recognition speed and efficiency, perspective distortion may still affect the accuracy and reliability of ALPR due to the uncertainty of camera shooting angle. Some existing license plate correction methods are computational expensive and low robust. We proposed a perspective correction method based on the bounding rectangle...
Driver assistance system enhances traffic safety and efficiency. Accurate 3D pose of front vehicle can help driver to make right decisions on road. We propose a novel real-time system to estimate 3D pose of the front vehicle. This system consists of two parallel threads: vehicle rear tracking and mapping. Vehicle rear is firstly identified in the video captured by an on-board camera, after license...
Different conditions, such as occlusions, changes of lighting, shadows and rotations, make vehicle type classification still a challenging task, especially for real-time applications. Most existing methods rely on presumptions on certain conditions, such as lighting conditions and special camera settings. However, these presumptions usually do not work for applications in real world. In this paper,...
AdaBoost classifiers with Haar-like features are widely used for license plate (LP) localization. However, it normally requires high-dimensional Haar-like features which cause extremely high computational cost. In this paper, a rejection cascade was built for LP localization with reduced Haar-like features. We first introduced line segment features as pre-input of Haar-like features for AdaBoost to...
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