ALPR - Extension to Traditional Plate Recognition Methods

Automatic license plate recognition (ALPR) methods and software are used in toll collection, traffic monitoring and other areas of road transport industry. Majority of ALPR methods and almost all in industrial use, try to recognize a license plate identifier from a single image. However, in a sequence of images, recognition of a license plate in any frame can be improved by considering the information from preceding and succeeding frames, using video object tracking. A new approach is presented, for combining a video tracking and a single frame ALPR method to improve the recognition rate. Unlike earlier techniques which are tied to specific object tracking and identifier recognition methods, the new method can be used with almost any tracking and single frame ALPR methods. Its key part is a method for clustering and alignment of candidate license plate identifiers in a video track. The results from five video sequences taken from a surveillance camera under various weather and light conditions demonstrate the recognition rate improvements.

[2]  Simone Calderara,et al.  Visual Tracking: An Experimental Survey , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  Azeem Shahzad,et al.  Real Time Localization, Tracking and Recognition of Vehicle License Plate , 2011, VISAPP.

[4]  Ian D. Reid,et al.  Joint tracking and segmentation of multiple targets , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[5]  Horst Bischof,et al.  Detecting, Tracking and Recognizing License Plates , 2007, ACCV.

[6]  Zhongfei Zhang,et al.  A survey of appearance models in visual object tracking , 2013, ACM Trans. Intell. Syst. Technol..

[7]  Xiangjian He,et al.  Number Plate Recognition Based on Support Vector Machines , 2006, 2006 IEEE International Conference on Video and Signal Based Surveillance.

[8]  Carlos A. B. Mello,et al.  A Complete System for Vehicle License Plate Recognition , 2009, 2009 16th International Conference on Systems, Signals and Image Processing.

[9]  Jiří Matas,et al.  Unconstrained licence plate and text localization and recognition , 2005, Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005..

[10]  Xiangjian He,et al.  Automatic License Plate Recognition: a Review , 2004, CISST.

[11]  Wael Badawy,et al.  Automatic License Plate Recognition (ALPR): A State-of-the-Art Review , 2013, IEEE Transactions on Circuits and Systems for Video Technology.

[12]  Horst Bischof,et al.  Efficient Maximally Stable Extremal Region (MSER) Tracking , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).