Towards a Multinational Car License Plate Recognition System
Machine Vision and Applications
A configurable method for multi-style license plate recognition
Pattern Recognition
Detecting, tracking and recognizing license plates
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II
Multiple clues for license plate detection and recognition
CIARP'10 Proceedings of the 15th Iberoamerican congress conference on Progress in pattern recognition, image analysis, computer vision, and applications
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
A cognitive and video-based approach for multinational License Plate Recognition
Machine Vision and Applications
License Plate Recognition From Still Images and Video Sequences: A Survey
IEEE Transactions on Intelligent Transportation Systems
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The aim of this work is to develop a multi-style license plate recognition (LPR) system. Most of the LPR systems are country-dependent and take advantage of it. Here, a new character extraction algorithm is proposed, based on the tree of shapes of the image. This method is well adapted to work with different styles of license plates, does not require skew or rotation correction and is parameterless. Also, it has invariance under changes in scale, contrast, or affine changes in illumination. We tested our LPR system on two different datasets and achieved high performance rates: above 90 % in license plate detection and character recognition steps, and up to 98.17 % in the character segmentation step.