A Multi-style License Plate Recognition System Based on Tree of Shapes for Character Segmentation

摘要

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.