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

机译:基于形状树的字符分割多样式车牌识别系统

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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.
机译:这项工作的目的是开发一种多样式车牌识别(LPR)系统。大多数LPR系统都依赖于国家/地区并加以利用。在此,基于图像形状树,提出了一种新的字符提取算法。此方法非常适合与不同样式的车牌一起使用,不需要偏斜或旋转校正,并且是无参数的。而且,它在缩放比例,对比度或仿射光照变化下具有不变性。我们在两个不同的数据集上测试了LPR系统,并获得了很高的性能:在车牌检测和字符识别步骤中达到90%以上,在字符分割步骤中达到98.17%。

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