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A novel algorithm for license plate location based on the RGB features and the texture features

机译:基于RGB特征和纹理特征的车牌定位新算法。

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In order to locate license plates in a complex environment, we develop a novel license plate location algorithm by combing the texture features of plate and features in the RGB color space. A picture is first filtered with a custom convolutional kernel in order to enhance the texture of characters, followed by morphological processing to get region set A. The RGB features of the license plate are then extracted from the picture, and region set B is obtained by performing morphological processing. Region set C is obtained by performing intersection operation of A and B. Finally, through elimination of pseudo-regions, the real license plate region is located. Evaluation of this algorithm on pictures sampled from different illuminations and road conditions demonstrates an accuracy of 98%.
机译:为了在复杂的环境中定位车牌,我们通过结合车牌的纹理特征和RGB颜色空间中的特征,开发了一种新颖的车牌定位算法。首先使用自定义的卷积核对图片进行滤波,以增强字符的纹理,然后进行形态学处理以获得区域集A。然后从图片中提取车牌的RGB特征,并通过以下方法获得区域集B:执行形态处理。通过执行A和B的相交运算获得区域集C。最后,通过消除伪区域,找到了真实车牌区域。对从不同光照和道路条件下采样的图片进行的算法评估表明,其准确性为98%。

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