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Illumination invariant lane color recognition by using road color reference neural networks

机译:使用道路颜色参考和神经网络的照明不变车道颜色识别

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Non-linearity of color changing in various lighting conditions is one of the primary factors which make lane color recognition difficult. This paper introduces an illumination invariant lane color recognition method which can recognize two lane colors (white, yellow) and copes with the non-linearity by using neural networks. Our method utilizes the road texture as the indicator of illumination condition and learns the relation between illumination condition and lane color by using multi-layer perceptron. The proposed method was verified by the experiment with a road images sequence of real driving situation.
机译:在各种照明条件下颜色变化的非线性是导致车道颜色识别困难的主要因素之一。本文介绍了一种照明不变车道颜色识别方法,该方法可以识别两种车道颜色(白色,黄色)并通过神经网络来应对非线性。我们的方法利用道路纹理作为照明条件的指标,并通过使用多层感知器来了解照明条件与车道颜色之间的关系。通过实际驾驶情况的道路图像序列的实验验证了该方法的有效性。

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