Color is an important indicator of product quality evaluation. In this paper, a method of color difference detection based on BP neural network was proposed. RGB values of objects were firstly extracted, which were three inputs of BP neural network. Then the trained neural network converted RGB values to L*a*b* values. Finally, according to the formula of the color difference, the objective quantificational value was calculated. The experimental results show that the proposed method can detect and analyze the color difference of objects.
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机译：颜色是产品质量评估的重要指标。提出了一种基于BP神经网络的色差检测方法。首先提取对象的RGB值，这是BP神经网络的三个输入。然后，经过训练的神经网络将RGB值转换为L * a * b *值。最后，根据色差公式计算出目标定量值。实验结果表明，该方法可以检测和分析物体的色差。
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