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Background Color Constancy Algorithm Based on Neural Network

机译:基于神经网络的背景颜色恒定算法

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This paper proposed a novel color constancy algorithm based on neural network to solve the problems of color constancy in the field of machine vision such as background image update. Because of the generalization capability of neural network, by means of appropriate sample sets, we adopt improved learning algorithm to train the neural network to obtain the mapping relation of the corresponding pixels of the image before and after the changes. After training, the neural network would output image data with color constancy. At last, the method was tested by the experiment of the video background update under the scenes with randomly selected illuminants, and it was proved to be effective.
机译:本文提出了一种基于神经网络的新型色彩恒定算法,解决了背景图像更新的机器视野中色彩恒定问题。由于神经网络的泛化能力,通过适当的样本集,我们采用改进的学习算法训练神经网络以获得更改之前和之后图像的相应像素的映射关系。在训练之后,神经网络将以色恒定输出图像数据。最后,通过随机选择的光照剂的场景下的视频背景更新的实验测试了该方法,并证明了它是有效的。

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