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Visual modeling of cathode ray tube displays for finding cross-media corresponding colors based on the natural color system color atlas and neural networks

机译:阴极射线管显示器的可视化建模,用于基于自然色彩系统色图集和神经网络查找跨媒体的对应颜色

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摘要

A visual method for characterizing cathode ray tube (CRT) displays and finding corresponding colors is presented. The method is motivated by the considerable expense of measuring instruments and the consideration of color appearance factors. In the experiment, a set of color chips in the natural color system (NCS) color atlas, an illuminant, and a CRT are used. 487 sample pairs of RGB (CRT) and HVC, which are the attributes of NCS color chips, are obtained by experimentally comparing softcopies and hard-copies in the office environment in the sense of best color matching to nine observers. Both the spectral data of the color chips and the colorimetric values of the CRT samples are measured. In addition, 12 error back-propagation (BP) neural networks are trained to help the realization of the transformation from HVC to RGB for data generalization. The current results show that the displays on the CRT can match the chips in color perception well.
机译:提出了表征阴极射线管(CRT)显示器并查找相应颜色的可视方法。该方法是由大量的测量仪器费用和对颜色外观因素的考虑所激发的。在实验中,使用了一组自然色系统(NCS)彩色图集中的彩色芯片,一个发光体和一个CRT。通过对9位观察者进行最佳色彩匹配的实验,将办公室环境中的软拷贝和硬拷贝进行实验比较,获得了487个RGB(CRT)和HVC样本对,它们是NCS彩色芯片的属性。测量彩色芯片的光谱数据和CRT样品的比色值。此外,还训练了12个错误反向传播(BP)神经网络,以帮助实现从HVC到RGB的转换,以进行数据概括。当前的结果表明,CRT上的显示器可以很好地匹配色彩感知方面的芯片。

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