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Computer vision system approach in colour measurements of foods: Part I. development of methodology

机译:食品颜色测量的计算机视觉系统方法:第一部分。方法论的发展

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Abstract The colour assessment ability of the computer vision system is investigated and the data are compared with colour measurements taken by a conventional colorimeter. Linear and quadratic models are built to improve currently used methodology for the conversion of RGB colour units to L * a * b * colour space. For this purpose, two innovative ideas are proposed and tested. First, substantial amount of colour tones is generated to cover as many points in the colour space as possible. Secondly, the colour space is calibrated separately, whereas in previous research in the literature, the colour space is calibrated simultaneously. It is found that the RGB colour units to L * a * b * colour space transformation approach proposed in this study is more logical and more accurate, and the prediction performance of the quadratic model is superior over the linear model.
机译:摘要研究了计算机视觉系统的颜色评估能力,并将数据与传统比色表拍摄的颜色测量进行了比较。建立线性和二次模型,以改进目前使用的方法,用于将RGB颜色单元转换为L * A * B *颜色空间。为此目的,提出并测试了两种创意。首先,产生大量色调以尽可能多地覆盖颜色空间中的多个点。其次,颜色空间分别校准,而在文献之前的研究中,颜色空间同时校准。结果发现,本研究提出的RGB颜色单元到L * A * B *颜色空间转换方法更为逻辑且更准确,并且二次模型的预测性能优于线性模型。

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