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Automatic determination of peroxides and acidity of olive oil using machine vision in olive fruits before milling process

机译:碾磨过程中橄榄水果机视觉自动测定橄榄油的过氧化物和酸度

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Ones of the most important parameters to measure of olive oil quality are acidity and peroxide index and, currently, they are measured in a laboratory using samples of olives extracted from a batch in the reception process. The aim of this work is to provide an automatic inspection system, based on computer vision-visible and infrared (IR) channels-, to infer automatically these parameters. The proposal uses the differences in superficial textures, the defects in IR pictures and a color estimation in CIELab. Furthermore, a different image preprocessing has been employed and an Artificial Neural Networks have been used as estimation technique. The system has reached good estimation results with R=96.3 in acidity and R=93.9 in peroxide index.
机译:用于测量橄榄油质量的最重要参数是酸度和过氧化物指数,目前,它们在实验室中测量,使用从接收过程中的批次中提取的橄榄样品测量。这项工作的目的是提供一种基于计算机视觉可见和红外(IR)通道的自动检测系统,以便自动推断这些参数。该提案利用肤浅纹理的差异,IR图片中的缺陷以及CIELAB中的颜色估计。此外,已经采用了不同的图像预处理,并且已经用作人工神经网络作为估计技术。该系统已达到良好的估计结果,其在酸度下r = 96.3和过氧化物指数中的r = 93.9。

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