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量化农产品中的非均匀颜色 第一部分:方法开发

Quantifying nonhomogeneous colors in agricultural materials part I: method development.

作者信息

Balaban M O

机构信息

Fishery Industrial Technology Center, University of Alaska Fairbanks, Kodiak, AK 99615, USA.

出版信息

J Food Sci. 2008 Nov;73(9):S431-7. doi: 10.1111/j.1750-3841.2008.00807.x.

Abstract

Measuring the color of food and agricultural materials using machine vision (MV) has advantages not available by other measurement methods such as subjective tests or use of color meters. The perception of consumers may be affected by the nonuniformity of colors. For relatively uniform colors, average color values similar to those given by color meters can be obtained by MV. For nonuniform colors, various image analysis methods (color blocks, contours, and "color change index"[CCI]) can be applied to images obtained by MV. The degree of nonuniformity can be quantified, depending on the level of detail desired. In this article, the development of the CCI concept is presented. For images with a wide range of hue values, the color blocks method quantifies well the nonhomogeneity of colors. For images with a narrow hue range, the CCI method is a better indicator of color nonhomogeneity.

摘要

使用机器视觉(MV)测量食品和农产品的颜色具有其他测量方法(如主观测试或使用色度计)所没有的优势。消费者的认知可能会受到颜色不均匀性的影响。对于相对均匀的颜色,通过机器视觉可以获得与色度计给出的平均值相似的颜色值。对于不均匀的颜色,可以将各种图像分析方法(色块、轮廓和“颜色变化指数”[CCI])应用于通过机器视觉获得的图像。不均匀程度可以根据所需的细节水平进行量化。在本文中,介绍了颜色变化指数概念的发展。对于具有广泛色调值范围的图像,色块方法能够很好地量化颜色的不均匀性。对于色调范围较窄的图像,颜色变化指数方法是颜色不均匀性的更好指标。

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