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首页> 外文期刊>Journal of food quality >Navel Orange Maturity Classification by Multispectral Indexes Based on Hyperspectral Diffuse Transmittance Imaging
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Navel Orange Maturity Classification by Multispectral Indexes Based on Hyperspectral Diffuse Transmittance Imaging

机译:基于高光谱漫透射成像的多光谱指标脐橙成熟度分类

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Maturity grading is important for the quality of fruits. Nondestructive maturity detection can be greatly beneficial to the consumer and fruit industry. In this paper, a hyperspectral image of navel oranges was obtained using a diffuse transmittance imaging based system. Multispectral indexes were built to identify the maturity with the hyperspectral technique. Five indexes were proposed to combine the spectra at wavelengths of 640, 760?nm (red edges), and 670?nm (for chlorophyll content) to grade the navel oranges into three maturity stages. The index of seemed to be more appropriate to classify maturity, especially to distinguish immature oranges that can be straightly identified in accordance with the value of this index . Different indexes were used as the input of linear discriminate analysis (LDA) and of -nearest neighbor (-NN) algorithm to identify the maturity, and it was found that -NN with could reach the highest correct classification rate of 96.0%. The results showed that the built index was feasible and accurate in the nondestructive classification of oranges based on the hyperspectral diffuse transmittance imaging. It will greatly help to develop low-cost and real-time multispectral imaging systems for the nondestructive detection of fruit quality in the industry.
机译:成熟度分级对水果的质量很重要。非破坏性成熟度检测对消费者和水果行业可能非常有利。在本文中,使用基于漫透射成像的系统获得了脐橙的高光谱图像。建立了多光谱索引以使用高光谱技术识别成熟度。提出了五项指标,以结合波长分别为640、760?nm(红色边缘)和670?nm(用于叶绿素含量)的光谱,以将脐橙分为三个成熟阶段。指数似乎更适合分类成熟度,尤其是区分可以根据该指数的值直接识别的未成熟橙子。使用不同的指标作为线性判别分析(LDA)和-最近邻(-NN)算法的输入来识别成熟度,发现-NN可以达到96.0%的最高正确分类率。结果表明,基于高光谱漫透射成像,建立的指标在橙子的无损分类中是可行和准确的。这将极大地有助于开发低成本,实时的多光谱成像系统,以用于行业中水果质量的无损检测。

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