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首页> 外文期刊>International journal of food properties >Application of Near-Infrared Hyperspectral Imaging for Detection of External Insect Infestations on Jujube Fruit
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Application of Near-Infrared Hyperspectral Imaging for Detection of External Insect Infestations on Jujube Fruit

机译:近红外高光谱成像在枣果实外来昆虫侵染检测中的应用

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A hyperspectral imaging system has been built for detecting external insect damage and acquiring reflectance images from jujubes in the near-infrared region of 900–1700 nm. Spectral information was extracted from each jujube, and six optimal wavelengths (987, 1028, 1160, 1231, 1285, and 1464 nm) were obtained using principal component analysis. The first principal component images (PC-1) using the selected six wavelengths were obtained for further image processing. The detection algorithm was then developed based on principal component analysis and two-band ratio (R1160/R1464) coupled with image subtraction algorithm (R1160-R1464). An identification accuracy of 93.1% for insect-infested jujubes and 100% classification rate for the intact ones were achieved. The results of this research demonstrated that it is feasible to discriminate insect-infested jujubes from intact jujubes using the near-infrared hyperspectral imaging technology.
机译:已经建立了一个高光谱成像系统,用于检测外部昆虫的伤害并从900-1700 nm的近红外区域的枣中获取反射图像。从每个枣中提取光谱信息,并使用主成分分析获得六个最佳波长(987、1028、1160、1231、1285和1464 nm)。获得使用所选六个波长的第一主成分图像(PC-1)以进行进一步的图像处理。然后基于主成分分析和两频比(R1160 / R1464)结合图像减法算法(R1160-R1464)开发了检测算法。被昆虫侵染的枣的识别准确率达到93.1%,完整的枣的识别率达到100%。这项研究的结果表明,使用近红外高光谱成像技术将昆虫侵染的枣与完整的枣区别开来是可行的。

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