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An automated system for detecting the infected figs by hyperspectral image analysis

机译:一种自动化系统,用于检测感染的感染图谱的斑点图像分析

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Turkey is the major producer of fig fruit and is the biggest dried fig exporter in the World. However, aflatoxin and mold related effects degrade the figs quality and make them inappropriate for human consumption. Aspergillus niger is one of these molds that degrades the quality and turns the color of figs into black. The figs infected by A. niger need to be eliminated from the sound figs before consumption. Traditionally, these figs are detected by manually testing each fig sample. However, manual testing is labor intensive and includes the risk of spreading the molds to the sound samples. In this study, a hyperspectral imaging and classification system is proposed to detect the A. Niger infected figs by non-destructive approach. The infected figs are detected by 100% accuracy by the proposed method.
机译:土耳其是图果实的主要生产国,是世界上最大的干燥无花果出口商。然而,黄曲霉毒素和模具相关效果降低了无花果的质量,使其不适合人类消费。曲霉虫是这些模具之一,可以降低质量,并将图1的颜色变为黑色。由A.尼日尔感染的无花果需要在消耗之前从声音图中消除。传统上,通过手动测试每个数字样本来检测这些无花果。然而,手动测试是劳动密集型,包括将模具扩散到声音样本的风险。在该研究中,提出了一种超细的成像和分类系统来通过非破坏性方法检测A. niger感染无花果。通过所提出的方法通过1​​00%的精度来检测感染的无花果。

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