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Vis/NIR hyperspectral imaging for detection of hidden bruises on kiwifruits

机译:可见/近红外高光谱成像,可检测奇异果上的隐匿瘀伤

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It is necessary to develop a non-destructive technique for kiwifruit quality analysis because the machine injury could lower the quality of fruit and incur economic losses. Bruises are not visible externally owing to the special physical properties of kiwifruit peel.We proposed the hyperspectral imaging technique to inspect the hidden bruises on kiwifruit. The Vis/NIR (408–1117 nm) hyperspectral image data was collected. Multiple optimal wavelength (682, 723, 744, 810, and 852 nm) images were obtained using principal component analysis on the high dimension spectral image data (wavelength range from 600 nm to 900 nm). The bruise regions were extracted from the component images of the five waveband images using RBF-SVM classification. The experimental results showed that the error of hidden bruises detection on fruits by means of hyperspectral imaging was 12.5%. It was concluded that the multiple optimal waveband images could be used to constructs a multispectral detection system for hidden bruises on kiwifruits.
机译:有必要开发一种用于猕猴桃质量分析的非破坏性技术,因为机器伤害可能会降低水果的质量并造成经济损失。由于奇异果皮的特殊物理特性,从外部看不到瘀伤。我们提出了高光谱成像技术来检查奇异果上隐藏的瘀伤。收集了Vis / NIR(408-1117 nm)高光谱图像数据。使用主成分分析对高维光谱图像数据(波长范围从600 nm到900 nm)获得了多个最佳波长(682、723、744、810和852 nm)图像。使用RBF-SVM分类从五个波段图像的成分图像中提取出瘀伤区域。实验结果表明,利用高光谱成像技术对水果进行隐伤检测的误差为12.5%。结论是,多个最佳波段图像可用于构建奇异果上隐藏的瘀伤的多光谱检测系统。

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