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Detecting Bruises on 'Golden Delicious' Apples using Hyperspectral Imaging with Multiple Wavebands

机译:使用多个波段的高光谱成像检测“金黄色”苹果上的瘀伤

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摘要

In this research, the potential of using a multi-spectral imaging system was investigated for detecting bruises on 'Golden Delicious' apples. For this purpose, a hyperspectral imaging system has been built in the spectral region between 400 and 1000nm. Based on the principal components analysis for the hyperspectral images, four wavebands were selected for a multi-spectral imaging test. The principal components analysis on the multi-spectral images gave very similar results as on the hyperspectral images. The second and third principal components scores images were found to be suitable for identifying the presence of bruises. An image processing and classification algorithm based on moments thresholding was developed. The classification results indicated that, for the sample population used in this experiment, about 93% of the non-bruised apples were recognised as sound. An accuracy of about 86% was achieved for detecting bruises, although all the bruised regions were found to remain in the images after moments thresholding.
机译:在这项研究中,研究了使用多光谱成像系统检测“金色美味”苹果上青肿的潜力。为此,已经在400至1000nm之间的光谱区域中建立了高光谱成像系统。基于高光谱图像的主成分分析,选择了四个波段进行多光谱成像测试。对多光谱图像进行主成分分析得出的结果与对高光谱图像非常相似。发现第二和第三主成分评分图像适合于识别瘀伤的存在。开发了基于矩阈值的图像处理和分类算法。分类结果表明,对于本实验中使用的样本种群,大约93%的未煮熟苹果被认为是有声的。尽管发现所有的瘀伤区域在瞬间阈值之后仍保留在图像中,但检测到瘀伤的准确性仍达到约86%。

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