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Estimation of citrus canker lesion size using hyperspectral reflectance imaging

International Journal of Agricultural and Biological Engineering 2013年第3期6卷 41-51页

作者： Nikhil P.Niphadkar Thomas F.Burks Jianwei Qin Mark A.Ritenour ATW Automation Inc. DaytonOH 45402USA Department of Agricultural and Biological Engineering University of FloridaGainesvilleFL 32611USA U.S.Department of Agriculture BeltsvilleMD 20705USA Department of Horticultural Sciences University of FloridaGainesvilleFL 34945USA

The Citrus industry has need for effective approaches to remove fruit with canker before they are shipped to selective international market such as the European *** research aims to determine the detectable size limit for cankerous lesions using hyperspectral imaging *** developed multispectral algorithms using visible to near-infrared wavelengths,were used to segregate cankerous citrus fruits from other peel conditions(normal,greasy spot,insect damage,melanose,scab and wind scar).However,this previous work did not consider lesion size.A two-band ratio method with a simple threshold based classifier(ratio of reflectance at wavelengths 834 nm and 729 nm),which gave maximum overall classification accuracy of 95.7%,was selected for lesion size estimation in this *** smallest size of cankerous lesion detected in terms of equivalent diameter was 1.66 *** effect of variation of threshold values and number of erosion cycles(applying morphological erosion multiple times to the image)on estimation of smallest detectable lesion was *** was found that small threshold values gave better canker classification accuracies,while exhibiting a lower overall classification ***,higher threshold values portrayed the opposite *** threshold value of 1.275 gave the optimum tradeoff between canker classification accuracy,overall classification accuracy and minimal lesion size *** the number of erosion cycles reduced detection rates of smaller canker lesions,leading to the conclusion that a single erosion cycle gave the best size estimation *** erosion kernel of the size 3 mm×3 mm was used during the exploration.

关键词： citrus canker lesion size disease detection hyperspectral reflectance imaging image classification multispectral algorithm size detection limit

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