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| Detection of Thrips Defect on Green-Peel Citrus Using Hyperspectral Imaging Technology Combining PCA and B-Spline Lighting Correction Method |
| DONG Chun-wang, YE Yang, ZHANG Jian-qiang, ZHU Hong-kai , LIU Fei |
1、Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou 310008, P.R.China
2、School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, P.R.China |
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摘要 In order to find an effective method of detecting thrips defect on green-peel citrus, a defect segmentation method was developed using a single threshold value based on combination of characteristic wavelengths principal component analysis (PCA) and B-spline lighting correction method in this study. At first, four characteristic wavelengths (523, 587, 700 and 768 nm) were obtained using PCA of Vis-NIR (visible and near-infrared) bands and analysis of weighting coefficients; secondarily, PCA was performed using characteristic wavelengths and the second principal component (PC2) was selected to classify images; then, B-spline lighting correction method was proposed to overcome the influence of lighting non-uniform on citrus when thrips defect was segmented; finally, thrips defect on citrus was extracted by global threshold segmentation and morphological image processing. The experimental results show that thrips defect in citrus can be detected with an accuracy of 96.5% by characteristic wavelengths PCA and B-spline lighting correction method. This study shows that thrips defect on green-peel citrus can be effectively identified using hyperspectral imaging technology.
Abstract In order to find an effective method of detecting thrips defect on green-peel citrus, a defect segmentation method was developed using a single threshold value based on combination of characteristic wavelengths principal component analysis (PCA) and B-spline lighting correction method in this study. At first, four characteristic wavelengths (523, 587, 700 and 768 nm) were obtained using PCA of Vis-NIR (visible and near-infrared) bands and analysis of weighting coefficients; secondarily, PCA was performed using characteristic wavelengths and the second principal component (PC2) was selected to classify images; then, B-spline lighting correction method was proposed to overcome the influence of lighting non-uniform on citrus when thrips defect was segmented; finally, thrips defect on citrus was extracted by global threshold segmentation and morphological image processing. The experimental results show that thrips defect in citrus can be detected with an accuracy of 96.5% by characteristic wavelengths PCA and B-spline lighting correction method. This study shows that thrips defect on green-peel citrus can be effectively identified using hyperspectral imaging technology.
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Received: 19 June 2013
Accepted:
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| Fund: This work was supproted by the National Key Technology R&D Program of China (2012BAF07B05). |
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Corresponding Authors:
YE Yang, Tel: +86-571-86653155, E-mail: yeyang@tricaas.com
E-mail: yeyang@tricaas.com
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| About author: DONG Chun-wang, E-mail: dongchunwang@tricaas.c |
Cite this article:
DONG Chun-wang, YE Yang, ZHANG Jian-qiang, ZHU Hong-kai , LIU Fei.
2014.
Detection of Thrips Defect on Green-Peel Citrus Using Hyperspectral Imaging Technology Combining PCA and B-Spline Lighting Correction Method. Journal of Integrative Agriculture, 13(10): 2229-2235.
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