期刊文献+

Detection of Thrips Defect on Green-Peel Citrus Using Hyperspectral Imaging Technology Combining PCA and B-Spline Lighting Correction Method 被引量:5

Detection of Thrips Defect on Green-Peel Citrus Using Hyperspectral Imaging Technology Combining PCA and B-Spline Lighting Correction Method
下载PDF
导出
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. 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.
出处 《Journal of Integrative Agriculture》 SCIE CAS CSCD 2014年第10期2229-2235,共7页 农业科学学报(英文版)
基金 supproted by the National Key Technology R&D Program of China(2012BAF07B05)
关键词 hyperspectral images principal component analysis lighting correction green-peel citrus thrips defect hyperspectral images, principal component analysis, lighting correction, green-peel citrus, thrips defect
  • 相关文献

参考文献8

二级参考文献122

共引文献332

同被引文献63

引证文献5

二级引证文献41

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部