Identification of maize kernel embryo based on hyperspectral imaging technology and PCA

Wenqian Huang, Jiangbo Li, Chi Zhang, Baohua Zhang*, Baihai Zhang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

To segment the embryo from the maize kernel, a hyperspectral imaging system has been built for acquiring reflectance images from maize kernels in the spectral region between 500 and 950 nm. Hyperspectral images of maize samples were evaluated using principal components analysis (PCA) with the goal of selecting several effective wavelengths that could potentially be used in a multispectral imaging system. The second principal component images using three effective wavelengths 510, 555 and 575 nm in the visible spectral (VIS) had good identification results under investigation. For the investigated independent test samples, 97.0% of embryos on samples were correctly separated from the maize kernels.

Original languageEnglish
Pages (from-to)243-247
Number of pages5
JournalNongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Volume28
Issue numberSUPPL. 2
DOIs
Publication statusPublished - Oct 2012

Keywords

  • Effective wavelengths
  • Embryo
  • Hyperspectral imaging
  • Image recognition
  • Maize kernel
  • Models
  • Principal components analysis

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