Automatic removal of binary background components expecting Raman big data and its application to human hair imaging

Akunna Francess Ujuagu, Momoko Furuta, Takakazu Nakabayashi, Len Ito, Shin Ichi Morita

研究成果: Article査読

1 被引用数 (Scopus)

抄録

We developed an automated method for removing binary background components from observed Raman spectra by tuning the scaling factors to seek the minimum lengths of the subtracted spectra. This method is effective, especially for large data including imaging data. For application, 400 Raman imaging spectra of a sliced cross section of a strand of gray human hair, fixed by glue on glass, were subjected to the proposed method by removing the glass and glue information. After the binary background removal, principal component analysis successfully detected small but important signals of tryptophan, which is peculiar to the hair cortex.

本文言語English
論文番号036501
ジャーナルApplied Physics Express
13
3
DOI
出版ステータスPublished - 2020 3 1

ASJC Scopus subject areas

  • 工学(全般)
  • 物理学および天文学(全般)

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