TY - JOUR
T1 - Automatic removal of binary background components expecting Raman big data and its application to human hair imaging
AU - Ujuagu, Akunna Francess
AU - Furuta, Momoko
AU - Nakabayashi, Takakazu
AU - Ito, Len
AU - Morita, Shin Ichi
N1 - Publisher Copyright:
© 2020 The Japan Society of Applied Physics.
PY - 2020/3/1
Y1 - 2020/3/1
N2 - 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.
AB - 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.
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U2 - 10.35848/1882-0786/ab6fb1
DO - 10.35848/1882-0786/ab6fb1
M3 - Article
AN - SCOPUS:85082680499
SN - 1882-0778
VL - 13
JO - Applied Physics Express
JF - Applied Physics Express
IS - 3
M1 - 036501
ER -