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Can I read Independent component analysis of hyperspectral data measured from overlapping latent fingermarks: Forensic potential of independent component images on EtoBox?
Independent component analysis of hyperspectral data measured from overlapping latent fingermarks: Forensic potential of independent component images by Atsushi Nakamura; Norimitsu Akiba; Kazuhito Hibino; Hidetoshi Kakuda; Karen Kawada; Masashi Karasawa; Mari Sakai; Takayuki Sota is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.
What is Independent component analysis of hyperspectral data measured from overlapping latent fingermarks: Forensic potential of independent component images about?
Overlapping fingermark images are sometimes discarded because fingermark collation for the individual fingermarks is difficult. Fluorescence hyperspectral data (HSD) measured using the models of double overlapping fingermarks obtained under the excitation of a high-power, continuous wave, green laser is suitable for obtaining individual fingermark images. However, there are limitations such as the problems on each spectrum of the individual fingermark and the forensic value of the obtained images. In this study, independent component analysis (ICA) was applied to the fluorescence HSD obtained from the models of doubly overlapping fingermarks, to obtain independent component (IC) spectra and the corresponding IC images. Forensic value of the obtained IC images was examined, considering the possibility of fingermark collation in masked fashion to the model sample information. The IC images obtained from the HSD had enough potential to enable extracting twelve minutiae required for fingermark collation if the image quality was good.
Who reads Independent component analysis of hyperspectral data measured from overlapping latent fingermarks: Forensic potential of independent component images?
It is typically read by researchers, students, and practitioners in Biochemistry, Genetics and Molecular Biology.
- Author
- Atsushi Nakamura; Norimitsu Akiba; Kazuhito Hibino; Hidetoshi Kakuda; Karen Kawada; Masashi Karasawa; Mari Sakai; Takayuki Sota
- Publisher
- Elsevier BV
- Published
- 2023
- Language
- EN
- Field
- Biochemistry, Genetics and Molecular Biology (Life Sciences)