Estimating the time of fingerprint deposition at a crime scene provides clues to the duration since the crime. We have previously shown that when the fingerprint was continuously irradiated with an ultraviolet laser, the intensity of fluorescence presented just after impression decreases, and the other fluorescence appeared at longer wavelengths and its intensity became stronger over time. In this study, the possibility of estimating the elapsed time was examined using the aging function originally proposed by the research group of University of Amsterdam. Fingerprints were stored for up to two years, and fluorescence spectra were periodically measured by excitation with the ultraviolet laser, to calculate the aging rate of the aging function as dividing the former fluorescence intensity by the latter one. As a result, the aging rate were shown to increase in the order of greater UV influence and higher humidity. Furthermore, aged fingerprints were visualized using a fluorescence peak that increases with time.
Fingerprints provide important clues to criminal investigations. Although there are various fingerprint detection methods such as powder or liquid, optical methods are useful for non-contact and non-destructive detection. However, in case of two or more overlapping fingerprints, they might be discarded because the features cannot be assigned to the individual fingerprints. The fact that the composition of fingerprints is unique for each individual is well known, so if this causes differences in inherent emission spectra of fingerprints, it is possible to separate overlapping fingerprints. Hyperspectral imaging is used in a variety of fields and also in forensic science, such as fingerprint detection. In this study, the separation of overlapping fingerprints using multivariate analysis was performed for effective use of fingerprints. Fluorescence hyperspectral data of overlapping fingerprints excited by a 532 nm CW laser were acquired by hyperspectral imaging in the visible region. Fluorescence spectra from fingerprints were measured in the wavelength range from 560 to 700 nm with the wavelength resolution of 1.1 nm. Thus, the hyperspectral data cube consisted of 600 (image) × 960 (image) × 128 (wavelength) pixels. An image, which are integrated over the wavelength range, showed the two fingerprints overlapping each other. Separation of overlapping fingerprints was tried applying principal component analysis, multivariate curve resolution - alternating least squares analysis, and partial least squares analysis to the fluorescence hyperspectral data. Among three methods examined herein, partial least squares analysis was found to be most effective for fingerprint separation.
Image enhancement of pre-processed and colored fingerprints such as ninhydrin-processed fingerprints in a complexpatterned background is important in crime investigation. Contrast adjustment, which is one of the most common image processing methods usually has a limitation in enhancing such fingerprints because of interference superposing patterns of the background. We propose three image processing methods using color information or spatial frequency information of an RGB material image. The first method is a hue-based method, which converts hue values of each pixel in CIELAB color space to corresponding brightness. The second method is a PCA-based method, which conducts principal component analysis on a color data of the material image and reconstructs three principal component images. Both proposed methods achieve more enhanced fingerprint images than the contrast adjustment gives. The PCA-based method works well even when the hue-based method does not. As the third proposed method, remaining background periodic patterns are removed for fingerprint enhancement by spatial frequency filtering using the Fast Fourier Transformation. According to estimated frequency components of background periodic patterns, we altered the width of frequency removing region of such background patterns, suggesting that there is an optimal width for each material for fingerprint enhancement. Also, we tested four different edge profiles of the frequency removing region and checked that an edge profile with gradual change tends to reduce the effect of suppressing the background periodic patterns compared to an edge profile with sharp change under the equivalent width of removing region of frequency components.
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