Quality-assured fingerprint image enhancement and extraction using hyperspectral imaging

Hyperspectral imaging is an emerging technology with a wide range of potential applications including remote sensing, chemical and pharmaceutical, food quality control and forensic science. In this paper, fingerprint extraction from various surfaces using visible and near-infrared hyperspectral imaging for forensic applications is explored. Firstly, spectral analysis is conducted, where principal component analysis (PCA) is employed to determine the most informative linear band combinations of the hypercube. Then, based on the fingerprint quality index measurement, the optimal principal component is determined to have the highest quality score. Accordingly, the fingerprint image is also enhanced due to the effect of PCA. Comprehensive experimental results are reported and analysed.