Image enhancement of pre-processed fingerprints using color information and spatial frequency filtering

Image enhancement of pre-processed and colored fingerprints such as ninhydrin-processed fingerprints in a complex-patterned 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.