Segmentation Procedure for Fingerprint Area Detection in Image Based on Enhanced Gabor Filtering

fingerprint, fingerprint area detection, semantic conformance testing, image segmentation, Gabor filters

This paper describes a detailed description of segmentation procedure for fingerprint area detection in a digital fingerprint image. Purpose of this procedure is to extract very precisely the fingerprint area and to separate it from the image background. The precise fingerprint area detection is important not only for vendors of minutiae extraction algorithms but also for semantic conformance testing for finger minutiae data in the newly created international standard. Our segmentation procedure was evaluated for real-world scenario, so the used fingerprints were scanned from real dactyloscopic fingerprint cards. These fingerprints were taken from Ground Truth Database of fingerprints (used subset of GTD originally belongs to NIST SD14 and SD29 databases). Our procedure had to deal with specific problems and properties of these images such as handwritten or printed characters, drawings or specific noise in the background or spread over the fingerprint itself. Our approach was compared with three other methods and yields significantly better results than the best of the benchmarked methods.