Fingerprint enhancement by spectral analysis techniques

Abstract

This paper presents techniques from spectral analysis that can be used for the enhancement and restoration of deteriorated latent fingerprints, which do not have adequate quality for their positive identification. The use of fingerprints as evidence of crime has been one of the most important utilities in forensics since the late 19/sup th/ century. Following the acquisition of a latent fingerprint, there are two operations to be performed: latent fingerprint enhancement and matching. To facilitate more accurate extraction of prominent features in the fingerprint, enhancement has to be performed in order to eliminate the noise and variety of background patterns. Matching is performed by comparing the enhanced latent fingerprint with one of the fingerprints already in a database. The latent fingerprints are often blurred, incomplete, degraded, and their spatial definition is not clear. These features make their classification and comparison very difficult if not impossible. For the solution of this problem, we analyzed some spatial non-linear filters and frequency domain filters using adaptive fast Fourier transform. As a result of the analysis we found that applying selective filters to the Fourier spectra, the resulting image showed prominent features in fingerprints that could not be extracted by other enhancement techniques.