Some challenges in forensic fingerprint classification and interpretation

Abstract

The usage of fingerprints is no longer limited to crime investigation. And automated fingerprint identification systems have been developed for a variety of applications. However, in law enforcement agency manual categorization and analysis are still an indispensible part of fingerprint operation mainly for the following two reasons: (1) Automated fingerprint classification and identification systems are far from perfection. They can help to expedite the identification process, but cannot completely replace human fingerprint experts in terms of identification accuracy; (2) Fingerprint classification can help speed up the automated searching process as fingerprint databases become overwhelmingly large. In this paper, we review existing classification systems, including Henry, Vucetich, Battley, and NCIC classification systems, and look into the challenges of classifying certain ambiguous fingerprints and interpreting latent prints. By reviewing literature and a representative case of fingerprint misidentification, we analyze the objective and subjective factors contributing to erroneous and inconsistent identification.

A Novel Approach for an Interoperable Biometric Verification

“…A minutia is a point that is located on the change of continuity of the ridges lines. Among the most used characteristic points in the matching algorithms, we have the bifurcation ridges and ending ridges as indicated in [4]. Figure 2 shows the schema of these two minutiae.…”

A State of Art for Survey of Combined Iris and Fingerprint Recognition Systems

“…The fingerprint is one of the traditional methods of identifying people, and it has been used widely, but it is not accurate enough. For example, it may be inconspicuous in the elderly on the other hand, the iris of the eye is one of the subtle and unchanging features with time [26][27][28]. Still, it suffers from some problems in the way the image is taken, as it can affect the distance, lighting, and direction of the person that can affect the quality of the captured image [29][30][31] , and this has led to the emergence of many studies and systems that Combines more than one biometric feature.…”