Automated Fingerprint Identification System (AFIS) refers to a computerized system used to store fingerprint images. Typically, investigators feed new print images into AFIS to identify the best matches. Accordingly, the identification process allows investigators to narrow their search parameters. Usually, AFIS technicians perform the final analyses of retrieved images to maintain accuracy. Prior to the computerization of such systems, the process of comparing fingerprint images was tedious and sometimes inaccurate. The development of AFIS, however, allowed technicians to perform comparisons within minutes and achieve a relatively higher accuracy of image identification.
Creation of Fingerprint Images
Fingerprints appear as a series of darkened lines representing the peaking aspects of the ridge skin whereas white spaces between the ridges represent the shallow portions of the ridge skin. Typically, fingerprint images are created in a variety of ways. One method utilizes finger-scanning to obtain fingerprints. Finger-scan systems may include storage and matching components, as well as image acquisition and image processing hardware. Scanning devices with such systems create quality images that promote fingerprint matching, feature extraction, thinning, and edge detection. In addition, the technologies can capture images exceeding five hundred dots per inch (DPI) to help forensic experts in identifying fingerprints.
Fingerprint Characteristics used for Comparison
In principle, fingerprint identification focuses on minutia or ridge endings. Information obtained from the ridge impressions of a fingerprint may include the friction ridges’ flow, the absence or presence of specific characteristics on ridge paths, and the detailed aspects of each ridge. Friction ridges may not show a continuous flow in the pattern of a fingerprint image. Instead, they may exhibit features such as dividing ridges or ending ridges. Accordingly, AFIS interprets the flows of all ridges to classify the fingerprint and extract minutia details.
Before the 1970s, forensic officers were trained to analyze inked fingerprints. In particular, they observed minutiae details like enclosures, bifurcations, ridge dots, and ridge endings. Next, they coded them and filed fingerprint cards according to fingerprint patterns like arches, loops, and whorls using Henry’s Classification System. Unfortunately, the processing of fingerprints using the manual method took several weeks to complete because a fingerprint bureau had to facilitate the analysis. Towards the end of the 1970s and the start of the 1980s, analog systems that combined filing codes with manual coding on computers were developed. The technique allowed trained staff to check collected fingerprints against computer-generated hard-copies of inked images. Nonetheless, the process was incredibly grueling and only eased after the 1986’s commercial release of AFIS database. Subsequently, software vendors started marketing their private AFIS products, which led to the emergence of confused markets and incompatible databases. By 2005, several firms had developed standard applications for bringing the national database together. The approach established a comprehensive library of prints and eased the agencies’ task of selecting suitable software for running AFIS database.
Presently, AFIS employs three approaches to compare fingerprints’ characteristics. First, investigators may lift ten-prints or the prints of every digit from an individual. The prints are then examined against the national database of cataloged ten-prints. The second approach requires trained staff to check a latent print against a ten-print catalog. Thirdly, investigators can check ten-prints obtained from a body or scene against cataloged individual latent prints. Unidentified fingerprints are often kept in the AFIS database and verified automatically against new entries.
In conclusion, AFIS is a computerized system used to store fingerprint images, which can be obtained through fingerprint-scanning. Accordingly, scanning devices can create quality images that facilitate fingerprint matching, feature extraction, thinning, and edge detection. Subsequently, AFIS employs three ways of comparing fingerprint characteristics. The approaches include lifting ten-prints from an individual and examining them against the national database of cataloged ten-prints. Thus, AFIS can effectively identify individuals using fingerprints gathered from a body or scene of a crime.
