Due to their uniqueness and consistency, fingerprints identification is among the most promulgated biometrics. For many years now fingerprints have been used for identification and only recently due to advancement in computers they have become automated (Maltoni, Maio, Jain, & Prabhakar, 2009). Fingerprint identification is popularized since it is easy to acquire, availability of numerous sources to collect from that is the ten fingers, and their established use of collections by law enforcement and immigration. This practice of finger identification started in the late 19th century with Sir Francis Galton who defined some of the characteristics with which fingerprints can be identified (Maltioni et al., 2009). Seemingly, these characteristics have been used to develop the current fingerprint automated technology.
According to Sir Francis Galton, the ridges of the friction skin are discontinuous; rather they have several interruptions which are referred to as Galton details or Galton characteristics. These characteristics are made up of three basic types (Maltioni et al., 2009): the ridge endings which is a minutia point at the ending of a friction ridge, the bifurcations which is a ridge that divides and looks like a fork, and dots. During the formation and positioning of the skin ridge friction, these characteristics are haphazardly scattered, like the all components of friction ridge skin cannot be duplicated from one individual to another or from one finger to the next thereby individualizing an individual from another. The Galton characteristic are usually vital when making an identification, even though there is no specific number of points to make an identification.
Fingerprints are made up of three unique patterns namely loops, whorls, and arches. Therefore, the difference between Galton characteristics and the patterns is patterns provide general characteristics while the Galton characteristics provide specific characteristics. For instance, the pattern type is used by analysts to make initial comparisons which enable them to include or exclude a known fingerprint from further analysis. Hence, to match a print, the analyst will use Galton characteristics in identifying specific characteristics on a suspect fingerprint with the same data from the known fingerprint.
The impact of Daubert on forensic sciences has been tremendous. For instance, forensic scientific evidence that was once accepted by the court have to undergo reevaluation under Daubert, and in some cases, they are excluded. A good example is a controversy generated by a federal district courts exclusion of identification using fingerprint analysis (Fradella, O'Neill, & Fogary, 2003). Furthermore, Kumho which is an extended form of Daubert to technical or non-scientific field has further affected the forensic science since it does not explain how to determine how an expert testimony is reliable on such non-scientific fields. Additionally, the Daubert-Kumho has had implications on the handwriting analysis. A lot of courts have dismissed handwriting analysis under Daubert while others still admit it, and others have put limitations on the scope of the testimony in preventing identification using the analysis of handwriting. Therefore, the increase in a reevaluation of evidentiary value by the courts of forensic science evidence raises questions such as whether the challenges to many types of forensic evidence will increase? This concern is mostly visible to comparing of humans for similarities example in the identification of firearms and tool mark, hair and fiber comparisons, and questioned documents comparisons. Also, the concerns are raised in the use of non-scientific forensic techniques such as the utilization of Luminol and phenolphthalein as a tentative test for blood.
Fradella, H. F., O'Neill, L., & Fogary, A. (2003). The impact of Daubert on forensic science. Pepp. L. Rev., 31, 323.
Maltoni, D., Maio, D., Jain, A., & Prabhakar, S. (2009). Handbook of fingerprint recognition. Springer Science & Business Media.
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