recognition to improve the specific performance of technologies designed to assist in firearms identification and to address systematically the problems that prevent current technologies from being scaled up.


Forensic analysis of firearms has traditionally been a process in which an expert examiner is charged with the task of matching spent cartridge cases or bullets with a particular firearm or linking evidence from different crimes to a particular weapon. This is fundamentally a process of verification, in which a hypothesis—that the same firearm was used in two firings—is accepted, rejected, or found to be inconclusive. This judgment is made on the basis of physical markings on the cartridge case or bullet, generally observed visually by the firearms examiner with the assistance of a microscope. An examiner must usually support the judgment of a match in court and thus seeks considerable evidence of a match in order to reach the conclusion of a definitive match.

In considering the development of ballistic image databases, it is critically important to distinguish this traditional process of verification, in which there are external reasons that lead investigators to ask whether two bullets or casings were fired by the same firearm, from the process of search in which a number of cases are compared with the goal of finding possible reasons to tie them together. In verification, one is validating or rejecting a specific hypothesis on the basis of additional data, in this case forensic evidence. In search, one is trying to come up with potential hypotheses by filtering through potentially large amounts of data. In general, search tasks are considerably more difficult than verification tasks. This same distinction arises in a number of areas other than ballistics, most notably biometrics. For instance, it is a considerably easier task to determine whether two particular fingerprints match each other than it is to find potentially matching fingerprints from a large database.

A central distinction between verification and search is that in a verification task one can be quite conservative, not accepting a match unless there is overwhelming evidence. In law enforcement this is ensured by the courts and expert testimony. In fingerprint-based security systems, this is ensured by requiring a very high-quality match of an individual’s stored fingerprint to the one read by a scanner, even if that requires several attempts by a user to have the print correctly read. In contrast, for a search task, if a system is too conservative it does not generate any useful potential matches, or hypotheses, to consider. Yet if a search system is not conservative enough, it generates too many useless hypotheses or false leads. Neither of these approaches is very useful. Thus, for search-based tasks, such as a ballistic image database, it is very important that the system have both a low false

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