Quantifying the weight of fingerprint evidence through the spatial relationship, directions and types of minutiae observed on fingermarks.
This paper presents a statistical model for the quantification of the weight of fingerprint evidence. Contrarily to previous models (generative and score-based models), our model proposes to estimate the probability distributions of spatial relationships, directions and types of minutiae observed on...
| Publicado en: | Forensic Science International Vol. 248; pp. 154 - 172 |
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| Autores principales: | , , , , |
| Formato: | Journal Article |
| Publicado: |
Elsevier B.V.
Mar2015
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=109703532&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 109703532 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 03790738 3L0 jtl: Forensic Science International issn: 03790738 maglogo: N pubinfo: dt: Mar2015 vid: 248 pid: 82545 pub: Elsevier B.V. place: Philadelphia, Pennsylvania artinfo: ui: 109703532 NLM25637956 2012914009 10.1016/j.forsciint.2015.01.007 NLM25637956 109703532 ppf: 154 ppct: 18 formats: fmt: @attributes: type: P tig: atl: Quantifying the weight of fingerprint evidence through the spatial relationship, directions and types of minutiae observed on fingermarks. aug: au: Neumann, Cedric Champod, Christophe Yoo, Mina Genessay, Thibault Langenburg, Glenn sug: ab: This paper presents a statistical model for the quantification of the weight of fingerprint evidence. Contrarily to previous models (generative and score-based models), our model proposes to estimate the probability distributions of spatial relationships, directions and types of minutiae observed on fingerprints for any given fingermark. Our model is relying on an AFIS algorithm provided by 3M Cogent and on a dataset of more than 4,000,000 fingerprints to represent a sample from a relevant population of potential sources. The performance of our model was tested using several hundreds of minutiae configurations observed on a set of 565 fingermarks. In particular, the effects of various sub-populations of fingers (i.e., finger number, finger general pattern) on the expected evidential value of our test configurations were investigated. The performance of our model indicates that the spatial relationship between minutiae carries more evidential weight than their type or direction. Our results also indicate that the AFIS component of our model directly enables us to assign weight to fingerprint evidence without the need for the additional layer of complex statistical modeling involved by the estimation of the probability distributions of fingerprint features. In fact, it seems that the AFIS component is more sensitive to the sub-population effects than the other components of the model. Overall, the data generated during this research project contributes to support the idea that fingerprint evidence is a valuable forensic tool for the identification of individuals. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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