Abstract
Rarity of latent fingerprints is important to law enforcement agencies in forensics analysis. While tremendous efforts have been made in 10-print individuality studies, latent fingerprint rarity continues to be a difficult problem and has never been solved because of the small finger area and poor impression quality. The proposed method is able to predict the core points of latent prints using Gaussian processes and align the latent prints by overlapping the core points. A novel generative model is also proposed to take into account the dependency on nearby minutiae and the confidence of minutiae in the probability of random correspondence calculation. The new methods are illustrated by experiments on the well-known Madrid bombing case. The results show that the probability that at least one fingerprint in the FBI IAFIS databases (over 470 million fingerprints) matches the bomb site latent is 0.93 which is large enough to lead to misidentification.
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Su, C., Srihari, S.N. (2011). Latent Fingerprint Rarity Analysis in Madrid Bombing Case. In: Sako, H., Franke, K.Y., Saitoh, S. (eds) Computational Forensics. IWCF 2010. Lecture Notes in Computer Science, vol 6540. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19376-7_15
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DOI: https://doi.org/10.1007/978-3-642-19376-7_15
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