Towards a Better Understanding of the Performance of Latent Fingerprint Recognition in Realistic Forensic Conditions

Puertas, Maria C.; Ramos, Daniel; Fiérrez, Julián; Ortega‐Garcia, Javier; Exposito, N.

doi:10.1109/icpr.2010.405

Cited by 6 publications

(6 citation statements)

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“…In recent years, palmprints have attracted more attention as a relevant and secure biometric method of personal identification, both in the civil and criminal fields. But while prints produced under controlled conditions, with ink or livescan methods provide high quality images (high‐resolution), although not always free of noises (disturbance of principal lines, wrinkles) that degrade the quality of some portions of the image, latent prints often give rise to low‐resolution images [30,32,33,37].…”

Section: Discussionmentioning

confidence: 99%

“…Nevertheless, the extraction of stable and robust features from palmprints is still a problem, not only because of the low quality of the patterns of palmprints, but also because of the computational complexity for the large image size. Puertas et al [37] showed that the combination of manual matching done by an expert and the matching done by an AFIS has shown that can outperform the expert and the system alone, because high performance degradation happens in the automatic extraction of minutiae compared to the manual extraction done by human experts. This could be even more relevant in palmprints.…”

Section: • Delta D Was Found In All Cases In the Ulnar Area Of The Dimentioning

confidence: 99%

“…In fingerprints, identification has been demonstrated that the combination of manual matching done by an expert and the matching done by an AFIS can outperform the expert and the system alone [37]. Results show high performance degradation in the automatic extraction of minutiae on fingerprints compared to manual extraction by human experts, which increases in the case of latents.…”

Section: Introductionmentioning

confidence: 99%

“…The correspondence analysis showed, with an inertia of 58.9%, a statistically significant association (Chi 2 = 1880.4 gl = 164 P < .0001) between the deltas and the location areas, separating the first dimension, with 38.68% of the inertia, deltas a, b, and d, located in the lateral areas of the hand, both radial and ulnar, from deltas c and t, located in the central areas of the hand.4 | DISCUSS IONIn recent years, palmprints have attracted more attention as a relevant and secure biometric method of personal identification, both in the civil and criminal fields. But while prints produced under controlled conditions, with ink or livescan methods provide high quality images (high-resolution), although not always free of noises (disturbance of principal lines, wrinkles) that degrade the quality of some portions of the image, latent prints often give rise to low-resolution images[30,32,33,37].…”

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Distribution of the minutiae in palmprints: Topological and sexual variability

Rivaldería

Gutiérrez‐Redomero

2020

Journal of Forensic Sciences

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Dermopapillary ridges that cover the surface of the fingers, the palm, and the sole of the feet, separated by furrows, are configured in patterns that, once formed in early stages of gestation, will be preserved throughout the individual's life, even after death if the skin is conserved. The inheritance of dermopapillary ridges is multifactorial and thus determined by both genetic and environmental factors. It is a polygenic inheritance that interacts with environmental factors, but only during the fetal formation stage. For this reason, once developed, they are not modified by the environment, and remain unaltered, except for traumatic damage or skin wear, throughout the life of the individual [1-6]. Like fingerprint identification, palmprint identification is based on the comparison of information obtained from friction ridges between a print of known origin (fingerprint) and a print of unknown origin (fingermark). Variability can be compared in palmprints following the taxonomy based on the one proposed by Maltoni et al. [7], separating the features into three levels: Features extracted at a global level from the friction ridges and flexion creases. These include the orientation of the lines, the separation between them, the

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Section: Discussionmentioning

confidence: 99%

Section: • Delta D Was Found In All Cases In the Ulnar Area Of The Dimentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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confidence: 99%

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Distribution of the minutiae in palmprints: Topological and sexual variability

Rivaldería

Gutiérrez‐Redomero

2020

Journal of Forensic Sciences

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“…(Montesanto et al, 2007) have studied the fingerprint verification based on the fuzzy logic, where they combined the results obtained using three different methods of minutiae extraction: the sequential method, the reactive agent and the neural classification system. (Puertas et al, 2010) studied the performance of a fingerprint recognition technology, in several practical scenarios of interest in forensic casework. First, the differences in performance between manual and automatic minutiae extraction for latent fingerprints were presented.…”

Section: Other Approachesmentioning

confidence: 99%