Occurrence and associative value of non-identifiable fingermarks

Fingermarks that have insufficient characteristics for identification often have discernible characteristics that could form the basis for lesser degrees of correspondence or probability of occurrence within a population. Currently, those latent prints that experts judge to be insufficient for identification are not used as associative evidence. How often do such prints occur and what is their potential value for association? The answers are important. We could be routinely setting aside a very important source of associative evidence, with high potential impact, in many cases; or such prints might be of very low utility, adding very little, or only very rarely contributing to cases in a meaningful way. The first step is to better understand the occurrence and range of associative value of these fingermarks. The project goal was to explore and test a theory that in large numbers of cases fingermarks of no value for identification purposes occur and are readily available, though not used, and yet have associative value that could provide useful information. Latent fingermarks were collected from nine state and local jurisdictions. Fingermarks included were those (1) collected in the course of investigations using existing jurisdictional procedures, (2) originally assessed by the laboratory as of no value for identification (NVID), (3) re-assessed by expert review as NVID, but with least three clear and reliable minutiae in relationship to one another, and (4) determined to show at least three auto-encoded minutiae. An expected associative value (ESLR) for each mark was measured, without reference to a putative source, based on modeling within-variability and between-variability of AFIS scores. This method incorporated (1) latest generation feature extraction, (2) a (minutiae-only) matcher, (3) a validated distortion model, and (4) NIST SD27 database calibration. Observed associative value distributions were determined for violent crimes, property crimes, and for existing objective measurements of latent print quality. 750 Non Identifiable Fingermarks (NIFMs) showed values of Log10 ESLR ranging from 1.05 to 10.88, with a mean value of 5.56 (s.d. 2.29), corresponding to an ESLR of approximately 380,000. It is clear that there are large numbers of cases where NIFMs occur that have high potential associative value as indicated by the ESLR. These NIFMs are readily available, but not used, yet have associative value that could provide useful information. These findings lead to the follow-on questions, “How useful would NIFM evidence be in actual practice?” and, “What developments or improvements are needed to maximize this contribution?

Automated Fingerprint Identification System: with and without the Possibility of Correction of a Digitalised Image

According to the fact that systems for automatic processing of biometric data are constantly advancing in terms of speed and reliability, as well as in terms of adding new processing capabilities, the question of choosing the appropriate system becomes more important. In this paper the idea is to present the technical and technological solutions of the Automated Fingerprint Identification System with different operating principles, with and without the possibility of correction or coding of a digitized image. Comparisons of different systems were performed in test and production environments. The test database with 10 000 records and about half a million records of dactyloscoped persons in the production of database for testing the performance of search was used. The results have shown that there exists a statistically significant difference (p < 0.001) between examined systems in face fingerprint search according to latent fingerprint databases (which means indirect verification). In the production environment, it was found that there exists statistically significant difference (p < 0.001) in the direct and indirect verification showing advantages and disadvantages of the compared systems

Prevalence of Pores in Latent Fingerprints

Of the many biometric traits recognized today, fingerprints are the most prevalent and familiar. The analysis of fingerprints involves level 1, level 2, and/or level 3 detail in the identification of a potential match. Traditionally, fingerprint matching was completely performed by hand, utilizing the ACE-V method. Thanks to the development of rapidly evolving technology, fingerprint matching has become an automated procedure through the use of fingerprint matching algorithms. In the literature, there has been an increase in the interest of developing Automatic Fingerprint Identification System (AFIS) algorithms that include level 3 details in the matching process. These studies have utilized live scanned and/or inked fingerprints, rather than latent fingerprints. However, practical use of AFIS algorithms involves unknown fingerprints, such as those collected at crime scenes, which are often latent in nature. In addition, research has also found that there is a wide variety in size and shape of pore structure, making automatic detection of pores difficult. The resultant quality of latent fingerprints is subject to various factors at the time of deposition, such as the deposition surface, environmental conditions, and composition of the fingerprint itself. Consequently, these factors, in addition to the inherent variance in pore structure, may very well affect the observance and use of level 3 details within a fingerprint. If the prevalence of pores proves to be unreliable and inconsistent in latent fingerprints, the push for including level 3 detail in the AFIS matching process may all be for nothing. For this reason, the effects of latent fingerprint deposition factors on pore identification needs to be considered and currently appears to be greatly under studied. In effort to begin to fill this gap in the current research, newly deposited latent fingerprints were collected and developed using both black fingerprint powder and cyanoacrylate fuming. Developed fingerprints were subsequently imaged via digital scan or digital camera, and enhanced using either Image J or Adobe\textsuperscript{\textregistered} Photoshop\textsuperscript{\textregistered}. Following image enhancement, pores were manually identified and marked using the Federal Bureau of Investigation (FBI) developed Universal Latent Workstation (ULW) software. Qualitative assessment of the 633 fingerprints collected resulted in 380 usable fingerprints for the remainder of the study. Observations regarding pore count within the replicate fingerprint sets indicated that total pore count/presence was not consistent. The Mann Whitney U test indicated that neither development method, black fingerprint powder nor cyanoacrylate fuming, produced pore data any better or worse than the other. Lastly, assessment of pore location resulted in a greater number of similarity scores being lower than the established threshold, indicating that pore location is not as easily assessed nor interpreted as hoped

AFIS Based Likelihood Ratios for Latent Fingerprint Comparisons

Latent fingerprints are one of the most common pieces of evidence found on a crime scene and represent accidental or unintentional prints collected as part of a criminal investigation. They are caused when the friction ridge skin comes in contact with a surface, and thus requires the use of chemical processing to be visualized with the naked eye. The comparison and identification of fingerprints depends on various factors such as the substrate quality, surface, duration, environmental factors and examiner experience. These factors can result in reduced clarity or content, and can even cause distortions as compared to a fingerprint taken under controlled conditions. Since the release of the National Academy of Sciences (NAS) report in 2009, the field of fingerprint analysis has come under much scrutiny. Specifically, the need for more research into the determination of the accuracy and reliability of the identifications made by fingerprint examiners has been raised.;One such method used for the comparison of latent fingerprint to known prints is through an Automated Fingerprint Identification System (AFIS). The AFIS used in this research was the AFIX Tracker R where where variables were assessed: match score, match minutiae, match status, delta match score and marked minutiae, to determine which variable(s) was a better indicator of a true match. Bayesian networks were then constructed to compute the likelihood ratios to evaluate the dependency of the variables on one another,where the performance of the likelihood ratios in determining the identity of the unknown latent was assessed using Tippett and ECE plots. Receiver Operating Characteristic (ROC) curves and Bayesian networks were constructed to perform statistical analysis of the matches obtained while comparing a latent print to a ten-print card. A combination of Tippett and Empirical Cross Entropy (ECE) plots were used to assess the performance of the AFIX Tracker R in classifying unknown prints. It was observed that a match minutiae of 15 or higher resulted in a 100% true match result whereas for the non-matches,no more than 13 match minutiae were found. Moreover, the delta match scores difference between the matches and non-matches were notable (delta score of 0.1-153 for matches compared to a score of 0-0.1 for the non-matches). Overall, it was determined that approximately 87% of the time a randomly selected known match would have a higher number of match minutiae as compared to a non-match

The retrieval of fingerprint friction ridge detail from elephant ivory using reduced-scale magnetic and non-magnetic powdering materials

An evaluation of reduced-size particle powdering methods for the recovery of usable fingermark ridge detail from elephant ivory is presented herein for the first time as a practical and cost-effective tool in forensic analysis. Of two reduced-size powder material types tested, powders with particle sizes≤40μm offered better chances of recovering ridge detail from unpolished ivory in comparison to a conventional powder material. The quality of developed ridge detail of these powders was also assessed for comparison and automated search suitability. Powder materials and the enhanced ridge detail on ivory were analysed by scanning electron microscopy and energy dispersive X-ray spectroscopy and interactions between their constituents and the ivory discussed. The effect of ageing on the quality of ridge detail recovered showed that the best quality was obtained within 1week. However, some ridge detail could still be developed up to 28days after deposition. Cyanoacrylate and fluorescently-labelled cyanoacrylate fuming of ridge detail on ivory was explored and was less effective than reduced-scale powdering in general. This research contributes to the understanding and potential application of smaller scale powdering materials for the development of ridge detail on hard, semi-porous biological material typically seized in wildlife-related crimes

Latent Print Examination and Human Factors: Improving the Practice Through a Systems Approach: The Report of the Expert Working Group on Human Factors in Latent Print Analysis

Fingerprints have provided a valuable method of personal identification in forensic science and criminal investigations for more than 100 years. Fingerprints left at crime scenes generally are latent prints—unintentional reproductions of the arrangement of ridges on the skin made by the transfer of materials (such as amino acids, proteins, polypeptides, and salts) to a surface. Palms and the soles of feet also have friction ridge skin that can leave latent prints. The examination of a latent print consists of a series of steps involving a comparison of the latent print to a known (or exemplar) print. Courts have accepted latent print evidence for the past century. However, several high-profile cases in the United States and abroad have highlighted the fact that human errors can occur, and litigation and expressions of concern over the evidentiary reliability of latent print examinations and other forensic identification procedures has increased in the last decade. “Human factors” issues can arise in any experience- and judgment-based analytical process such as latent print examination. Inadequate training, extraneous knowledge about the suspects in the case or other matters, poor judgment, health problems, limitations of vision, complex technology, and stress are but a few factors that can contribute to errors. A lack of standards or quality control, poor management, insufficient resources, and substandard working conditions constitute other potentially contributing factors

The Assessment of Fingerprint Quality for a More Effective Match Score in Minutiae-Based Matching Performers

One of the most common types of evidence recovered from a crime scene are latent fingerprints, however these impressions are often of low quality. The quality of a latent fingerprint is described as the degree to which the ridge details can be observed. If the quality of the latent fingerprint is very clear, a minutiae-based matching algorithm with automatic extraction may detect and utilize the minutiae that are truly present in the fingerprint. However, if the impression is of poor quality, the minutiae-based matching algorithm\u27s automatic extraction may detect fewer features and could completely miss features resulting in the return of an unrelated candidate. The aim of this research was to determine a method to improve the match score of latent fingerprints by removing the bad quality regions, where both a subjective and objective methods were utilized. The subjective method utilized the predetermined quality categories of good, bad or ugly to assign a latent fingerprint. After classification, each impression was processed by AdobeRTM PhotoshopRTM and four quality areas were serially removed. In the objective method, each latent fingerprint was assessed with NFIQ algorithm and then MINDTCT algorithm. The MINDTCT algorithm provided a quality map that was used to remove successive portions of each latent fingerprint. The resulting new images from both methods were compared to a database using the two different minutiae-based matching algorithms: AFIX TrackerRTM and BOZORTH3.;The results were examined utilizing the statistical methods of receiver operator characteristic (ROC) curves, area under the ROC curve (AUC), cumulative match characteristic (CMC) curve, Wilcoxon signed-rank test, Spearman\u27s rank correlation and the comparison of the removal methods. ROC curves and the resulting AUC were able to determine that the AFIX TrackerRTM program is a reliable performer with high AUC values, while the BOZORTH3 minutiae-based algorithm did not perform well with low AUC scores of around 0.5. The results produced from the CMC curves showed that the subjective method produced higher rank 1 and top 10 rank identification than the objective method, contrary to what was hypothesized. The correlation scores showed the manual and automatic extraction were weakly correlated to one another. However, a very weak to no correlation between the algorithms of the BOZORTH3 and AFIX Tracker R was observed. The comparison between the subjective and objective methods of removal showed the examiner allowed for a more conservative removal of the fingerprint than the objective method. With this result in connection with the CMC curve results shows that being more conservative produces higher rank 1 and top ten rank identification scores