Sexual dimorphism and topological variability in fingerprint ridge density in a north-west Indian population.

The science of fingerprints is very crucial in criminal investigation as it helps identify perpetrators or victims of a crime. Fingerprint ridge density (FPRD), which refers to the number of ridges within a specific area on the epidermal skin layer of the distal phalanges in humans, has been found to differ between males and females. This study attempts to estimate the sex from FPRD and evaluates the diversity in FPRD across several topological areas. The study involves 208 participants (120 males, 88 females) between the ages 18 to 25 years from a North-west Indian population. Fingerprints were collected, and FPRD was accessed in radial, ulnar, and proximal areas as recommended by Gutierrez-Redomero et al. (Forensic Sci Int 180(1):17-22, 2008). FPRD has been quantified using the techniques described by Acree (Forensic Sci Int 102(1):35-44, 1999). When evaluating FPRD in the lateral pocket loops and twin loops, the proximal-side core was considered. The study reveals that males have a mean fingerprint ridge density of 12.82 ridges/25 mm2 while females have 13.01 ridges/25 mm2. Females have higher fingerprint ridge density solely in the proximal area; males have higher fingerprint ridge density in both radial and ulnar areas. In conclusion, this research underscores the potential of fingerprint ridge density as a parameter for investigating population variations and individual identification. Future studies on fingerprint ridge density in India's diverse population will help establish reference ranges, allowing for sex and likely population group estimation, making it a valuable tool for preliminary examinations and exclusion criteria for sex estimation in crime scene investigations.

Hierarchical Perceptual Noise Injection for Social Media Fingerprint Privacy Protection.

Billions of people share images from their daily lives on social media every day. However, their biometric information (e.g., fingerprints) could be easily stolen from these images. The threat of fingerprint leakage from social media has created a strong desire to anonymize shared images while maintaining image quality, since fingerprints act as a lifelong individual biometric password. To guard the fingerprint leakage, adversarial attack that involves adding imperceptible perturbations to fingerprint images have emerged as a feasible solution. However, existing works of this kind are either weak in black-box transferability or cause the images to have an unnatural appearance. Motivated by the visual perception hierarchy (i.e., high-level perception exploits model-shared semantics that transfer well across models while low-level perception extracts primitive stimuli that result in high visual sensitivity when a suspicious stimulus is provided), we propose FingerSafe, a hierarchical perceptual protective noise injection framework to address the above mentioned problems. For black-box transferability, we inject protective noises into the fingerprint orientation field to perturb the model-shared high-level semantics (i.e., fingerprint ridges). Considering visual naturalness, we suppress the low-level local contrast stimulus by regularizing the response of the Lateral Geniculate Nucleus. Our proposed FingerSafe is the first to provide feasible fingerprint protection in both digital (up to 94.12%) and realistic scenarios (Twitter and Facebook, up to 68.75%). Our code can be found at https://github.com/nlsde-safety-team/FingerSafe.

The effect of fingerprint expertise on visual short-term memory.

Expert fingerprint examiners demonstrate impressive feats of memory that may support their accuracy when making high-stakes identification decisions. Understanding the interplay between expertise and memory is therefore critical. Across two experiments, we tested fingerprint examiners and novices on their visual short-term memory for fingerprints. In Experiment 1, experts showed substantially higher memory performance compared to novices for fingerprints from their domain of expertise. In Experiment 2, we manipulated print distinctiveness and found that while both groups benefited from distinctive prints, experts still outperformed novices. This indicates that beyond stimulus qualities, expertise itself enhances short-term memory, likely through more effective organisational processing and sensitivity to meaningful patterns. Taken together, these findings shed light on the cognitive mechanisms that may explain fingerprint examiners' superior memory performance within their domain of expertise. They further suggest that training to improve memory for diverse fingerprints could practically boost examiner performance. Given the high-stakes nature of forensic identification, characterising psychological processes like memory that potentially contribute to examiner accuracy has important theoretical and practical implications.

Study of the fingerprints of a Spanish sample for the determination of the hand and finger.

The individuality and permanence of fingerprints make of them a very useful feature in the identification of individuals. There are now automated computer programmes that allow a quick comparison between a fingermark and a database. However, in order to assess the strength of evidence in fingerprint identification, complementary information on the frequencies of the different morphological features of the dermopapillary ridges is required. This idea is used in this work as a starting point to evaluate the frequencies of the parameters used in the determination of the hand and finger in a large sample of 2600 fingerprints taken from 134 male and 127 female Spanish population. Based on these fingerprints, the frequencies of different categories of the following parameters were obtained: type of pattern, slope of the apex ridge, subtype of two-delta pattern, ridge tracing, major angle, major ridge count, bisector, rotation of the central ridge, assimilation to loops and slant. Moreover, the results have shown that these characters are useful for the determination of the hand in whorls (two-delta pattern) and loops (one-delta pattern), but not for the determination of the finger. The most useful and classificatory parameter when determining the hand of origin of a two-delta fingerprint is the slope of the apex ridge, and for the one-delta pattern, knowing the location of the delta allows the correct estimation of the hand of a fingerprint in more than 93% of the cases. The data presented in this paper are novel and can be used by latent print examiners to improve the statistical basis of their decisions in reaching conclusions.

Toward multidimensional information: A derivatization-free UHPLC-QqQ MS/MS method for amino acid components of fingerprint.

The analysis of fingerprint chemical composition is a meaningful way to excavate the multidimensional information of fingerprint, including the donor profiling information and the age of a fingerprint, which broadens the evidential values of fingerprint, especially for the partial and distorted fingerprint. But the research remains still in the pilot phases or is ongoing. Amino acids are the dominant organic substances in latent sweat fingerprint and influenced by many donor factors. Hence, their content reflects personal information of donors. Forensic science will be revolutionized if suspects can be individualized by their amino acid content. The diverse nature, distinct physicochemical properties, and ultra-micro levels of amino acids present in fingerprints make it hard to detect. A high sensitivity method for detecting and quantifying multiple amino acid components is required. UHPLC-QqQ MS/MS offers high sensitivity, high separation, simultaneous multicomponents detection, and no derivatization, making it an ideal method for detecting and analyzing amino acids in fingerprints. Therefore, in this study, we propose and validate an efficient UHPLC-QqQ MS/MS method for the extraction and analysis of 13 amino acids from fingerprint. We compared the results of amino acids of 10 different substrates and found that the inherent amino acids in most porous substrates would have been extracted along with the fingerprint amino acids, making them unsuitable for quantitative amino acid analysis. Instead, plastic sheets are ideal substrates for laboratory studies. Then, extensive experiments were conducted among 30 donors for multidimensional information analysis. The type of samples analyzed were eccrine-rich fingerprints. A Binary Logistic Regression (BLR) model was developed, and the female and male donors were successfully differentiated by amino acids in fingerprints. Two other mathematical models were also developed to verify the accuracy, and all three different mathematical models were able to identify donors of different genders with over 90% accuracy. This demonstrates that amino acids have the potential to provide more information for donors as metabolic markers. In the future, we will conduct a series of experiments to analyze more multidimensional information for individual identification by amino acid content in the fingerprint.

Harnessing fluorescent carbon quantum dots from natural resource for advancing sweat latent fingerprint recognition with machine learning algorithms for enhanced human identification.

Nowadays, it is fascinating to engineer waste biomass into functional valuable nanomaterials. We investigate the production of hetero-atom doped carbon quantum dots (N-S@MCDs) to address the adaptability constraint in green precursors concerning the contents of the green precursors i.e., Tagetes erecta (marigold extract). The successful formation of N-S@MCDs as described has been validated by distinct analytical characterizations. As synthesized N-S@MCDs successfully incorporated on corn-starch powder, providing a nano-carbogenic fingerprint powder composition (N-S@MCDs/corn-starch phosphors). N-S@MCDs imparts astounding color-tunability which enables highly fluorescent fingerprint pattern developed on different non-porous surfaces along with immediate visual enhancement under UV-light, revealing a bright sharp fingerprint, along with long-time preservation of developed fingerprints. The creation and comparison of latent fingerprints (LFPs) are two key research in the recognition and detection of LFPs, respectively. In this work, developed fingerprints are regulated with an artificial intelligence program. The optimum sample has a very high degree of similarity with the standard control, as shown by the program's good matching score (86.94%) for the optimal sample. Hence, our results far outperform the benchmark attained using the conventional method, making the N-S@MCDs/corn-starch phosphors and the digital processing program suitable for use in real-world scenarios.

Technical note: A preliminary assessment of UV-C imaging using the Full Spectrum Imaging System (FSIS-II) for the detection of latent fingermarks.

The Full Spectrum Imaging System (FSIS-II) was assessed for the detection of latent fingermarks on a variety of substrates, specifically focusing on UV-C imaging for untreated marks and those that have been treated with cyanoacrylate (CA). The use of UV-C was effective at the detection of latent fingermarks on a variety of substrates and UV-C imaging may be effective when UV-A does not provide any fingermark detections on thermal paper. A Phase 2 and a small Phase 3 trials on aluminium cans were carried out with a detection sequence of UV-C imaging, CA fuming, UV-C imaging, UV-A imaging and BY40. For Phase 2 laboratory trials, the use of initial UV-C reflection was effective at removing the background and was a useful tool for initial screening. The use of UV-C was superior to UV-A after CA fuming and provided the highest overall number of high-quality marks. For phase 3 trials, the results showed that BY40 fluorescence was marginally more effective than UV-C imaging of CA-treated marks. This preliminary study shows that the FSIS-II and UV-C imaging can complement other methods for the detection of latent fingermarks.

Fingerprint Recognition in Forensic Scenarios.

Fingerprints are unique patterns used as biometric keys because they allow an individual to be unambiguously identified, making their application in the forensic field a common practice. The design of a system that can match the details of different images is still an open problem, especially when applied to large databases or, to real-time applications in forensic scenarios using mobile devices. Fingerprints collected at a crime scene are often manually processed to find those that are relevant to solving the crime. This work proposes an efficient methodology that can be applied in real time to reduce the manual work in crime scene investigations that consumes time and human resources. The proposed methodology includes four steps: (i) image pre-processing using oriented Gabor filters; (ii) the extraction of minutiae using a variant of the Crossing Numbers method which include a novel ROI definition through convex hull and erosion followed by replacing two or more very close minutiae with an average minutiae; (iii) the creation of a model that represents each minutia through the characteristics of a set of polygons including neighboring minutiae; (iv) the individual search of a match for each minutia in different images using metrics on the absolute and relative errors. While in the literature most methodologies look to validate the entire fingerprint model, connecting the minutiae or using minutiae triplets, we validate each minutia individually using n-vertex polygons whose vertices are neighbor minutiae that surround the reference. Our method also reveals robustness against false minutiae since several polygons are used to represent the same minutia, there is a possibility that even if there are false minutia, the true polygon is present and identified; in addition, our method is immune to rotations and translations. The results show that the proposed methodology can be applied in real time in standard hardware implementation, with images of arbitrary orientations.

Unveiling intra-person fingerprint similarity via deep contrastive learning.

Fingerprint biometrics are integral to digital authentication and forensic science. However, they are based on the unproven assumption that no two fingerprints, even from different fingers of the same person, are alike. This renders them useless in scenarios where the presented fingerprints are from different fingers than those on record. Contrary to this prevailing assumption, we show above 99.99% confidence that fingerprints from different fingers of the same person share very strong similarities. Using deep twin neural networks to extract fingerprint representation vectors, we find that these similarities hold across all pairs of fingers within the same person, even when controlling for spurious factors like sensor modality. We also find evidence that ridge orientation, especially near the fingerprint center, explains a substantial part of this similarity, whereas minutiae used in traditional methods are almost nonpredictive. Our experiments suggest that, in some situations, this relationship can increase forensic investigation efficiency by almost two orders of magnitude.

Measuring the rarity of core-delta distances in fingerprint patterns in the Dutch population.

In latent print examination, a conclusion on an individualization is primarily based on the presence of corresponding minutiae. Depending on the level of correspondence between the minutiae on the fingermark and on the reference print, a match is concluded. However, a fingermark is analyzed on all three levels: general pattern combined with core-delta distance, minutiae, and third-level detail. In the opinion of the authors, next to the conclusion based on minutiae, all information should be included in the final assessment of the evidence if present. In this study, we present the results of frequency data on the combination of fingerprint patterns and their core-delta distances. The frequency data allow examiners to substantiate their subjective opinions on the strength of corresponding patterns and core-delta distances based on measurements. The frequencies of the core-delta distances in this study were obtained by encoding core-delta distances in a collection of more than 20,000 fingerprints containing either a loop or a whorl pattern. The frequencies for the core-delta distances of loop patterns were subsequently compared with data from the National Institute of Standards and Technology. This study will demonstrate that core-delta distances in loop and whorl patterns contribute significantly to the overall evidential strength of fingerprint evidence. By adding pattern and core-delta distance information to the evaluation of fingerprint evidence, more challenging fingermarks could be added to fingerprint case reports.

Reliability of ordinal outcomes in forensic black-box studies.

Forensic science disciplines such as latent print examination, bullet and cartridge case comparisons, and shoeprint analysis, involve subjective decisions by forensic experts throughout the examination process. Most of the decisions involve ordinal categories. Examples include a three-category outcome for latent print comparisons (exclusion, inconclusive, identification) and a seven-category outcome for footwear comparisons (exclusion, indications of non-association, inconclusive, limited association of class characteristics, association of class characteristics, high degree of association, identification). As the results of the forensic examinations of evidence can heavily influence the outcomes of court proceedings, it is important to assess the reliability and accuracy of the underlying decisions. "Black box" studies are the most common approach for assessing the reliability and accuracy of subjective decisions. In these studies, researchers produce evidence samples consisting of a sample of questioned source and a sample of known source where the ground truth (same source or different source) is known. Examiners provide assessments for selected samples using the same approach they would use in actual casework. These studies often have two phases; the first phase comprises of decisions on samples of varying complexities by different examiners, and the second phase involves repeated decisions by the same examiner on a (usually) small subset of samples that were encountered by examiners in the first phase. We provide a statistical method to analyze ordinal decisions from black-box trials with the objective of obtaining inferences for the reliability of these decisions and quantifying the variation in decisions attributable to the examiners, the samples, and statistical interaction effects between examiners and samples. We present simulation studies to judge the performance of the model on data with known parameter values and apply the model to data from a handwritten signature complexity study, a latent fingerprint examination black-box study, and a handwriting comparisons black-box study.

Development, detection and decipherment of obfuscated fingerprints in humans: Implications for forensic casework.

Fingerprints have been widely used and accepted as an effective method of human identification. This biometric tool aids in criminal investigations for personal identity for over a century. Whilst the Automatic Fingerprint Identification System (AFIS) has bolstered security efforts, it has also opened doors to potential scams, affecting both civilian and law enforcement operations. Despite extensive research on fingerprint authentication issues, very little attention has been given to addressing the problem of fingerprint alteration or obfuscation. Fraudsters, with the guidance of experts, have developed new techniques to obscure their fingerprints intentionally. Fingerprint obfuscation is the deliberate alteration of fingerprint patterns with the aim of concealing their true identity, raising concerns amongst security and investigative organizations. The objective of the current communication is to highlight the numerous techniques used for obfuscation, forgery and alteration of fingerprints in humans. It further accentuates the need for identification and interpretation of these altered fingerprints and recommends notifying law enforcement agencies of potential threats.

Dermatoglyphic Profiles of Competitive Athletes: CrossFit and Ultra-Marathon / Perfiles Dermatoglíficos de Deportistas Competitivos: CrossFit y Ultramaratón

SUMMARY: In the sports field, sports are usually classified according to the predominance of the energy system used during the competition; sports like Crossfit and ultra-marathon could be totally opposite due to the needs of athletes to achieve good places. Due to the above, the objective was established to compare the dermatoglyphic profiles of CrossFit and Ultra-marathon athletes according to the predisposition of the energy systems, aerobic and anaerobic, used in the competitions. Cross-sectional descriptive study, where the dermatoglyphic profile of 21 athletes of national presence (10 crossfit and 11 ultra-marathon runners) was determined, through the Computerized Dermatoglyphic System, brand Salus Dermatoglifia, according to the Cummins and Midlo protocol, which consists of taking the fingerprints of the 10 fingers of the hands. The fingerprint designs of the human being (arch, loop and whorl) and the elements contained in them (nucleus and delta) were analyzed, differences were established through the Analysis of Variance test in the SPSS V.25 statistical package. The results show significant differences between the average scores of the line count of both disciplines (108 and 165), being higher in ultra-marathon runners, associated with greater aerobic resistance. Another significant and relevant finding was the presence of arch-type fingerprints only in CrossFit athletes associated, along with low line count, with strength and power. It is concluded that Crossfit and Ultra-marathon athletes have dissimilar natural physical characteristics, which is why they participate and excel in different sports where they have enhanced their natural physical abilities through training.

En el ámbito deportivo, los deportes suelen clasificarse según el predominio del sistema energético utilizado durante la competición; Deportes como el Crossfit y la ultramaratón podrían ser totalmente opuestos debido a las necesidades de los deportistas de conseguir buenos lugares. Debido a lo anterior, se estableció como objetivo comparar los perfiles dermatoglíficos de atletas de CrossFit y Ultramaratón según la predisposición de los sistemas energéticos, aeróbico y anaeróbico, utilizados en las competencias. Estudio descriptivo transversal, donde se determinó el perfil dermatoglífico de 21 deportistas de presencia nacional (10 crossfit y 11 ultramaratonistas), a través del Sistema Dermatoglífico Computarizado, marca Salus Dermatoglifia, según el protocolo Cummins y Midlo, el cual consta de tomando las huellas dactilares de los 10 dedos de las manos. Se analizaron los diseños dactilares del ser humano (arco, asa y verticilo) y los elementos contenidos en ellos (núcleo y delta), se establecieron diferencias mediante la prueba de Análisis de Varianza en el paquete estadístico SPSS V.25. Los resultados muestran diferencias significativas entre las puntuaciones medias del recuento de líneas de ambas disciplinas (108 y 165), siendo superiores en los corredores de ultramaratón, asociado a una mayor resistencia aeróbica. Otro hallazgo significativo y relevante fue la presencia de huellas dactilares tipo arco sólo en atletas de CrossFit asociadas, junto con un bajo número de líneas, con fuerza y potencia. Se concluye que los atletas de Crossfit y Ultramaratón tienen características físicas naturales disímiles, por lo que participan y destacan en diferentes deportes donde han potenciado sus capacidades físicas naturales a través del entrenamiento.

Multi-region minutiae depth value-based efficient forged finger print analysis.

The application of biometrics has expanded the wings to many domains of application. However, various biometric features are being used in different security systems; the fingerprints have their own merits as it is more distinct. A different algorithm has been discussed earlier to improve the security and analysis of fingerprints to find forged ones, but it has a deficiency in expected performance. A multi-region minutiae depth value (MRMDV) based finger analysis algorithm has been presented to solve this issue. The image that is considered as input has been can be converted into noisy free with the help of median and Gabor filters. Further, the quality of the image is improved by sharpening the image. Second, the preprocessed image has been divided into many tiny images representing various regions. From the regional images, the features of ridge ends, ridge bifurcation, ridge enclosure, ridge dot, and ridge island. The multi-region minutiae depth value (MRMDV) has been computed based on the features which are extracted. The test image which has a similarity to the test image is estimated around MRMDV value towards forgery detection. The MRMDV approach produced noticeable results on forged fingerprint detection accuracy up to 98% with the least time complexity of 12 seconds.

The laboratory perspective: Confirming the integrity of fingermark enhancement reagents.

Validation is particularly important in forensic science. Each process utilised by a forensic laboratory will undergo validation to ensure it is functioning as expected. Some pieces of equipment (hardware) will be simple to validate, and this will be conducted regularly. However, many commonly employed fingermark enhancement reagents, such as ninhydrin and 1,2-Indandione, do not have clearly defined and robust validation parameters. To that end, artificial fingermark solutions, particularly amino acid solutions, have previously been investigated as a controlled validation method, via deposition onto a substrate. Whilst amino acid reagents are important, there is also a wider group of latent fingermark constituents (targets) that require the use of other enhancement reagents within the forensic laboratory. The work presented herein seeks to expand on the concept of amino acid printing, by exploring the possibilities of depositing a sebaceous solution matrix, thereby facilitating the testing of reagents such as Oil-Red-O and Physical Developer. In addition, we present a method that extends capabilities beyond fingermark enhancement reagents for porous substrates, by developing a methodology that enables process validation of the cyanoacrylate fuming technique to be easily facilitated. These simple and effective solutions have the capacity to serve as a crucial process validation check within the laboratory validation workflow.

Shifting decision thresholds can undermine the probative value and legal utility of forensic pattern-matching evidence.

Forensic pattern analysis requires examiners to compare the patterns of items such as fingerprints or tool marks to assess whether they have a common source. This article uses signal detection theory to model examiners' reported conclusions (e.g., identification, inconclusive, or exclusion), focusing on the connection between the examiner's decision threshold and the probative value of the forensic evidence. It uses a Bayesian network model to explore how shifts in decision thresholds may affect rates and ratios of true and false convictions in a hypothetical legal system. It demonstrates that small shifts in decision thresholds, which may arise from contextual bias, can dramatically affect the value of forensic pattern-matching evidence and its utility in the legal system.

Multifunctional Eu(III)-modified HOFs: roxarsone and aristolochic acid carcinogen monitoring and latent fingerprint identification based on artificial intelligence.

The exploration of multifunctional materials and intelligent technologies used for fluorescence sensing and latent fingerprint (LFP) identification is a research hotspot of material science. In this study, an emerging crystalline luminescent material, Eu3+-functionalized hydrogen-bonded organic framework (Eu@HOF-BTB, Eu@1), is fabricated successfully. Eu@1 can emit purple red fluorescence with a high photoluminescence quantum yield of 36.82%. Combined with artificial intelligence (AI) algorithms including support vector machine, principal component analysis, and hierarchical clustering analysis, Eu@1 as a sensor can concurrently distinguish two carcinogens, roxarsone and aristolochic acid, based on different mechanisms. The sensing process exhibits high selectivity, high efficiency, and excellent anti-interference. Meanwhile, Eu@1 is also an excellent eikonogen for LFP identification with high-resolution and high-contrast. Based on an automatic fingerprint identification system, the simultaneous differentiation of two fingerprint images is achieved. Moreover, a simulation experiment of criminal arrest is conducted. By virtue of the Alexnet-based fingerprint analysis platform of AI, unknown LFPs can be compared with a database to identify the criminal within one second with over 90% recognition accuracy. With AI technology, HOFs are applied for the first time in the LFP identification field, which provides a new material and solution for investigators to track criminal clues and handle cases efficiently.

Estudio Piloto Comparativo entre la Identificación Dactiloscópica y Poroscópica con Fines de Identificación Humana en el Perú / Comparative Pilot Study Between Dactyloscopy Identification and Poroscopy for Human Identification Purposes in Peru

La dactiloscopía o papiloscopía corresponde al estudio científico de las impresiones digitales, palmares y plantares, que tiene por finalidad la identificación infalible o indubitada del individuo. Existen tres niveles para identificar con mayor certeza nivel 1 (tipo o patrón dactilar), el nivel 2 (minucias o puntos característicos) y el nivel 3 (poroscopia y crestoscopia). Por ello, es necesario analizar las características de las impresiones dactilares directas y las huellas dactilares directas con la finalidad de verificar la presencia de puntos y poros característicos para mejorar el proceso de identificación humana. Se analizaron 80 muestras (54 mujeres y 26 hom- bres). A partir de ellos, se capturaron 800 impresiones y 800 huellas dactilares directas con tampón dactilar y polvo black. En huellas con tampón se identificaron 71.25 % y 1.25 % con 14 y 6 Puntos Característicos respectivamente y en grupos de poros el 84 % y 35 % para un grupo de 1 y grupos de 7 y 8 poros respectivamente. Con polvo black solo se identificaron Puntos Característico y no Poros. La cantidad de poros en hombres fue mayor igual a 10 (LR= 2.08) y en mujeres menor igual a 6 (LR= 1.93). Los grupos de poros fueron para hombres menores o iguales a 12 poros (LR= 1.04) y mayores o iguales a grupos de 13 poros (LR=1.28) para mujeres. Se consiguieron identificar grupos de poros con tampón dactilar pero no con polvos químicos lo que podría emplearse para implementar un protocolo para el uso del nivel 3 de identificación.

SUMMARY: Dactyloscopy or papiloscopy corresponds to the scientific study of digital, palmar and plantar impressions, whose purpose is the infallible or indubitable identification of a subject. There are three levels to identify with greater certainty level 1 (type or fingerprint pattern), level 2 (minutiae or characteristic points) and level 3 (poroscopy and crestoscopy). Therefore, it is necessary to analyze the characteristics of direct fingerprints and direct fingerprints in order to verify the presence of characteristic points and pores to improve the human identification process. 80 samples (54 women and 26 men) were analyzed. Of these, 800 impressions and 800 direct fingerprints with fingerprint buffer and black powder were captured. In footprints with buffer, 71.25 % and 1.25 % were identified with 14 and 6 Characteristic Points respectively and in groups of pores 84 % and 35 % for a group of 1 and groups of 7 and 8 pores respectively. With black powder, only Characteristic Points and no Pores were identified. The number of pores in men was greater than 10 (LR= 2.08) and in women less than 6 (LR= 1.93). The groups of pores were less than or equal to 12 pores (LR= 1.04) for men and greater than or equal to groups of 13 pores (LR=1.28) for women. It was possible to identify groups of pores with a fingerprint buffer but not with chemical powders, which could be used to implement a protocol for the use of level 3 identification.

Production of artificial fingermarks. Part II - The use of a modified inkjet printer for the deposition of synthetic secretions.

This study is the second part of a larger body of research dedicated to the production of synthetic secretions and the use of an inkjet printer to deposit realistic artificial fingermarks. An artificial emulsion combining eccrine and sebaceous compounds, which was described and tested in the first part of this research, was used as it showed a promising compatibility with common detection techniques. An inkjet printer was modified to print the emulsion on two different substrates: paper (porous) and acetate (non-porous). After optimisation of the printing parameters, multiple fingermarks were printed and processed with a range of standalone detection techniques: 1,2-indanedione-zinc, ninhydrin, Oil Red O, and physical developer on paper, and cyanoacrylate fuming, rhodamine 6G, gold/zinc vacuum metal deposition, and silver black powder on acetate. The detection techniques were also applied in sequence, which is considered one of the biggest advantages of the emulsion over simpler amino acid mixtures that are usable with amino acid reagents only. Natural fingermarks deposited by a single donor were processed with the same techniques for comparison. The effect of water immersion was also investigated, where fingermarks printed on paper were immersed in water for 15 min, before being processed with 1,2-indanedione-zinc and Oil Red O. The results showed that realistic-looking fingermarks could be printed on paper and that printing on acetate was also possible albeit of lower quality due to the nature of the substrate. The artificial fingermarks were successfully enhanced by all the detection techniques tested, at the notable exception of physical developer. The results obtained were very similar to what is generally observed with real fingermarks, and it was observed that the impact of water immersion on the artificial fingermarks was comparable as well. These findings open new perspectives for the development of multi-target quality control test strips or for the standardisation of proficiency testing and interlaboratory collaborative exercises where ground truth is crucial to guarantee comparable results and objective assessment.