An unconstrained palmprint region of interest extraction method based on lightweight networks.

Accurately extracting the Region of Interest (ROI) of a palm print was crucial for subsequent palm print recognition. However, under unconstrained environmental conditions, the user's palm posture and angle, as well as the background and lighting of the environment, were not controlled, making the extraction of the ROI of palm print a major challenge. In existing research methods, traditional ROI extraction methods relied on image segmentation and were difficult to apply to multiple datasets simultaneously under the aforementioned interference. However, deep learning-based methods typically did not consider the computational cost of the model and were difficult to apply to embedded devices. This article proposed a palm print ROI extraction method based on lightweight networks. Firstly, the YOLOv5-lite network was used to detect and preliminarily locate the palm, in order to eliminate most of the interference from complex backgrounds. Then, an improved UNet was used for keypoints detection. This network model reduced the number of parameters compared to the original UNet model, improved network performance, and accelerated network convergence. The output of this model combined Gaussian heatmap regression and direct regression and proposed a joint loss function based on JS loss and L2 loss for supervision. During the experiment, a mixed database consisting of 5 databases was used to meet the needs of practical applications. The results showed that the proposed method achieved an accuracy of 98.3% on the database, with an average detection time of only 28ms on the GPU, which was superior to other mainstream lightweight networks, and the model size was only 831k. In the open-set test, with a success rate of 93.4%, an average detection time of 5.95ms on the GPU, it was far ahead of the latest palm print ROI extraction algorithm and could be applied in practice.

Preliminary investigations into the use of the ancient pigments Han blue and Han purple as luminescent dusting powders for the detection of latent fingermarks.

Here we present our preliminary studies into the inorganic pigments Han blue (BaCuSi4O10) and Han purple (BaCuSi2O6) as near-infrared luminescent fingerprint dusting powders. These pigments were developed in ancient China around 800 BCE and both show luminescence in the NIR region. There remains, however, ambiguity in the literature concerning their photophysical properties. Samples of Han blue and Han purple artist's pigments were characterized by optical microscopy, infrared, ultraviolet-visible absorbance and luminescence spectroscopy. Their performance as fingerprint dusting powders, without any further treatment, on non-porous surfaces were compared to exfoliated lipophilic coated Egyptian blue and commercial fluorescent powders in a pilot study. These results demonstrate for the first time that both ancient pigments show promise as alternative dusting powders for latent fingermarks.

Quaternary phosphonium AIEgens nanoparticles as innovative agents for developing latent fingerprints.

Quaternary phosphonium salts, a significant category of organophosphorus compounds, have garnered substantial attention from chemists due to their wide range of applications across various research areas. These compounds are utilized in organic synthesis, catalysis, medicinal chemistry, natural materials, and coordination chemistry. Their versatility and effectiveness in these fields make them valuable tools in scientific research. Despite their extensive use in various applications, the potential of quaternary phosphonium compounds as fluorescent agents for revealing latent fingerprints (LFPs) remains largely unexplored, presenting an exciting opportunity for further research and development in forensic science. In this study, we designed molecules that combine the aggregation-induced emission (AIE) chromophore with triphenylphosphine to create a series of novel AIE amphiphiles, namely TPP1, TPP2, and TPP3. Through precise adjustment of the carbon chain length between the phenoxy group and the terminal triphenylphosphine, we were able to finely tune the nanostructures and hydrophobicity of the materials. TPP3 emerged as the optimal candidate, possessing the ideal particle size and hydrophobicity to effectively bind to LFPs, thus enabling efficient fingerprint visualization with enhanced fluorescence upon aggregation. Our findings introduce an innovative approach to fingerprint visualization, offering high selectivity, superior imaging of level 3 structures, and long-term effectiveness (up to 30 days). Additionally, TPP3's outstanding performance in imaging level 3 structures of LFPs is beneficial for analyzing incomplete LFPs and identifying individuals. By significantly improving the detection and analysis of LFPs, this approach ensures more accurate and reliable identification, making it invaluable for forensic investigations and security measures. The adaptability of these compounds to various fingerprint surfaces highlights their potential in diverse practical applications, enhancing their utility in both forensic science and security fields. This versatility allows for precise fingerprint visualization across different scenarios, making them a critical tool for advancing biometric and security technologies.

Aggregation-induced emission luminogens for latent fingerprint detection.

For over a century, fingerprints have served as a pivotal tool for identification of individuals owing to their enduring characteristics and easily apparent features, particularly in the realm of criminal investigations. Latent fingerprints (LFPs) are "invisible fingerprints" that are most commonly available at crime scenes and require a rapid, selective, sensitive, and convenient method for detection. However, existing fingerprint development techniques harbour limitations, prompting the exploration of novel approaches that prioritize investigator safety and environmental sustainability. Leveraging the unique photophysical properties of aggregation-induced emission luminogens (AIEgens) has emerged as a promising strategy for on-site analysis of LFP visualization. In this highlight, we have presented a comparative analysis of various AIEgens (organic compounds, metal complexes, nanoparticles, and polymers) for the development and detection of LFPs. Through this examination, insights into the efficiency and potential applications of AIE-based fingerprint development techniques are provided. In addition, several strategies have been proposed for circumventing the limitations of existing AIEgens. We hope that this highlight article will encourage more researchers to investigate AIEgens in LFP detection, contributing to forensic science.

Latent fingerprint imaging using irradiated novel mixed metal oxides (MXOY, M = Ba, Zn, Al, Ce) nanophosphor.

Latent fingerprint developed at the site of crime is considered as crucial physical evidence in forensic investigation. The mixed metal oxides (MXOY, M = Ba, Zn, Al, Ce) nanophosphor was synthesised by irradiating the precursor solution with 60Co gamma radiation followed by solution combustion method. The structural, morphological, optical characteristics and fingerprint imaging were studied using X-ray diffraction (XRD), scanning electron microscopy, UV-visible spectroscopy and powder dusting method, respectively. The XRD results revealed that the average crystallite size is found to be 30 nm with the estimated bandgap of 3.18 eV. The broadband UV exited luminescence of the phosphors was observed at λMax = 330 nm. The PL spectrum shows three emission bands at 432, 444 and 460 nm that corresponds to blue regions, suggesting that the synthesised nanophosphor is a potential luminous material for latent fingerprinting and luminescent devices.

Healing Function for Abraded Fingerprint Ridges in Tactile Texture Sensors.

Tactile texture sensors are designed to evaluate the sensations felt when a human touches an object. Prior studies have demonstrated the necessity for these sensors to have compliant ridges on their surfaces that mimic human fingerprints. These features enable the simulation of contact phenomena, especially friction and vibration, between human fingertips and objects, enhancing the tactile sensation evaluation. However, the ridges on tactile sensors are susceptible to abrasion damage from repeated use. To date, the healing function of abraded ridges has not been proposed, and its effectiveness needs to be demonstrated. In this study, we investigated whether the signal detection capabilities of a sensor with abraded epidermal ridges could be restored by healing the ridges using polyvinyl chloride plastisol as the sensor material. We developed a prototype tactile sensor with an embedded strain gauge, which was used to repeatedly scan roughness specimens. After more than 1000 measurements, we observed significant deterioration in the sensor's output signal level. The ridges were then reshaped using a mold with a heating function, allowing the sensor to partially regain its original signal levels. This method shows potential for extending the operational lifespan of tactile texture sensors with compliant ridges.

Using the refractive index of latent fingerprints for the quantification and characterisation of sample deposition.

Latent fingerprints (LFPs) are predominantly used for personal identification, but in recent years research has shown their potential for drug screening. Despite this there is no standardised collection method to allow accurate drug test interpretation. We sought to help address this by characterising different variables related to sweat deposition in LFPs as the knowledge is limited. A series of experiments were conducted firstly to validate a novel tool called the Ridgeway (Intelligent Fingerprint Ltd. UK) to quantify the amount of sweat deposited from a LFP using the refractive index (RI). A significant positive correlation was observed between the Ridgeway score (Rs) and LFP mass [r = 0.868, p < 0.01]. The Rs was used as means to investigate optimal sampling to characterise sample deposition for drug screening purposes. It was found with a consistent disposition pressure (300 - 400 g) and surface (glass slide) no significant difference was observed between the left and right index finger [left: p = 0.938; right: p = 0.838]. Significantly higher Rs [p<0.01] were obtained when 10 cumulative LFPs were deposited compared to a single LFP, suggesting a larger sweat quantity. We also wanted to investigate optimal eccrine sweat sampling to confirm drug ingestion over drug contamination of the fingerprint. We found that wearing gloves did not significantly improve mean difference in Rs when compared to no gloves [p = 0.239]. To produce eccrine only LFPs, external contamination (e.g. sebaceous sweat) needs to be removed. Soap with lint free tissue was significantly better for this compared to antibacterial hand gel [p<0.01]. Our findings showed that the Ridgeway tool effectively quantified LFPs at the point of deposition using a refractive index and enabled us to establish conditions for consistent LFP sampling.

How often do fingerprint examiners disagree in routine casework?

During routine casework, fingerprint examiners are required to make decisions pertaining to the sufficiency of friction ridge skin impressions. Prior experimental research has established that differences of opinion between examiners are expected, though it is uncertain if these findings are representative of the decisions made during casework. In this study, 5000 job-cards completed by fingerprint experts of the NSW Police Force were scrutinised to track the differences of opinion that occurred between examiners. Experts recorded 19,491 casework decisions, which resulted in 8964 reported identification and inconclusive determinations. Expert decision making was found to be unanimous in 94.8 % of these determinations; 4.6 % involved one expert-to-expert disagreement; and 0.5 % involved two expert-to-expert disagreements. Nil determinations featured more than two expert-to-expert disagreements. Expert-to-expert disagreements occurred in 3.7 % of all identification and inconclusive casework verification decisions. However, verifying experts were more likely to agree with a prior expert's identification decision, than a prior expert's inconclusive decision. The observed expert-to-expert identification disagreement rate was 2.0 %, whereas the observed expert-to-expert inconclusive disagreement rate was 12.5 %. Overall, most casework disagreements arose due to subjective differences concerning the suitability of friction ridge skin information for comparison or sufficiency for identification. Experts were more concordant in their decision-making with other experts than with trainees, and approximately three times more likely to disagree with a prior trainees' identification or inconclusive decision than a prior experts' identification or inconclusive decision. We assume these differences reflect trainees' developing proficiencies in assessing the suitability or sufficiency of friction ridge skin impression information. Differences of opinion in casework are expected, which exposes the subjective nature of fingerprint decision-making. Computer-based quality metric and likelihood ratio tools should be considered for use in casework to guide examiner evaluations and mitigate examiner disagreements.

Instant in situ highlighting of latent fingerprints by a green fluorescent probe based on aggregation-induced emission.

Fluorescence sensing of latent fingerprints (LFPs) has gained extensive attention due to its high sensitivity, non-destructive testing, low biotoxicity, ease of operation, and the potential for in situ visualization. However, the realization of in situ visualization of LFPs especially with green emission and rapid speed is still a challenge. Herein, we synthesized an amphibious green-emission AIE-gen TPE-NI-AOH (PLQY = 62%) for instant in situ LFP detecting, which integrates the excellent fluorescence properties of naphthalimide (NI) with a hydrophilic head and the AIE character as well as the donating property of tetraphenylethene (TPE). TPE-NI-AOH in ethanol/water binary solvent was used as an environmentally friendly LFP developer and achieved in situ green-fluorescence visualization of LFPs. The fluorescence signal achieves its 60% saturated intensity in 0.37 s and nearly 100% in 2.50 s, which is an instant process for the naked eye. Moreover, level 3 details and super-resolution images of LFPs could be observed clearly. Besides, the TPE-NI-AOH developer could be stored for at least 6 months, suitable for long-term storage. This instant in situ highlighting method does not require post-processing operations, providing a more convenient, rapid, and efficient detection method of LFPs. This work would inspire the further advancement of fluorescent sensors for fingerprint imaging.

Fingermark quality: A survey of examiners and researchers.

The primary aim of fingermark research is to advance the quantity and quality of fingermarks detected using novel techniques or improvements on existing methods. Subsequently, there is a need to evaluate these methods to determine the quality of the developed mark, which is mostly done by the use of a numerical scale with descriptors to assist in the evaluation. However, this evaluation is often complicated due to a wide range of variables that impact the way quality assessment is performed. This is particularly true when considering it is currently unknown what assessment parameters are required to encompass the overall definition of quality. Likewise, the definition of fingermark quality is not universally agreed upon, which leads to significant subjective interpretation when a researcher chooses a scale. The purpose of this study was to investigate the factors contributing to fingermark quality in order to generate a deeper understanding of current approaches and definitions. A survey was created through a dataset that consisted of over 500 fingermarks detected in controlled laboratory conditions with a range of techniques. The images selected for the survey were based upon representing a full range of quality, each with a varying range of attributes. The survey looked at different parameters and descriptions used in current assessment protocols, asked participants to grade marks based on chosen parameters, and investigated current chosen methods by researchers in fingermark definition. The survey relied upon the participation of both examiners and researchers in fingermark detection. The results indicate that quality assessment methods implemented by researchers are not utilising all parameters that fingermark researchers and examiners deem important. This is especially true for contrast and background development, considered as two of the top parameters by examiners and researchers, which are not regularly used in most quality scale assessment methods. The survey ultimately demonstrated that the current subjective quality assessment methods were not always suitable and highlighted more appropriate parameters and descriptors that should be considered when assessing the quality of a fingermark.

Complete Region of Interest for Unconstrained Palmprint Recognition.

Unconstrained palmprint images have shown great potential for recognition applications due to their lower restrictions regarding hand poses and backgrounds during contactless image acquisition. However, they face two challenges: 1) unclear palm contours and finger-valley points of unconstrained palmprint images make it difficult to locate landmarks to crop the palmprint region of interest (ROI); and 2) large intra-class diversities of unconstrained palmprint images hinder the learning of intra-class-invariant palmprint features. In this paper, we propose to directly extract the complete palmprint region as the ROI (CROI) using the detection-style CenterNet without requiring the detection of any landmarks, and large intra-class diversities may occur. To address this, we further propose a palmprint feature alignment and learning hybrid network (PalmALNet) for unconstrained palmprint recognition. Specifically, we first exploit and align the multi-scale shallow representation of unconstrained palmprint images via deformable convolution and alignment-aware supervision, such that the pixel gaps of the intra-class palmprint CROIs can be minimized in shallow feature space. Then, we develop multiple triple-attention learning modules by integrating spatial, channel, and self-attention operations into convolution to adaptively learn and highlight the latent identity-invariant palmprint information, enhancing the overall discriminative power of the palmprint features. Extensive experimental results on four challenging palmprint databases demonstrate the promising effectiveness of both the proposed PalmALNet and CROI for unconstrained palmprint recognition.

Analysis of palmprints and soleprints of black-tufted marmosets (Callithrix penicillata): are there similarities to humans?

Friction ridges are important and unique biometric features that have been studied in fingerprint science since antiquity and used for human identification. This study aimed to analyze palmprints and soleprints of Callithrix penicillata, including the description of flexion creases, regions, minutiae classification, and delta counting, in order to evaluate the uniqueness of these data and feasibility of using this information as an identification method. Palmprints and footprints were collected using commercial fingerprint ink on A4 size paper. Following image digitalization using the GIMP (2.10.14) image editing program, regions and flexion creases were identified. A total of 600 minutiae were classified in females (288 palms and 312 soles) and 732 in males (360 palms and 372 soles), and all deltas were counted. It was possible to identify three main inconstant flexion creases, in both palmprints and soleprints, with different distribution and orientation when compared to those in humans. Less variety in the types of minutiae and differences in the distribution of deltas were found when compared to human studies. In addition, the hypothesis of non-coincident characteristics in each sample was confirmed.

Use of automated quality assessment algorithms in fingermark detection research - Application to IND/Zn vs DFO.

When developing detection techniques for fingermarks, the detected fingermarks must be evaluated for their quality to assess the effectiveness of the new method. It is a common practice to compare the performance of the new (optimized) technique with the traditional or well-established ones. In current practice, this evaluation step is carried out by a group of human assessors. A new approach is applied in this paper and consists of using algorithms to perform this task. To implement this approach, the comparison between IND/Zn and DFO has been chosen because it has already been the subject of many articles published in recent years and a consensus exists on the superiority of IND/Zn over DFO. The quality of 3'600 fingermarks developed using both detection techniques was assessed automatically using two algorithms: LQM (Latent Quality Metric) and ILFQM (Improved Latent Fingerprint Quality Metric). The distribution of quality scores was studied for both detection techniques. The results showed that fingermarks detected with IND/Zn received higher scores on average than fingermarks detected with DFO, which is in line with the consensus in the literature based on human assessment. The results of this research are promising and shows that automated fingermark quality assessment is an efficient and viable way to comparatively assess fingermark detection techniques.

Hydrochromic and piezochromic dual-responsive optical film derived from poloxamer and ethyl cellulose for visual fingerprints identification.

Developing new materials that could identify fingerprint using the naked eye and observe the level 3 microscopic details is challenging. Here, we designed a novel hydrochromic and piezochromic dual-responsive optical film, which achieved the visual transparency transition. The performances of hydrochromic and piezochromic responses from high transparency to opaque whiteness were attributed to the introduction of poloxamer. The hygroscopic swelling of the disordered micelles led to light scattering, causing the hydrochromic response. The piezochromic response may be ascribed to the microcracks in the fragments of poloxamer crystals, which changed the refractive index of light. The fascinating combination of hydrochromic and piezochromic response was effectively applied in fingerprint identification. Hydrochromic response accurately recognized sweat pores, and piezochromic response could gradually reveal the ridges and valleys according to the different color of imprinted fingerprints. The film could identify fake fingerprints based on the differences in sweat pores between fake fingerprints and living fingers. More importantly, the film could easily detected not only the clear ridges but also the detailed sweat pores using the naked eye, indicating that the film has profound research significance in fingerprint analysis and liveness fingerprint detection.

The effect of following best practice reporting recommendations on legal and community evaluations of forensic examiners reports.

Commentators have recommended that forensic scientists' reports contain various disclosures to facilitate comprehension. However, little research has explored whether following best practice recommendations for disclosure impacts on receivers' impressions of the evidence. We examined whether forensic science reports that are more compliant with these best practice recommendations reduced overvaluing of the evidence and sensitized legal and community decision-makers to evidence quality. Across three experiments, 240 legal practitioners/trainees and 566 community decision-makers were presented with a fingerprint or footwear report that was either compliant or non-compliant with best practice recommendations. Participants were then asked to make evaluations and decisions based on the report. We found mixed effects of report compliance. Report compliance affected community participant's evaluations of the persuasiveness of the evidence but had limited impact on the judgments of legal practitioners/trainees. When presented with compliant reports, we found that community participants regarded unknown reliability evidence as less reliable and less persuasive than high reliability evidence, suggesting disclosures helped reduce overvaluing of the evidence and create sensitivity to differences in evidence quality. These results suggest compliance with reporting recommendations does affect community impressions, while only minimally influencing legal impressions of forensic science evidence. The costs and/or benefits of this outcome require further examination.

Showcasing water-based delivery of an amino acid targeting fingermark developer in a hydrogel.

Most recommended methods for visualising fingermarks on paper rely on chemical developers that target and react with amino acids. Traditionally, these developers are sprayed onto paper substrates in solutions of per- and polyfluoroalkyl substances (PFAS), but now those same PFAS chemicals are undergoing phaseout or phasedown, which threatens to undermine forensic capabilities. This situation provides an opportunity to pivot towards greener approaches to fingermark visualisation. The ideal methodology would be a water-based treatment, as these provide superior safety for practitioners, combined with environmental sustainability. A major hurdle to implementing a water-based fingermark developer targeting amino acids is that water, as a universal solvent, can dissolve the eccrine components in fingermarks, as well as any optical or luminescent dyes that are created, causing the ridge detail to run or dissolve. This work circumvents this problem by delivering the amino acid developer alloxan in a hydrogel, which enables sharp fingermark ridge details to be observed despite it being a water-based treatment. Alloxan dissolved in a viscous hydrogel is shown here to react with the amino acids in fingerprint residues to form the coloured dye murexide, supported by optimisation and characterisation studies.

Wet SPF: A wet powder suspension for the detection of latent fingermarks on the sticky side of adhesive tape for use in Seychelles.

WET UCIO is an inexpensive carbon-based powder suspension, reportedly as effective as commercially available formulations for latent fingermark detection on the sticky side of adhesive tapes. However, the surfactant solution used in WET UCIO is not readily accessible outside Europe, limiting its use in Seychelles or other non-European jurisdictions. In this study, the UCIO formulation was modified based on a 'frugal forensic' approach, by replacing the surfactant solution with an in-house sodium dodecyl sulfate solution prepared in 5 % aqueous ethanol. A comparative assessment against Wetwop™ using eight different pressure-sensitive adhesive tapes found that the modified formulation was at least as effective as commercial powder suspension. Modifying this technique under the frugal forensic framework has enhanced its accessibility to other jurisdictions and is recommended for validation in Seychelles.

The effects and benefits of a latent print AFIS deferral policy.

Forensic laboratories in the United States had an estimated backlog of 570,100 requests for all forensic services at the end of 2014. Latent print requests represented approximately 12% of that total backlog [1, NIJ 2019]. With ever-increasing demands and backlogs, a review of laboratory or section practices becomes vital to operations. Work process and business practice changes can increase efficiencies and result in the reduction of casework backlogs and turnaround times. The automated fingerprint identification system (AFIS) deferral policy implemented by the Latent Print Comparative Section (LPCS) of the Phoenix Police Department Laboratory Services Bureau (PPD LSB) was employed to address the latent print backlog. Five years of multiple AFIS request types were analyzed to demonstrate the positive effects and benefits of such policies, including a 26.32% decrease in turnaround time over the data collection and analysis period and a 90.96% reduction in backlogged requests for one year.

Matrix- and surface-assisted laser desorption/ionization-mass spectrometry analysis of fingermark components for forensic studies: current trends and future prospects.

The chemical analysis of fingermarks (FMs) has attracted considerable attention in the realm of forensic investigations. Techniques based on direct ionization of a sample by laser irradiation, specifically matrix-assisted laser desorption ionization-mass spectrometry (MALDI-MS), have provided excellent figures of merit for analyzing high molecular-weight compounds. However, it can be challenging to analyze low molecular-weight compounds using MALDI-MS owing to potential interference produced by the organic matrices in the low molecular-weight region, which can impede the detection of small molecules (m/z < 700 Da). Alternately, surface-assisted laser desorption/ionization-mass spectrometry (SALDI-MS) has shown great promise for small molecules analysis owing to the unique properties of the nanostructures used, particularly, minimal chemical background in low m/z region improved the production of ions involved in this method. The advancement of MALDI-MS and SALDI-MS has propelled their application in the analysis of FM components, focused on gaining deep insights into individual traits. This review aims to outline the current role of MALDI-MS and SALDI-MS in the chemical analysis of FMs. It also describes the latest achievements in forensic intelligence derived from fingermark analysis using these powerful methods. The accomplishments include the understanding of certain characteristics and lifestyles of donors. The review offers a comprehensive overview of the challenges and demands in this field. It suggests potential enhancements in this rapidly expanding domain to bridge the gap between research and practical police casework.

Customizable Presentation Attack Detection for Improved Resilience of Biometric Applications Using Near-Infrared Skin Detection.

Due to their user-friendliness and reliability, biometric systems have taken a central role in everyday digital identity management for all kinds of private, financial and governmental applications with increasing security requirements. A central security aspect of unsupervised biometric authentication systems is the presentation attack detection (PAD) mechanism, which defines the robustness to fake or altered biometric features. Artifacts like photos, artificial fingers, face masks and fake iris contact lenses are a general security threat for all biometric modalities. The Biometric Evaluation Center of the Institute of Safety and Security Research (ISF) at the University of Applied Sciences Bonn-Rhein-Sieg has specialized in the development of a near-infrared (NIR)-based contact-less detection technology that can distinguish between human skin and most artifact materials. This technology is highly adaptable and has already been successfully integrated into fingerprint scanners, face recognition devices and hand vein scanners. In this work, we introduce a cutting-edge, miniaturized near-infrared presentation attack detection (NIR-PAD) device. It includes an innovative signal processing chain and an integrated distance measurement feature to boost both reliability and resilience. We detail the device's modular configuration and conceptual decisions, highlighting its suitability as a versatile platform for sensor fusion and seamless integration into future biometric systems. This paper elucidates the technological foundations and conceptual framework of the NIR-PAD reference platform, alongside an exploration of its potential applications and prospective enhancements.