Fingerprint Research Articles

Determination and Correlation of Finger Print Pattern and Blood Grouping in Diabetes Mellitus: An Analytical Study

BACKGROUND: To Determine and correlate between fingerprint patterns and blood group in type II diabetes mellitus. RESULTS: One hundred individuals with type II diabetes mellitus and One hundred normal individuals as controls were selected for study. Fingerprints were obtained by dactyloscopy. Various fingerprint patterns like arches, whorls, loops were studied and correlated with the respective blood group based on ABO system among the volunteer controls and diabetics. After obtaining results, the analysis was made using Chi square test and One way ANOVA which showed, the most predominant fingerprint pattern among the 100 diabetic volunteers is “Arch pattern” and the most predominant blood group was “O” positive among the diabetic volunteers. Also correlating both finger print and blood group “Whorl pattern” with “B” blood group showed higher predominance among the healthy volunteers. CONCLUSIONS: This is the first study correlating finger print pattern with blood grouping in subjects of Diabetes mellitus. Our study findings showed that O positive blood group with arch pattern type of finger print was the most common findings among diabetes. Thus correlating fingerprint pattern and blood grouping act as a early predictor tool for diagnosing Type II Diabetes mellitus.

Retrospective analysis of pattern of injuries and cause of death in unclaimed dead bodies brought to Mortuary of Private Medical Institute

Introduction: Establishment of identity is required both in living and dead bodies and in both civil and criminal cases. Unclaimed body is defined as dead person who had no next of kin or no relative or no authorized representative willing to make final disposition of the remains.Aims and objective: The aim of this study was to determine the pattern and distribution of injuries and to find out the cause of the death in unclaimed bodies.Material and methods: In this retrospective study all the autopsies of unclaimed body from September 2018 to August 2022 were included.Results: A total 75 unclaimed body were brought to mortuary for autopsy. Out of 75 cases, 65 (87%) were male and 10 (13 %) were female. Majority of unclaimed bodies in this study belonged to age group 40-50. Contusion on the body was most common type of external injury. Lower limb was most common body part for external injuries. Skull was most common site for fracture. Temporal and temporoparietal were most common cranial bone fractured. Mandible was most common facial bone fractured. Liver laceration was most common internal organ injured in unclaimed bodies. Subarachnoid haemorrhage was most common intracranial haemorrhage. Most common cause of death in the present study was haemorrhage and shock due to antemortem injury.Conclusions: Identification of unclaimed dead body need to be increased by police workforce. Bodies which are unclaimed should be brought to mortuary just after prompt investigation so that autopsy should be started before decomposition which may interfere with autopsy finding and even in identification of the unclaimed body. Colour photography, DNA sampling, finger printing and maintaining dental records should be done for every unclaimedbody.

Development of a facial recognition model using optimized convolution neural network with Tiny-ML and fingerprint authentication for safe lock entry

Safe boxes have been used for centuries to protect valuable items, and their design and construction have evolved over time to improve security. In this study, we carried out the design and implementation of a facial recognition technology using optimized convolutional neural networks (CNNs) with TinyML and fingerprint. The facial recognition system is designed using pre-trained CNN architectures then optimized with TinyML to make it fit into resource constrained edge device, the fingerprint recognition is designed using ridge matching biometric algorithm which fits in perfectly into the microcontroller-based system. The safe box was fabricated using sheet metal and insulated using heat resistive material (fiber glass), components like OV2640 camera module, ESP32-S3, R305 Fingerprint sensor, 4.3 inches touch screen TFT display and a charging module to manage and charge the systems battery were used. The system was implemented to be a level two security and two-way verification system using secured Wi-Fi to access the system before the facial and fingerprint recognition functionality is activated, the sequence of operation can either be facial recognition before fingerprint recognition or fingerprint recognition before facial recognition. Evaluating the system’s facial recognition performance with confusion matrix, of all the optimized CNN architectures like VGGNet, SENet, RestNet, MobileNet-V2, EfficientNet-B0, SENet Architecture performed best outputting an accuracy of 98%, precision of 92%, also SENet unoptimized model performed same, MobileNet-V2 performed optimally in the inference speed test with a speed of 15ms/images with the fingerprint also evaluated using confusion matrix and perform with 98% accuracy. It was noticed that the inference speed of the unoptimized model is faster than that of the TinyML optimized model which is justifiable based on the processing clock speed, memory usage, GPU and architecture of the microcontroller/microprocessor. From the result obtained TinyML proves to be suitable mean for edge AI (artificial intelligence) and is recommended for future research and development.

Fingerprint Identification with Fusion of Gabor and Minutiae Features Using BPNN Classifier

This study presents an innovative approach to fingerprint identification by leveraging the fusion of Gabor and Minutiae features, employing a Backpropagation Neural Network (BPNN) classifier for accurate categorization. The process involves initial handling of a fingerprint image dataset, including crucial pre-processing steps such as resizing images and implementing morphological operations like dilation, erosion, and opening. Subsequently, Gabor features and minutiae extraction are performed, followed by the fusion of these features to create a comprehensive representation. To address dimensionality concerns, Principal Component Analysis (PCA) is applied. The dataset, comprising the fused features and corresponding labels, is then loaded for the final step - classification using a BPNN. The network is configured for feed-forward backpropagation, distinguishing fingerprint patterns into categories such as arch, left loop, right loop, tented, and whorl. The evaluation metric used to measure the success of the classification process is accuracy. This approach aims to enhance fingerprint recognition by combining distinctive Gabor and minutiae features, ultimately achieving a more robust and precise identification system through the utilization of neural network-based classification. Keywords—BPNN, PCA, Finger Print Images Dataset

Different fetal effects on fingers from exposure to phenytoin, phenobarbital, and carbamazepine.

Exposure at conception to phenytoin (PHT), phenobarbital (PB), and carbamazepine (CBZ) has been associated with several different effects on the fetus, including hypoplasia of the distal phalanges, dysmorphic facial features, and structural abnormalities such as oral clefts and neural tube defects. One question is whether each of these antiepileptic drugs (AEDs) has the same effects or just similar effects. A systematic examination of the fingers of children exposed at conception to PHT, PB, or CBZ, as monotherapy, has been used to address this question. The findings in the examinations of the fingers of 115 AED-exposed children (40, PHT; 34, PB; 41, CBZ) and their parents were compared to the findings in 111 age- and sex-matched children and their parents. The evaluations used were both subjective assessments and objective measurements. Shortening and narrowing of the fifth fingernail and an increased frequency of arch patterns in the dermal ridges were more common in PHT-exposed children. A significant decrease in the length of the nail, but not width, occurred in the PB-exposed children. Stiffness of the interphalangeal joints was more common in the CBZ-exposed children. The findings in children exposed to PHT, PB, or CBZ, as monotherapy, showed that all three exposures in early pregnancy affected the fingers, but the effects were not the same. The most striking effects were present in PHT-exposed children.

The role of phenotypic factors in predicting the effectiveness of chemoprophylaxis in children

Background. The purpose was to study the prognostic role of some phenotypic factors in the effectiveness of tuberculosis chemoprophylaxis in children at present stage. Materials and methods. To study the role of phenotypic factors in predic­ting the effectiveness of tuberculosis chemoprophylaxis, an analysis was performed of dermatoglyphic indicators, gender, and the inactivation phenotype of isonicotinic acid hydrazide (IAH) in 76 children with tuberculin skin test conversion who underwent a 3-month course of preventive therapy with isoniazid. Dermatoglyphics of fingers and palms was determined according to the standard method [5]. The dynamics of skin sensitivity to tuberculin PPD-L according to the Mantoux test with 2 tuberculin units was used as a criterion for the effectiveness of chemoprophylaxis. According to the latter, the examinees were divided into two groups: the first one consisted of 52 children in whom the size of a wheal decreased by 4 mm or more after the end of a course (effective chemoprevention); the second one included 24 patients in whom skin sensitivity to tuberculin increased or remained at the previous level or decreased by a wheal size for 3 mm or less (ineffective chemoprevention). Results. The conducted statistical analysis revealed a significant difference in 7 indicators between the groups (p < 0.05). Determination of their prognostic informativeness made it possible to rank the prognostic significance of phenotypic signs, namely: the size of the atd angle on the left palm (J = 1.7), the number of ulnar loops on the right hand (J = 1.4), the type of IAH inactivation (J = 1.3), the number of whorls on the right hand (J = 1.2), the total number of whorls (J = 1.1), the atd angle on the right palm (J = 0.7), the number of whorls on the left hand (J = 0.5). The correlation analysis between the dermatoglyphic indicators and the type of IAH inactivation showed that there are reliable connections between them (p < 0.05), but their number differs significantly in groups. In patients with ineffective chemoprophylaxis, the number of correlations (n = 13) exceeded that of the alternative group (n = 2) by more than 6 times, which indicates significant structural phenotypic differences. Conclusions. There were significant correlations between the type of IAH inactivation and dermatoglyphic indicators, but the number of such connections was 6 times higher in children with ineffective chemoprophylaxis than in the alternative group. This indicates that a more pronounced integration of dermatoglyphic genes and the ability to neutralize IAH is a favorable moment in general, but negative in relation to the effectiveness of tuberculosis prevention.

Fingerprint Recognition and Verification using Fourier Domain Filtering and Histogram Equalization Techniques

Fingerprint Recognition is a vital method in biometric identification and verification of human beings in various domains like Security, Digital Forensics, Internet of Things (IoT), and many more. Each individual human is having distinct fingerprint pattern than others, hence it is one of the most prominent and widely used method to distinguish individuals. Many research studies and solutions have been developed in biometric domain since a decade, which influences now in making the process of fingerprint recognition more optimized, faster and efficient. However, present fingerprint acquisition/recognition systems have some limitations, mainly longer computation time for fingerprint matching and evaluating the results. This paper presents a procedure for fingerprint matching that takes into account minutiae features in finger print images and the process of creating an OpenCV structure for minutiae extraction and matching of fingerprints.

Automated Baby Stroller Using IOT

The Automated Baby Stroller is an Internet of Things (IoT) based project that incorporates sensors and hardware integrated with ESP 8266. One of the key modules of this project is "Fingerprint Authentication for Authorized Handler of Baby Stroller", which aims to provide enhanced security for the baby stroller. The handlers of the stroller need to authenticate themselves through fingerprint recognition in order to unlock the wheels of the stroller. If the handler fails to authenticate, an alarm is raised. Additionally, the stroller is equipped with a sensor that detects obstacle the way. In this work, we provide a brief overview of the design and working of a prototype of the Smart Baby Stroller with fingerprint authentication and sensing features. Key Words: Baby Stroller, Automated Baby Stroller, IoT, Fingerprint Authentication, Authorized Handler, ESP 8266, Security, Sensor, Prototype.

Detection of HPTLC Fingerprint in Aerial Parts of Aerva lanata Linn. HPTLC Finger Print Profile and Evaluation of in vitro Antioxidant Activity of Aerva lanata Linn. Juss

Detection of HPTLC Fingerprint in Aerial Parts of Aerva lanata Linn. HPTLC Finger Print Profile and Evaluation of in vitro Antioxidant Activity of Aerva lanata Linn. Juss

Combined experimental and quantum computational studies on 5-Fluorouracil salicylic acid cocrystal: Assessment on anti-breast cancer potential through docking simulation

5-fluorouracil salicylic acid (5FUSA) cocrystal was synthesised via mechanochemical and solution evaporation technique and spectroscopic experiments and theoretical research were conducted. Methods for the experiments included XRD, FTIR, and UV spectroscopy. Following that, 5FUSA was the subject of quantum chemistry investigations employing the DFT/B3LYP/6–311++G (d, p) basis level. First, the resultant simulated XRD pattern was compared to the relevant experimental pattern. The estimated FT-IR frequencies were gathered from the same level of theory and compared to the experimental data. To learn more about the reactive properties of the 5FUSA, the molecular electrostatic potential plot was generated, and Fukui function calculations were also performed. In order to examine intramolecular interactions and verify the bioactivity of the 5FUSA molecule, the natural bond orbital study was also carried out. We examined the UV–Vis absorption wavelengths (λ) via theoretical (TD-DFT) and experimental methods. The non-linear optical properties were identified, and it was discovered that it had three times the NLO activity of urea. The inter- and intramolecular interactions of the 5FUSA were explored using the Hirshfeld surface and finger print approaches. At various temperatures thermodynamic parameters were calculated and topological analyses were conducted using the (ELF, LOL, and RDG). The anticancer activity of 5FUSA cocrystal was studied using molecular docking and the docking scores ranges between -8.1 to -9.0 Kcal/mol against breast tumor proteins.

Enhanced luminescence of Dy-activated in-situ synthesized LaAlO3/MgO nanocomposites for cool wLED and latent finger printing applications

In the current study, a series of trivalent Dysprosium doped La1-xDyxAlO3/MgO (with x = 0, 1, 3, 5, 7 and 9 mol. %) nanophosphor composites have been synthesized via Pechini sol-gel method. Structural properties were analyzed using XRD, Rietveld refinement and FESEM. The prepared nanophosphors exhibit rhombohedral/face-centered structure. The bandgap values of the nanophosphors were found to be in the range of 5.39–5.75eV. At the sintering temperature of 900 °C, La1-xDyxAlO3/MgO (x = 5 mol.%) nanocomposite exhibit significant enhancement in the white light emission as compared to La1-yDyyAlO3 (y = 5 mol.%). PL intensity of composite further increases with the rise in sintering temperature up to 1200 °C. Dexter's theory and Burshtein model when applied to PL and TRPL profiles unveil the d-d energy transfer mechanism that shifts from donor-acceptor to donor-donor transfer with dopant concentration. Other exemplary colorimetric and luminescence-based parameters such as, CRI, CCT, life-time, energy transfer efficiencies and probabilities indicate the potential suitability of fabricated phosphor for w-LED and imaging applications. The optimized nanophosphor composite, i.e., La1-xDyxAlO3/MgO (x = 5 mol.%) has been explored for Latent Finger Printing and it successfully identified all the levels-1, 2 and 3 features of fingerprint.

Variational autoencoder-assisted unsupervised hardware fingerprint authentication in a fiber network.

Physical-layer authentication (PLA) based on hardware fingerprints can safeguard optical networks against large-scale masquerade or active injection attacks. However, traditional schemes rely on massive labeled close-set data. Here, we propose an unsupervised hardware fingerprint authentication based on a variational autoencoder (VAE). Specifically, the triplets are generated through variational inference on unlabeled optical spectra and then applied to train the feature extractor, which has an excellent generalization ability and enables fingerprint feature extraction from previously unknown optical transmitters. The feasibility of the proposed scheme is experimentally verified by the successful classification of eight optical transmitters after a 20 km standard single-mode fiber (SSMF) transmission, to distinguish efficiently the rogue from legal devices. A recognition accuracy of 99% and a miss alarm rate of 0% are achieved even under the interference of multiple rogue devices. Moreover, the proposed scheme is verified to have a comparable performance with the results obtained from supervised learning.

Deep Learning Model Based Criminal Identifications System

Criminal record generally contains all the information both personal and criminal with the photograph of the person. In order to recognize Criminal, identification of some sort is required, designated by eyewitnesses. In most cases the resolution or/and quality of the recorded image sections is unsatisfactory and is difficult to recognize the face. Recognition can be achieved in various different ways like DNA, eyes, finger print, etc. One of the ways is face identification. Since facial recognition technology is powered by artificial intelligence, it can provide excellent results in identifying criminals. Even considering that most people, when committing an illicit activity, try to hide their identity: hiding their faces or covering their faces with scarves, masks, etc. In such cases, AI uses deep learning methods to identify the individual. In this project, proposed an Deep Face an automatic criminal identification system for Police Department to enhance and upgrade the criminal distinguishing into a more effective and efficient approach using Convolutional neural network algorithms. In our proposed methodology, a database is created by storing both full and sliced images of the criminals along with all the personal and criminal details. The captured images of the person get compared with the criminal data Law Enforcement Agencies have in their database. The CNN involves mapping the face with some facial points, allowing the true identity of the individual to be revealed. Using technology, this idea will add plus point in the current system while bringing criminals spotting to a whole new level by automating tasks. Law enforcement receive alerts when an individual claimed by the authorities is identified by our technology, speeding up their arrest and preventing new crimes. Customize notifications and alarms based on a variety of detection or recognition events and program automated security response workflows and SMS and email notifications. Index Terms— Criminal records, Database, Facial recognition, Deep face, User Interface, Neural networks, Detection, Automation.

Hardware Fingerprint Authentication Based on Siamese Neural Networks in PON

Hardware Fingerprint Authentication Based on Siamese Neural Networks in PON

Identification of Dermal Crease Patterns as a Link between Genetics and Periodontitis: Reliability and Credibility

Introduction: The disruptions in the ectodermal layer during intrauterine growth in the process of the formation of epidermal ridges can be linked to the association between dermatoglyphics and abnormalities of the tooth and periodontium. Given the genetic linkage of periodontal disease this study was hypothesized at observing the association of chronic periodontitis, aggressive periodontitis, and individuals with healthy periodontium as per the 1999 AAP classification of periodontitis with their fingerprint patterns and ridge count. Materials and Methods: Patients belonging to an age cohort of 18–50 who visited the department of periodontics and implantology were included in the study. Patients’ periodontal status was determined and was enrolled in the study. A total of 114 subjects were compared, where 38 subjects belonged to the individual group of periodontal condition that are designated as Group A (healthy), Group B (chronic periodontitis), and Group C (aggressive periodontitis). A total of 1140 fingerprints were collected. They were analyzed and classified according to their patterns and also the ridges were counted. Results: The comparison between three groups showed a statistically significant difference between increased percentage frequency of radial loops (28%) in chronic periodontitis and plain whorls (26.3%) in aggressive periodontitis. There was a significant difference between ridge count among all the three groups, the highest being in healthy and the least between aggressive periodontal conditions. Conclusion: Observations of the study show that there was a difference in fingerprint pattern between patients of all the three periodontal conditions indicating a link between epidermal ridges and condition of periodontium.

Where do they come from?

Globular clusters (GCs), as old as our Galaxy, constantly lose their members to the field as they cross through the Milky Way (MW). These escaped GC stars (or escapees) are thought to contribute significantly to the MW halo. If a star left the host GC a long time ago, chemical finger prints (e.g., N enrichment) may reveal its origin. In this work we aim to establish dynamical connections between N-rich field stars recently identified by LAMOST and the existing MW GCs. By constructing the full action distribution in combination with metallicity, we found 29 potential GC progenitors for 15 N-rich field stars. In particular, some of them may be related to MW accretion events. On the other hand, if a star has recently left its host GC via tidal evaporation, it still maintains the kinematic properties of the cluster. Here we identify extra-tidal candidates based on their spatial locations, proper motions (PMs), and their positions on color-magnitude diagrams (CMDs). We successfully identified more than 1600 extra-tidal candidates in the vicinity of six Gaia-Enceladus (GE)-related GCs: NGC 1851, NGC 1904, NGC 6205, NGC 6341, NGC 6779, NGC 7089. The density map of the extra-tidal candidates is confirmed to be an efficient way to find extra-tidal structures. The two possible density peaks at opposite sides of the inner boundary is a good indicator for a long stellar stream. Among 95 extra-tidal candidates with spectroscopic radial velocities and metallicity, 54 of them are confirmed to be GC escaped stars as they share similar properties to host GCs. These extra-tidal candidates are ideal targets for follow-up spectroscopic observation as it greatly improves the scientific outcome. Once a statistically significant number of spectroscopic radial velocities and metallicities are available, the GC dynamical evolution (e.g., mass loss, rotation) can be carefully investigated.

Smart Attendance System

Abstract: The combination of Electronics Engineering and Information Technology is played a significant roles in developing several aspects in academics such has in students attendance monitoring. Taking attendance manually often time consuming process which also increased mistakes and false in the attendance so overcome this situation we make this project Smart Attendance System. In this project, we will learn how to build IOT based Smart Attendance System using NodeMCU ESP8266 12E, OLED Display and Finger print module R608. we have also created database to register the student fingerprint in database. The system works in such a manner that when we put our finger on the sensor, which would scan their finger print and send the data to the NodeMCU.

Analysis of fingerprint patterns and axial triradius digital angles in the Komering population

Some dermatoglyphic components that can be used to analyze a population are fingerprint patterns and Axial Tri-Radius Digital (ATD) angles because they are unique to each ethnic group. This study aimed to determine variations in fingerprint patterns and ATD angles in the Komering population in Palembang. The study of fingerprint patterns and ATD angles was descriptive. The sample size was 43 respondents registered in the Gunung Batu Family Association (IKA GUBA) Komering Ulu Timur in Palembang City. The results showed that the ulnar loop pattern was the most common fingerprint pattern, with 90.4% on the right palmar hand and 85.9% on the left palmar hand. The most minor fingerprint pattern is accidental whorl, which is 0% on the right palmar hand and 1.8% on the left. The 30°-45° angle dominates the right and left palmar ATD angles (88.4% and 86.0% respectively).

Unmasking Aadhar Authentication Issues: A Case Study of Biometric and PDS Access in Mundoti, Rajasthan

This paper goes into great depth about how hard India's Aadhaar-based identification system is to understand, especially when it comes to how important it is for people to be able to access simple services. Most of the study is about Mundoti, a village in Kishangarh, Rajasthan, where people's farming and hard work-based lives have made it hard to use Aadhaar. The paper looks at how common negative fingerprinting is and how it affects people's ability to use the Public Distribution System (PDS). It does this through a case study and direct and indirect research methods. Through conversations, it looks into the connection between having to wear fingerprints at work, demographics, and any possible effects on PDS. The study says that the people of Mundoti have trouble with Fingerprint authentication because of work in agriculture. This means that they are facing problems in getting important food aid. The study makes it clear that these problems need to be fixed. The people who live in Mundoti have trouble verifying their Aadhaar cards because their fingerprints are worn down from working hard in agriculture. The study also shows that age, gender, and job have a big effect on how likely it is that you will have identification problems. The paper argues that these fingerprint-related problems should be fixed so that important social aid programs can be carried out successfully in rural India. It suggests creating different ways to prove your identities, like eye scans or private biometric-based solutions so that vulnerable people aren't kept from important services like PDS as much as possible. This paper adds to the larger conversation about local ecosystems that includes everyone. It stresses how important it is to change rules and procedures to fit the needs of people living in rural areas.

Dermatoglyphic palmar pattern variations in congenitally deaf and mute subjects

Background: Dermatoglyphics have the unique merit of retaining all their peculiarities unchanged throughout life, and afford in consequence an incomparably surer criterion of identity than any other bodily feature. The rationale for studying dermatoglyphic features is derived from the fact that development of dermal ridges and congenital deafness seems to develop at around the same time. Methods: The material for the study consisted of palm prints of congenitally deaf and mute children of 100 subjects with congenital deafness and muteness between 5-21 years of age and 50 control of similar age group with normal hearing and speech were chosen. The principal patterns of thenar/ I interdigital, interdigital II, interdigital III, interdigital IV and hypothenar area were noted. Position of axial triradius, ‘atd’ angle, pattern of palmar Flexion Creases, presence as well as pattern of the Simian Line and the Sydney Line were recorded. Results: The percentage of open field was maximum in subjects in thenar / interdigital area I. and in interdigital area IV. The mean a-b, c-d and atd angle ridge palmar ridge count was less in subjects in comparison to controls. Highly statistically significant results were obtained between subjects and control for the simian crease pattern when both hands were considered together in which the percentage of transitional type was more than the typical simian crease in subjects. Conclusion: When combined with other clinical and investigative features, dermatoglyphic study can serve as a diagnostic impression and can be advocated as a useful screening device.