Fingerprint Recognition Research Papers - Academia.edu (original) (raw)

2025, Anuario Colombiano de Historia Social y de la Cultura

Objetivo: resaltar una desconocida historia de la identificación científica en el Ecuador entre 1896 y 1927. Atendiendo a la circulación y adaptación de sistemas de antropometría y dactiloscopía entre Juan Vucetich, jefe de las Oficinas de Estadísticas e Identificación de la Provincia de Buenos Aires, y jefes de policía e intelectuales ecuatorianos, las tempranas prácticas de identificación en el Ecuador se extendieron más allá de los delincuentes, abarcando a grupos sociolaborales y civiles, pero en especial a los ciudadanos chinos. Metodología: lo anterior se realiza a través del análisis de fuentes primarias, como cartas, periódicos, revistas, leyes, oficios y registros de identidad. Originalidad: hasta ahora, son hechos inexplorados por los estudios sobre identificación en América Latina. En esta
circulación sur-sur de sistemas de identificación tuvieron un rol predominante los ecuatorianos Aníbal Viteri Lafronte y Ernesto Sáenz de Viteri. En especial este último, quien estudió antropometría y dactiloscopía en Buenos Aires, organizó las primeras oficinas de identificación dactiloscópica del Ecuador, en Quito y Guayaquil, en 1924, y en la ciudad colombiana de Cali, en 1927. Conclusiones: el Ecuador formó parte de las naciones latinoamericanas que mantuvieron conexiones con Juan Vucetich y adaptaron los sistemas de identificación biométricos establecidos en Argentina y Chile con propósitos de control policial y racial. Finalmente, el Ecuador intervino dinámicamente en la difusión y organización de servicios de identificación dactiloscópica en la región, como fue el caso de Cali, Colombia.

2025, 2006 IEEE International Symposium on Signal Processing and Information Technology

New technology for recognizing fingerprints for security purposes is proving as regards as reliable but efficient recognition is depending on the quality of input fingerprint image. Recognition of the fingerprint becomes a complex computer problem while dealing with noisy and low quality images. The proposed SWT based composite method is used for fingerprint image enhancement using SWT transform, morphological operation, quick mask and spatial filters. We have applied proposed method on FVC2002 fingerprint database and experimental results shows that this composite method is more effective and robust than the other existing method. Finally the result has compared using the texture descriptors.

2025, 2006 International Conference on Advanced Computing and Communications

In this paper, we have considered a problem of uneven background extraction and segmentation of good, normal and bad quality fingerprint images, though we propose an algorithm based on morphological transformations. Our result shows that the proposed algorithm can successfully extract the background of good, normal and bad quality images of fingerprint and well segment the foreground area. The algorithm has been tested and executed on FVC2002 database and the performance of proposed algorithm is evaluated through subjective and objective quality measures. This algorithm gives good and promising result and found suitable to remove superfluous information without affecting the structure of fingerprint image as well as reduces the storage space for the resultant image upto 77%. Our results will be useful for precise feature extraction in automatic fingerprint recognition system.

2025, Zenodo (CERN European Organization for Nuclear Research)

This paper describes the results of an extensive study and comparison of popular hash functions SHA-1, SHA-256, RIPEMD-160 and RIPEMD-320 with JERIM-320, a 320-bit hash function. The compression functions of hash functions like SHA-1 and SHA-256 are designed using serial successive iteration whereas those like RIPEMD-160 and RIPEMD-320 are designed using two parallel lines of message processing. JERIM-320 uses four parallel lines of message processing resulting in higher level of security than other hash functions at comparable speed and memory requirement. The performance evaluation of these methods has been done by using practical implementation and also by using step computation methods. JERIM-320 proves to be secure and ensures the integrity of messages at a higher degree. The focus of this work is to establish JERIM-320 as an alternative of the present day hash functions for the fast growing internet applications.

2025

Abstract-This paper focuses on extensive testing of multimatcher methods for obtaining a system that is comparable with the state-of-the-art commercial matchers. Through extensive testing, we propose an ensemble method that uses minutiae, correlation-based, and hybrid methods. To further improve our system, we conduct experiments with matchers that are also based on different enhancement techniques, combining matcher scores by sum rule. Our results are validated on all four FVC2004 DBs and on the easier FVC2002 DB2. Finally, ...

2025, Computer Science and Information Technology

This article describes the computer system developed for the detection of minutiae in fingerprints images. The system described can perform automatic and manual extraction of important data from the fingerprints images, storing that information in the internal database. The statistical calculations, including calculations for cumulative frequency analysis, generated by the system are very important for calculating distinction rates. The system is also capable to differentiate by male or female gender, finger, fingerprint type and sector that has been divided the fingerprint.

2025, Time Vision

In hospitals, safety goes beyond patient care. It also means protecting restricted areas like labs, ICUs, and medicine rooms. One of the best ways to do this is by using biometric access control systems. These systems make it easier and safer to manage who enters sensitive spaces. Let's explore why access control system installation is a smart move for hospitals.

2025, Journal of computer and communications

Fingerprint identification and recognition are considered popular technique in many security and law enforcement applications. The aim of this paper is to present a proposed authentication system based on fingerprint as biometric type, which is capable of recognizing persons with high level of confidence and minimum error rate. The designed system is implemented using Matlab 2015b and tested on a set of fingerprint images gathered from 90 different persons with 8 samples for each using Futronic's FS80 USB2.0 Fingerprint Scanner and the ftrScanApiEx.exe program. An efficient image enhancement algorithm is used to improve the clarity (contrast) of the ridge structures in a fingerprint. After that core point and candidate core points are extracted for each Fingerprint image and feature vector have been extracted for each point using filterbank_based algorithm. Also, for the matching the KNN neural network was used. In addition, the matching results were calculated and compared to other papers using some performance evaluation factors. A threshold has been proposed and used to provide the rejection for the fingerprint images that does not belong to the database and the experimental results show that the KNN technique have a recognition rate equal to 93.9683% in a threshold equal to 70%.

2025, IEEE Transactions on Image Processing

This paper presents a new approach to improve the performance of finger vein identification systems presented in the literature. The proposed system simultaneously acquires the finger vein and low resolution fingerprint images and combines these two evidences using a novel score level combination strategy. We examine the previously proposed finger vein identification approaches and develop a new approach that illustrates it superiority over prior published efforts. The utility of low resolution fingerprint images acquired from a webcam is examined to ascertain the matching performance from such images. We develop and investigate two new score level combinations, i.e., holistic and nonlinear fusion, and comparatively evaluate them with more popular score level fusion approaches to ascertain their effectiveness in proposed system. The rigorous experimental results presented on the database of 6,264 images from 156 subjects illustrate significant improvement in the performance, both from the authentication and recognition experiments.

2025, Zenodo (CERN European Organization for Nuclear Research)

The demand for indoor localization services has led to the development of techniques that create a Fingerprint Map (FM) of sensor signals (e.g., magnetic, Wi-Fi, bluetooth) at designated positions in an indoor space and then use FM as a reference for subsequent localization tasks. With such an approach, it is crucial to assess the quality of the FM before deployment, in a manner disregarding data origin and at any location of interest, so as to provide deployment staff with the information on the quality of localization. Even though FM-based localization algorithms usually provide accuracy estimates during system operation (e.g., visualized as uncertainty circle or ellipse around the user location), they do not provide any information about the expected accuracy before the actual deployment of the localization service. In this paper, we develop a novel framework for quality assessment on arbitrary FMs coined ACCES. Our framework comprises a generic interpolation method using Gaussian Processes (GP), upon which a navigability score at any location is derived using the Cramer-Rao Lower Bound (CRLB). Our approach does not rely on the underlying physical model of the fingerprint data. Our extensive experimental study with magnetic FMs, comparing empirical localization accuracy against derived bounds, demonstrates that the navigability score closely matches the accuracy variations users experience.

2025, arXiv (Cornell University)

Liveness Detection (LivDet) is an international competition series open to academia and industry with the objective to assess and report state-of-the-art in Presentation Attack Detection (PAD). LivDet-2023 Noncontact Fingerprint is the first edition of the noncontact fingerprint-based PAD competition for algorithms and systems. The competition serves as an important benchmark in noncontact-based fingerprint PAD, offering (a) independent assessment of the state-of-the-art in noncontact-based fingerprint PAD for algorithms and systems, and (b) common evaluation protocol, which includes finger photos of a variety of Presentation Attack Instruments (PAIs) and live fingers to the biometric research community (c) provides standard algorithm and system evaluation protocols, along with the comparative analysis of state-of-the-art algorithms from academia and industry with both old and new android smartphones. The winning algorithm achieved an APCER of 11.35% averaged over all PAIs and a BPCER of 0.62%. The winning system achieved an APCER of 13.0.4%, averaged over all PAIs tested over all the smartphones, and a BPCER of 1.68% over all smartphones tested. Four-finger systems that make individual finger-based PAD decisions were also tested. The dataset used for competition will be available 1 to all researchers as per data share protocol.

2025

The quality of the fingerprint images greatly affects the performance of the minutiae extraction. Dry fingerprint images are poor quality, which his ridges are scratchy locally and there are many white pixels in the ridges. In order to improve the quality of the fingerprint image, many researchers have been made efforts on the image enhancement algorithms. If the preprocessing is applied for the dry fingerprint image enhancement step, the quality gets would be more robust. In this paper, used the preprocessing method improve image quality appropriately, by applies several steps on the dry fingerprint image, smoothing, skeltonization, dilation, and the union of black pixels in the original image and dilated image. Experimental results indicate that the preprocessing method improves the quality of the dry fingerprint images significantly.

2025, IEEE Transactions on Pattern Analysis and Machine Intelligence

A minutiae-based template is a very compact representation of a fingerprint image, and for a long time, it has been assumed that it did not contain enough information to allow the reconstruction of the original fingerprint. This work proposes a novel approach to reconstruct fingerprint images from standard templates and investigates to what extent the reconstructed images are similar to the original ones (that is, those the templates were extracted from). The efficacy of the reconstruction technique has been assessed by estimating the success chances of a masquerade attack against nine different fingerprint recognition algorithms. The experimental results show that the reconstructed images are very realistic and that, although it is unlikely that they can fool a human expert, there is a high chance to deceive state-of-the-art commercial fingerprint recognition systems.

2025, The International Arab Journal of Information Technology

The main purpose of the classification of fingerprints is to devise a formula by which a given collection of fingerprints can be tracked and registered. To accelerate the system for classifying fingerprints, it is necessary to utilize fingerprint image characteristics and avoid the different fingerprint forms arising from fingerprint rotation. This paper presents a simple, new approach to the extraction of characteristics from fingerprint images. The proposed method demonstrates that, for a given image, the features remain constant even after being subjected to a wide range of rotations; thus, it creates an array of characteristics which can be used to identify a person from their fingerprint. To achieve this goal, a basic hit-and-miss operation with different structural components is used to detect and count various features in the fingerprint picture; these features are directly identified based on the texture of the fingerprint. The chosen features are used to index the finger im...

2025, Innovative Design Thinking Approaches in Software Engineering

The integration of Legal Design Thinking into software engineering represents a transformative shift in the development of legal technology. By applying user- centered design principles, this approach enhances legal accessibility, operational efficiency, and client satisfaction. This chapter systematically reviews the core tenets of Legal Design Thinking, including empathy, ideation, prototyping, and testing, and examines its role in improving legal services through software applications. Additionally, this work explores the challenges of integrating Legal Design Thinking into software development, particularly concerning technical constraints, ethical considerations, and regulatory compliance. Future opportunities, such as advancements in AI, automation, and interdisciplinary collaboration, are discussed as potential pathways for further innovation in the legal sector. This chapter aims to provide valuable insights for legal practitioners, software engineers, and policymakers in the evolving landscape of legal technology and user- centered innovation.

2025, 2018 International Carnahan Conference on Security Technology (ICCST)

The version in the Kent Academic Repository may differ from the final published version. Users are advised to check for the status of the paper. Users should always cite the published version of record.

2025, Springer eBooks

Fingerprint recognition represents the most installed recognition modality in modern mobile devices. Currently, there are thousands and thousands of smartphones equipped with fingerprint sensors; the type of sensor and its position on the device changes depending on the model. The fingerprints sensors are typically positioned in the home button (front side), even if sensors embedded on the backside or on the lateral side are equally common. In this paper, we research how the ergonomics of the mobile fingerprint systems influences the user experience and consequently the outcome of the identification. For this reason, we assessed the user interaction with a fingerprint recognition system installed in 3 smartphones (differentiated by the position of their fingerprint sensors). Data collected during the experiment let us analyse how the position of the sensors changes the recognition system's performance and the user feelings while completing a biometric authentication.

2025, Advances in Intelligent Systems and Computing

2025, Journal of Computer Networks, Architecture, and High-Performance Computing

The level of crime of theft in people's homes from time to time is increasing and increasingly unsettling for many people and various groups, from leading sources claiming that there has been an increase in theft in people's homes from the previous year, by conducting research objects in the community by identifying existing problems. It can be concluded that this happens because the house door security system still uses conventional which is classified as unsafe or easily broken into, by carrying out research method steps in the form of analysis and data collection and in the form of designing tools by describing some of the main supporting tools that the problem can be minimized by using technology that is currently developing that is already well systemized, namely using a microcontroller or Arduino as the main control center, assisted by using a fingerprint sensor as a process for recording and identifying fingerprints and NodeMCU for to connect to a WiFI network where l...

2025, Journal of Engineering Science and Technology

In recent years, Finger Outer Knuckle (FOK) has come out as a promising biometric modality. This paper considers enhancing the FOK recognition of verification by using a suggested efficient deep learning network. It is called the Deep Recurrent Neural Network (DRNN). This network has the ability to deal with both minor and major FOKs. It consists of input layer, hidden layers, output layer and global feedback. It can further increase the verification performance. Images of minor and major FOKs from the Indian Institute of Technology Delhi Finger Knuckle (IITDFK) dataset are employed. The result demonstrates promising accuracy verification rate of 96% after utilizing both major and minor FOKs.

2025, Proceedings of I …

Abstract. The Project MOSAICLearning tries to alleviate the high economic cost derived from the examinations in a distance university, allowing by a side the remote examination using biometric and security techniques, and by an-other one... more

2025

Vehicle fuel theft is a prevalent problem causing financial loss and inconvenience to owners. This paper presents a GSM-based fuel theft detection system that monitors the fuel level in a vehicle's tank and provides instant alerts via SMS and an audible alarm when unauthorized fuel drainage is detected. The system is built around a microcontroller interfaced with a fuel level sensor, a GSM modem for SMS communication, and a buzzer alarm. To prevent false alarms during normal vehicle operation, the system is armed only when the ignition is off. A prototype has been constructed and tested, demonstrating that the system can successfully detect rapid fuel level drops and send SMS alerts within seconds, thereby offering a cost-effective solution for improving vehicle fuel security..

2025

This project addresses the limitations of the current manual attendance system for non-teaching staff at Federal Polytechnic Bida, which suffers from inaccuracies, inefficiencies, and a high risk of fraudulent practices like buddy punching. To overcome these issues, this study focuses on designing and implementing a facial recognition-based Attendance Monitoring System. By using facial recognition technology, which relies on unique facial features for identification, this system aims to provide a more accurate, secure, and automated approach to attendance tracking. Facial recognition offers a contactless method that reduces errors associated with manual entry and minimizes the potential for attendance fraud. Additionally, this technology allows for real-time monitoring, providing administrators with up-to-date data that can aid in better staff management and decision-making. Through detailed steps involving data collection, database creation, and system integration, this project seeks to enhance attendance practices at the institution, improving overall efficiency, security, and accountability for non-teaching staff.

2025, International Journal of Engineering Research and Advanced Technology

Fingerprint recognition is one of the interesting and mature biometric technique for personal identification or authentication application. The objective of the work is to retrieve personal data by using the fingerprint. In this paper, the fingerprint of a person is captured via Digital Persona U.are.U 4500 fingerprint scanner. The input fingerprint is firstly enhanced using contrast stretching and two morphological operations (dilation and erosion). Next, 160x160 size of the center region of the fingerprint is cropped and extracted minutiae such as ridges and bifurcations. These minutiae are used as the features of a particular fingerprint. These features are put into the Neural Network for person recognition. Various experiments will confirm and prove the accuracy and performance of the proposed fingerprint recognition system.

2025, International Journal of Database Theory and Application

This paper presents a report on the experimental study of the impact of false minutiae on the performance of fingerprint matching systems. A 3-tier algorithm comprising of preprocessing, minutiae extraction and post-processing stages formed the backbone of the experiments. The pre-processing stage enhanced the fingerprint image, the minutiae extraction stage used the minutiae properties to detect and extract true and false minutiae points while the post-processing stage eliminated the false minutiae points. The experiments were performed on the four datasets in each of the three standard fingerprint databases; namely FVC2000, FVC2002 and FVC2004. The completion times for the minutiae extraction and the post-processing algorithms on each dataset were measured. A standard fingerprint matching algorithm was also implemented for verifying the impact of false minutiae points on FAR, FRR and the matching speed. Analysis of the obtained results revealed that for reliable and optimal performance of fingerprint matching systems, false minutiae points must be eliminated as much as possible from their operations.

2025, British Journal of Applied Science & Technology

Fingerprint has continued to enjoy dominance over other biometrics like face, iris, nose, signature among others in human verification and authentication. This is promoted by its major characteristics which include availability, uniqueness, consistency and reliability. Fingerprint verification and authentication involves the serial stages of enrolment, processing and matching. Enrolment through a number of fingerprint capturing devices helps to read the fingerprint into a target location from where processing takes place. Processing of a fingerprint image involves enhancement, feature extraction and singular point detection. Matching of fingerprint is performed based on the extraction results to establish its source or similarity level. The extraction of true singular (core and delta) and feature points is paramount for a true fingerprint matching and a number of algorithms had been formulated to accomplish it. This paper presents a review and evaluation of commonly known fingerprint singular point detection algorithms with emphasis on methodologies, strengths and weaknesses.

2025, International Conference

As a result of the massive frauds, rigging and post election violence associated with student's elections in most Nigerian tertiary institutions, it is true that these institutions needs another system of voting other than the manual system. Thus, in this paper software development support systems like unified modeling language (UML) was used to design the system, C#.Net programming language to code the logic of the application, Visual Studio compiler to test run the application, SQL Server to design the database and ASP.Net to design the interfaces of the application. The full implementation of this system in Nigerian Universities will go a long way to solving the problems associated with the current (manual) system of voting and set a foot print for other elections in the country at large, thereby contributing to the country's National Development.

2025, AAU J. Physical & Applied Sciences.

Attendance management is a very important aspect for most sectors of the world including learning institutions, ministries and organizations. Managing student's attendance in learning institutions during lectures can be very tasking, incredible and time consuming if done manually. Manually taking attendance lacks the feature of authentication. For the obvious reasons stated above, a student attendance management system which uses fingerprint for recognition has been developed in this paper to manage student's attendance. This system takes the attendance of students using fingerprint reader and stores the records in a database on the server. This student attendance management system was designed using C# as the core programming language. ASP.NET was adopted for the development of the user interface and the application database uses Microsoft SQL server. The results of the implementation shows that the system can help to monitor, manage and generate accurate lecture attendance register without compromised. This will help to improve the operations of our higher institutions of learning and also encourages many students in attending their lectures since they knew that, such system need their fingerprint authentication and cannot be compromised. This system can also be modified and deployed to eliminate impersonation in the conduct of computer-based examination in institution of higher learning.

2025, International Journal For Multidisciplinary Research

Modern car security systems have been developed as a result of the growing demand in the automotive sector for increased convenience and security. In order to provide safe access management and authentication for cars, this paper suggests a face recognition system-based auto security system that makes use of facial recognition techniques. When a match is detected, the system uses computer vision algorithms to identify and detect the faces of approved drivers, enabling the car to be unlocked and started without any issues. In order to convert near infrared face images into their corresponding visible images, we develop a nir-vis image translation model. Using two distinct nir databases of face images, the pre-trained face embedding model is applied to present the evaluation performances. The proposed system offers improved security by eliminating the need for traditional key-based systems and providing a robust biometric-based authentication mechanism. Anti-spoofing procedures are al...

2025, IEEE Latin America Transactions

The field orientation and binarization in an image are widely used in authentication and identification of fingerprints and analysis of textures. The proposed algorithm reuses the operations of addition and multiplication to calculate the orientation field using the commutative property and uses Digital Differential Analyzer (DDA) algorithm in the generation of convolution masks for the binarization of fingerprint images. The performance of the processing time and the result of the binarization of proposed algorithm in respect to results of the algorithms that use convolution masks in binarization were satisfactory compared to other algorithms in the literature.

2025, TRECVID

In this paper we describe the system designed by the ITU MSPR Group for content based video fingerprinting as applied to the TRECVID 2010 Content Based Copy Detection (CBCD) benchmark. This year focus of the system was on integration of audio and video fingerprinting to improve the robustness to attacks. The proposed system consists of three main modules: Audio/video fingerprint extraction, audio/video search and retrieval, and audiovisual decision fusion. We propose a video feature extraction scheme based on the Nonnegative Matrix Factorization (NMF) which is an efficient dimension reduction technique in video processing. Video fingerprint generation module takes the factorization matrices generated by NMF as its input and converts them to binary hashes by differencial coding . For audio data we perform an audio fingerprinting method that is similar to the one proposed in . Extracted audio and video hashes are indexed into a database. Searching module first applies a hash matching procedure to locate potential matching points both in audio and video. This is followed by decision fusion that eliminates false alarms and finalizes the matching and retrieval.

2025, 2015 10th International Conference on Information, Communications and Signal Processing (ICICS)

In this paper we evaluate user-equipment (UE) positioning performance of three cluster-based RF fingerprinting methods using LTE and WLAN signals. Real-life LTE and WLAN data were collected for the evaluation purpose using consumer cellular-mobile handset utilizing 'Nemo Handy' drive test software tool. Test results of cluster-based methods were compared to the conventional grid-based RF fingerprinting. The cluster-based methods do not require grid-cell layout and training signature formation as compared to the gridbased method. They utilize LTE cell-ID searching technique to reduce the search space for clustering operation. Thus UE position estimation is done in short time with less computational cost. Among the cluster-based methods Agglomerative Hierarchical Cluster based RF fingerprinting provided best positioning accuracy using a single LTE and six WLAN signal strengths. This method showed an improvement of 42.3 % and 39.8 % in the 68th percentile and 95th percentile of positioning error (PE) over the grid-based RF fingerprinting.

2025, 2015 International Conference on Location and GNSS (ICL-GNSS)

In this paper we propose a novel optimization algorithm for grid-based RF fingerprinting to improve user equipment (UE) positioning accuracy. For this purpose we have used Multi-objective Genetic Algorithm (MOGA) which enables autonomous calibration of gridcell layout (GCL) for better UE positioning as compared to that of the conventional fingerprinting approach. Performance evaluations were carried out using two different training data-sets consisting of Minimization of Drive Testing measurements obtained from a dynamic system simulation in a heterogeneous LTE small cell environment. The robustness of the proposed method has been tested analyzing positioning results from two different areas of interest. Optimization of GCL is performed in two ways: (1) array-wise calibration of the grid-cell units using non-overlapping GCL and (2) creating an overlapping GCL to cover of whole simulation area with different rectangular grid-cell units. Simulation results show that if sufficient amount of training data is available then the proposed method can improve positioning accuracy of 56.74% over the conventional grid- based RF fingerprinting.

2025, International Conference on Localization and GNSS 2014 (ICL-GNSS 2014)

This paper proposes a novel technique to enhance the performance of grid-based Radio Frequency (RF) fingerprint position estimation framework. First enhancement is an introduction of two overlapping grids of training signatures. As the second enhancement, the location of the testing signature is estimated to be a weighted geometric center of a set of nearest grid units whereas in a traditional grid-based RF fingerprinting only the center point of the nearest grid unit is used for determining the user location. By using the weighting-based location estimation, the accuracy of the location estimation can be improved. The performance evaluation of the enhanced RF fingerprinting algorithm was conducted by analyzing the positioning accuracy of the RF fingerprint signatures obtained from a dynamic system simulation in a heterogeneous LTE small cell environment. The performance evaluation indicates that if the interpolation is based on two nearest grid units, then a maximum of 18.8% improvement in positioning accuracy can be achieved over the conventional approach.

2025, 2013 First International Black Sea Conference on Communications and Networking (BlackSeaCom)

2025, 2008 Second International Conference on Electrical Engineering

A novel approach to determining unique fingerprint features with high repeatibility is described. The techniques described are particularly suitable for CE applications and devices employing inexpensive capacitative fingerprint sensors. The extraction of robust seeds for generating repeatable encryption keys is discussed and some preliminary approaches are described.

2025

Biometric authentication systems have emerged as a critical method of ensuring secure access control across various domains, from mobile phones to financial transactions. However, the systems are increasingly vulnerable to spoofing attacks, where imposter individuals attempt to deceive the biometric sensors using counterfeit biometrics, like images, 3D prints, or printed fingerprints. Spoofing attack development poses a significant threat to the security and reliability of biometric authentication systems. Current defense mechanisms are typically ineffective in providing realtime detection and adequate protection against sophisticated spoofing attacks. This research aims to fill the large gap in current biometric security systems using research into new detection and defense methods against spoofing attacks. The core focus is on designing advanced algorithms and machine learning models capable of detecting subtle but noticeable artifacts in biometric information that point to manipulation or forgery. Secondly, the research delves into multi-modal biometric systems that combine various biometric modalities (e.g., face recognition, fingerprint, and iris scanning) to enhance spoofing resilience. The research also delves into the integration of explainable AI practices such that detection models not only exhibit high accuracy but also provide interpretable and transparent results. This research aims to enhance the resistance of biometric systems to emerging spoofing methods with the innovations proposed, thereby offering a practical solution to a real problem for existing authentication technology. The results will help to make the security and reliability of biometric identification more robust in many sensitive sectors, including financial institutions, government security, and personal devices.

2025

In its final report, the 9/11 Commission concluded that funding and completing a "biometric entry-exit screening system" for travelers to and from the United States is essential to our national security. The commission noted that the United States has built the first phase of a biometric screening system known as US-VISIT, and recommended that the "patchwork" of other border screening systems be consolidated with US-VISIT to serve as the basis for a single system to streamline border inspections. This report provides an overview of biometric technologies and the major U.S. biometric border screening systems, including US-VISIT, and discusses issues such as cost, performance, and user acceptance. Based in part upon the commission's recommendations, Congress included biometric provisions related to entry/exit control in the Intelligence Reform and Terrorism Prevention Act of 2004 (P.L. 108-458). This topic will probably continue to be of interest to the 109 th Congress. This report will be updated as needed.

2025

With the introduction of the newest Automated Teller Machine (ATM) at Royal Bank of Scotland which operates without a card or authentication by entering Personal Identification Number (PIN) to withdraw cash up to £100, a more secured ATM can be designed and implemented with more secured feature of biometrics- facial recognition as PIN. Security is an indispensable issue in banking operations; with the advent of technology such as e-banking, mobile banking etc security has become an issue that needs utmost paramountcy. Principal Component Analysis (PCA) are employed in face recognition system, it seeks to capture the variations in a collection of face images and use them to encode and compare images of individual faces by using statistical dimensionality reduction method to produce the optimal linear squares decomposition of a training set and eigen faces. This research would afford the entire society more reliable ATM model and incidence of fraud which have decline the customer conf...

2025

In modern work environments, the need for efficient and automated systems to manage workspace and data has become increasingly vital. The project "Automated Workspace: Data and Resource Management Using IoT" aims to address this need by leveraging Raspberry Pi, MERN Stack Development, and RFID technology to create a streamlined and effective solution for attendance tracking resource and data management. Each employee is issued an RFID card, which serves as their unique identifier. The RFID cards are used to supply electricity to cabinets when scanned, ensuring controlled resource utilization. The primary functions of the system include logging entry and exit times, updating attendance status, updating leaves and maintaining an accurate count of attendance records and salary count. This automation significantly reduces the manual effort required for attendance, leave tracking, minimizing errors and enhancing accuracy. Raspberry Pi serves as the central processing unit, facilitating real-time interaction between the RFID reader, the web platform, and the data management components. The system leverages MongoDB for robust data storage, ensuring seamless and efficient management of employee records and resource data. A web-based platform allows employees to log in, apply for leave, and track their salary and attendance, while administrators can manage leave requests and oversee employee data. By automating key functions such as attendance tracking, resource management, and data storage, the system reduces manual effort, minimizes errors, and enhances operational efficiency, making it a valuable solution for modern workplaces.

2025, SGBIT

2025

Cryptography-biological authentications are mechanisms that attempt to identify users by combining unique features such as physical and behavioral characteristics. The old method which was based on passwords (e.g., public key, AES, etc.) can be easily discovered by attackers. In order to improve local security key, this paper presents a method that uses biological fingerprints and iris patterns to generate cryptographic keys. In this method, fingerprint and iris images are collected from the users and the security private key will be created by combining extracted patterns of iris and fingerprint and a hash function. The private key is used for cryptographic applications. Results showed that the model presented in this paper is more resistant against attacks compared with the patterns that are solely based on passwords.

2025, IEEE Transactions on Image Processing

2025

In this paper, the development of an attendance management system using biometrics is proposed. As the manual method of attendance system produced errors and taking lot of time during lecture period, an efficient and organized biometrics system for students' attendance is purposed. The electronic system not only used to take attendance for the students, but a database is also mentioned to store all the information which can be manipulated further in future. This biometric system, which is involved in the identification and verification of each individual student by scanning the characteristics of fingerprints. This type of verification is widely used in various aspects of life for different purposes, like in security, police identification, etc. In addition to this, once the students are registered, then respective parents and proctors are also being updated through the SMS generated by a GSM modem interfaced with the system and also an Android App is also developed to check the...

2025, IEEE Access

The diverse architectural evolution and intensive data explosion in the forthcoming 5G will have severe impacts on providing seamless and robust mobility management. In this paper, P-persistent energyaware handover (HO) decision strategies with mobility robustness are proposed both for intra-handover cases while a femto user equipment (FUE) roams into another femto access point (FAP) and for cross-tier handover cases while a macro user equipment (MUE)/FUE roams into/out of the FAP in a dynamic cell sizing involving macro-femto two-tier networks. To approximate the densely deployed small-cells, a unique RF fingerprint (RFF)-based localization is employed to enable efficient small-cell detection by an RFF matching mechanism. The prediction of the HO trigger is jointly determined by a P-persistent decision mechanism that formulates the specific HO behaviors when an MUE/FUE roams into (HO-in) and out of (HO-out) a femtocell in terms of the correlated coverage variance and UE trajectory features, whereas the target selection follows a utility function in consideration of the UE traveling time and the achievable throughput. The closed-form stationary probabilities of the proposed VHO/HHO decisions are analyzed by a Semi-Markov-based framework. In addition, an adjustable sensing mechanism with dynamic intervals is proposed when UE is located far from the RFF matching region, which can have a positive influence on reducing unnecessary UE energy consumption. Numerical results are presented for the decision accuracy analyses (too early, too late, and ping-pong HOs), energy-efficiency, and resource utilization of the two-tier system. The comprehensive evaluations indicate that the proposed scheme can enhance the mobility robustness and enable an optimal trade-off between the energy efficiency (EE) and system capacity while eliminating the architectural impacts caused by the dynamic topology and the dense deployment for the next-generation macro-femto two-tier networks. INDEX TERMS Horizontal and vertical handover, cell discovery, RF fingerprint, dynamic localization, energy-aware, RAT selection.

2025

With the rise of crimes in Automated Teller Machines, the security of the ATM is at stake. The Traditional Security Methods such as passwords or pins had always been a cause of worry to the users because of it getting lost, stolen or forgotten. The biometric authentication uses one's unique features as password. The paper deals with one of the oldest biometric traits, Fingerprint Recognition. The paper moreover adds a sophisticated voice input system and a Password Breaking scheme. The end results of a highly secure and sophisticated ATM system enhances the efficacy of the system, providing customer satisfaction in banking sectors.

2025, International Transactions on Artificial Intelligence (ITALIC)

A teacher attendance system utilizing fingerprints has been implemented at Ponpes Daarul Muttaqien II. However, fingerprint recognition errors frequently occur if the scanner is unclean. Teachers fill out an attendance update form for various reasons, including forgotten attendance, damaged fingerprints, and unnoticed absences. The Human Resources Bureau receives updates from around 28 instructors within one week. Statistics reveal that 30% of instructors update due to finger injuries preventing recognition, and 70% due to forgetting. Amid the COVID-19 pandemic, organizations advise remote work. Similarly, only specific sections, like technical and security units, require attendance at Ponpes Daarul Muttaqien II. Due to the potential risks of linking fingerprints to virus transmission, this study proposes a web-based attendance system. It employs the RESTful API approach, JWT Security, and the Haversine Formula Algorithm. The system mandates employees to be within 100 meters of a designated coordinate point for attendance. The system tracks attendance status, arrival and delay times, and absence status. Future enhancements might involve facial recognition for more robust validation. In conclusion, this innovative approach addresses attendance challenges, offering adaptability, security, and potential fraud prevention.

2025, Proceedings of SPIE

Sensor fingerprint is a unique noise-like pattern caused by slightly varying pixel dimensions and inhomogeneity of the silicon wafer from which the sensor is made. The fingerprint can be used to prove that an image came from a specific digital camera. The presence of a camera fingerprint in an image is usually established using a detector that evaluates cross-correlation between the fingerprint and image noise. The complexity of the detector is thus proportional to the number of pixels in the image. Although computing the detector statistic for a few megapixel image takes several seconds on a single-processor PC, the processing time becomes impractically large if a sizeable database of camera fingerprints needs to be searched through. In this paper, we present a fast searching algorithm that utilizes special "fingerprint digests" and sparse data structures to address several tasks that forensic analysts will find useful when deploying camera identification from fingerprints in practice. In particular, we develop fast algorithms for finding if a given fingerprint already resides in the database and for determining whether a given image was taken by a camera whose fingerprint is in the database.

2025, IJSREM

This solution not only provides transparency, it frees up administrative processes through automation. This product eliminates impersonation, improves timeliness, and provides a computerized attendance record. Due to its modularity, this solution is also easy to connect to a cloud platform and mobile apps. By replacing old fashion logins, it also provides a safe and easy user experience. This is the major milestone we have taken toward digitization of education.