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

In this project, an attempt has been made to the development of an authenticated electronic voting system using fingerprint and facial images. The two-fold authentication system improves the security of the voting process and reduces the chances of a corrupt election process. The facial recognition process utilizes the Local Binary Pattern Histogram and Support Vector Machine process to scan, store and recognize faces efficiently. The fingerprint recognition involves the capturing of multiple 2D images and High Sensitive Pixel Amplifier to improve the quality of those images to scan the fingerprint to provide the primary form of authentication. Visual Basic is used to develop a very easy to use User Interface that enables an easy voting process. A private server is used to store both the user data and the election results separately. This reduces the chances of external manipulation of the election results.

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- Computer Science, Artificial Intelligence, Biometrics, Fingerprint Recognition
- by Luca Cazzanti
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- Mechanical Engineering, Signal Processing, Content Management, Search Engines

Internet of Things (IoT) and services is an interesting topic with a wide range of potential applications like smart home systems, health care, telemedicine, and intelligent transportation. Traditionally, key agreement schemes have been evaluated to access IoT services which are highly susceptible to security. Recently, Biometric-based authentication is also used to access IoT services and devices. They are involving a larger amount of memory with increased running time and found to be computationally infeasible. To provide robust authentication for IoT services, Histogram of Neighborhood Tripartite Authentication with Fingerprint Biometrics (HNTA-FB) for IoT services is proposed in this paper. This proposed HNTA-FB method uses binary patterns and a histogram of features to extract the region of interest. To reduce the memory requirements while providing access to IoT services, Histogram of Neighborhood Binary Pattern Pre-processing (HNBPP) model is proposed. The discriminative power of Neighbourhood Binary Pattern Registration (NBPR) is integrated with the normalized sparse representation based on the histogram. Additionally, this work presents a new Tripartite User Authentication model for fingerprint biometric template matching process. When compared with different state-of-the-art methods, the proposed method depicts significantly improved performance in terms of matching accuracy, computational overhead and execution speed and is highly effective in delivering smart home services.

An access control system by fingerprints is one of the most widely spread biometric techniques linked with ensuring the security of the enterprise. The uniqueness of fingerprints is something staying unchanged during the whole life. For example, such features as the face shape, manner of walking may change over time time but fingerprints will not. However, the fingerprint itself can give an image of a bad quality because of the state of the skin, bad impression, dirty surface of the finger, etc. That's why, the methods for image enhancement should be implemented to get more accurate results. This study discusses reliable techniques and propose a reliable algorithm of the fingerprint image enhancement for the access control system to be applied as a part of the security system in the company.

- by Valentyn N Sichkar
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- Image Processing, Gabor filters, Optical Sensors, Fingerprint Recognition
- by Reaz Ahmed
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- Computer Science, Resilience, Protocols, Mathematical Analysis
- by erdinc kocer
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- Signal Processing, Pattern Recognition, Biometrics, Proceedings
- by Amr Abdel-Hamid
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- Engineering, Computer Science, Law, Intellectual Property

After collecting a data base of fingerprint images, we design a neural network algorithm for fingerprint recognition. When presented with a pair of fingerprint images, the algorithm outputs an estimate of the probability that the two images originate from the same finger. In one experiment, the neural network is trained using a few hundred pairs of images and its performance is subsequently tested using several thousand pairs of images originated from a subset of the database corresponding to 20 individuals. The error rate currently achieved is less than 0.5%. Additional results, extensions, and possible applications are also briefly discussed.

- by Pierre Baldi
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- Neural Network, Multidisciplinary, Segmentation, Bit Error Rate

The main objective of this project is to enable safe and secure voting system and is to avoid misconceptions which take place in election period. Voting System helps to choose their government and also the political representatives. It also ensures that to avoid fake and repeated vote during election. In this project the finger print is given as input. All the database of the voter include their finger print, photo, mobile number etc has been stored in the MATLAB. If the finger print enrolled by the voter should be matched with the database, It enables the voter to enroll his/her vote. If the finger print doesn’t match the system will lock the process. The important is that the voter can enroll their vote at their desire location. And also the number of vote enrolled should be updated in the database administration unit every time after voting is done. The smart voting system will enhance better accuracy and high speed process. Through this voting system the disadvantages which are in the electronic voting system should be overcome.

- by Jiankun Hu
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- Algorithms, Artificial Intelligence, Biometrics, Biometry
- by Giuseppe Messina
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- Algorithms, Image Processing, Computational Complexity, Digital Photography
- by Johannes Ueberberg
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- Digital imaging, Digital Watermarking, Spread Spectrum, Digital Fingerprinting
- by Jiankun Hu
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- Engineering, Set Theory, Mesh generation, Topology
- by Xudong Jiang
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- Signal Processing, Feature Extraction, Adaptive Filters, Fingerprint Recognition

Biometrics represents a return to a traditional way of identifying someone relying on what that person is instead of what that person knows or owns. Even though the significant amount of research that has been done in this field, there is still much to do as new emerging scenarios of application appear everyday. Biometric recognition systems are no longer restricted to forensic investigation or control management of employees. They have been gaining a visibility and applicability in daily use devices which reinforces their usability in all aspects of our day to day life. With this spread of biometric applications, nowadays commonly found in our laptops, our smart phones, some bank management services and airport custom services, a necessity for improved security also is rising. The importance of protecting our identity and our data has become crucial as our devices are filled with sensible information of many kinds. Therefore the presentation attack or liveness detection methods as ...

- by Ana F. Sequeira
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- Engineering, Biometrics, Biometrics - Iris Recognition, Fingerprint Recognition

Automatic Fingerprint authentication for personal identification and verification has received considerable attention over the past decades among various biometric techniques because of the distinctiveness and persistence properties of fingerprints. Now fingerprints are set to explode in popularity as they are being used to secure smart phones and to authorize payments in online stores. The main objective of this paper is to review the extensive research work that has been done over the past decade and discuss the various approaches proposed for fingerprint matching. The proposed methods were based on 2D correlation in the spatial and frequency domains, Artificial Neural Networks, Hough transform, Fourier transform, graphs, local texture, ridge geometry etc. All these different techniques have their pros and cons. This paper also provides the performance comparison of several existing methods proposed by researchers in fingerprint matching.

- by Shoba Leslie
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- Computer Science, Algorithms, Computer Graphics, Artificial Intelligence
- by eren camlikaya
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- Biometrics, Databases, Man, Fingerprint

To enhance low-quality fingerprint images, we present a novel method that first estimates the local orientation of the
fingerprint ridge and valley flow and next performs oriented diffusion filtering, followed by a locally adaptive contrast
enhancement step. By applying the authors’ new approach to low-quality images of the FVC2004 fingerprint databases, the
authors are able to show its competitiveness with other state-of-the-art enhancement methods for fingerprints like curved
Gabor filtering. A major advantage of oriented diffusion filtering over those is its computational efficiency. Combining
oriented diffusion filtering with curved Gabor filters led to additional improvements and, to the best of the authors’
knowledge, the lowest equal error rates achieved so far using MINDTCT and BOZORTH3 on the FVC2004 databases. The
recognition performance and the computational efficiency of the method suggest to include oriented diffusion filtering as a
standard image enhancement add-on module for real-time fingerprint recognition systems. In order to facilitate the
reproduction of these results, an implementation of the oriented diffusion filtering for Matlab and GNU Octave is made
available for download.

- by dario maio and +1
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- Information Systems, Algorithms, Artificial Intelligence, Biometrics

This research work has application for attendance system of employer's and students in general. The system will facilitate institutions/ organization to make attendance individual in time along with data information thumb impression will be taken as a signature for the system entry. Main design and challenge in this system is the design of database architecture and its business logic.

- by Imran Anwar Ujan
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- Biomedical Imaging, Feature Extraction, Fingerprint Recognition
- by Vincenzo Piuri
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- Image Registration, Fingerprint Recognition, Image Sensors
- by David Molnar
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- Privacy, Biometrics, Security and Privacy, Authentication

The increased development of IT tools and social communication networks has significantly increased the need for people to be identified with reliable and secure tools hence the importance of using biometric technology. Biometrics is an emerging field where technology improves our ability to identify a person. The advantage of biometric identification is that each individual has its own physical characteristics that cannot be changed, lost or stolen. The use of fingerprinting is today one of the most reliable technologies on the market to authenticate an individual. This technology is simple to use and easy to implement. The techniques of fingerprint recognition are numerous and diversified, they are generally based on generic algorithms and tools for filtering images. This article proposes a fingerprint recognition chain by highlighting improved processing tools to facilitate data retrieval. The results are retrieved and validated using Matlab.

Eye tracking and behavioral methods were used to assess the effects of fatigue on performance in latent print examiners. Eye gaze was measured both before and after a fatiguing exercise involving fine-grained examination decisions. The eye tracking tasks used similar images, often laterally reversed versions of
previously viewed prints, which holds image detail constant while minimizing prior recognition. These methods, as well as a within-subject design with fine grained analyses of the eye gaze data, allow fairly strong conclusions despite a relatively small subject population. Consistent with the effects of fatigue on
practitioners in other fields such as radiology, behavioral performance declined with fatigue, and the eye gaze statistics suggested a smaller working memory capacity. Participants also terminated the search/examination process sooner when fatigued. However, fatigue did not produce changes in inter-examiner consistency as measured by the Earth Mover Metric. Implications for practice are discussed.

- by Brandi Emerick and +1
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- Eye tracking, Fatigue, Perceptual expertise, Fingerprint Recognition

ARTICLE INFO Detection of the Distorted Fingerprints major causes to non-match in fingerprint at time matching fingerprint sample. This problem causes all the recognition of fingerprint algorithm application. It is complicated in negative type matching application. That means watch list and duplication application. In such way criminal user porpusly hide his fingerprint identification. In this paper we use the K-means, Canny-edge algorithm to detect and rectify distorted fingerprint image. Distortion and rectification is view as a regression problem where user input skein distorted fingerprint output is distortion field. To solve this problem K-means & Canny-edge fingerprint algorithm is use.

- by Shivkumar Shete
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- Information Systems, Engineering, Principal Component Analysis, Matlab

This paper presents comparison concerning various biometric systems simply by defining their advantages and disadvantages. A brief introduction is usually offered regarding commonly used biometrics, including, Face, Iris, Fingerprint, Finger Vein, Lips, Voice. The comparison criteria list introduced is restricted to accuracy, size of template, cost, security level, and long term stability.

Most of existing audio fingerprinting systems have limitations to be used for high-specific audio retrieval at scale. In this work, we generate a low-dimensional representation from a short unit segment of audio, and couple this fingerprint with a fast maximum inner-product search. To this end, we present a contrastive learning framework that derives from the segment-level search objective. Each update in training uses a batch consisting of a set of pseudo labels, randomly selected original samples, and their augmented replicas. These replicas can simulate the degrading effects on original audio signals by applying small time offsets and various types of distortions, such as background noise and room/microphone impulse responses. In the segment-level search task, where the conventional audio fingerprinting systems used to fail, our system using 10x smaller storage has shown promising results. Our code and dataset will be available.

- by Sungkyun Chang
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- Information Retrieval, Machine Learning, Database Systems, Audio Signal Processing

Overlapped fingerprints occur due to multiple impressions of fingerprints on the same object at same place. This is natural in uncontrolled environments, or they are the residual fingerprints left over on fingerprints scanner. Overlapped fingerprints need to be separated into individual fingerprints for recognition. Separation of overlapped fingerprints involves steps, segmentation of image regions, feature extraction and classification. State of the art algorithms for separation of overlapped fingerprints adopts region wise processing approach to feature extraction. Therefore segmentation of overlapped region is an essential step for robust feature extraction. This paper presents a new algorithm for segmentation of overlapped region using time series two dimensional Autoregressive (2D AR) model. AR model parameters are estimated using Least Squares (LS) method which ensures minimum mean square error. The performance of the algorithm is evaluated using a standard database of 100 overlapped fingerprints images. The results are compared with ground truth results and are found satisfactory. Segmentation accuracy achieved is between 80% to 90%.

- by Shoba Leslie
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- Computer Science, Algorithms, Computer Graphics, Artificial Intelligence
- by Shoba Leslie
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- Computer Science, Algorithms, Computer Graphics, Artificial Intelligence

- by Sungkyun Chang
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- Engineering, Computer Science, Information Retrieval, Machine Learning
- by mehdi salehi
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- Computer Science, Computer Graphics, Computer Vision, Pattern Recognition

The increase in use of automated fingerprint recognition puts on it a challenge of processing a diverse range of fingerprints. To make it supportive in consisting fingerprint detail extraction, quality control is required, which is used in identification/verification. Fingerprint verification is one of the most reliable personal identification methods and it plays a very important role in forensic applications like criminal investigations, terrorist identification and National security issues. Some fingerprint identification algorithm (such as using Fast Fourier Transform (FFT), Minutiae Extraction) may require so much computation as to be impractical. Because quality of fingerprints varies according to the user population’s ages and fingerprint quality has an impact on overall system performance, it is important to understand the significance of fingerprint samples from different age groups.
Keywords— Minutia, cross-correlation, Otsu’s binarization, FFT.

- by IJAERS Journal
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- Fingerprint Recognition

This paper presents a novel approach for deciding on the appropriateness or not of an acquired fingerprint image into a given database. The process begins with the assembly of a training base in an image space constructed by combining Principal Component Analysis (PCA) and edge detection. Then, the parameter value (H) – a new feature that helps in the decision making about the relevance of a fingerprint image in databases – is derived from a relationship between Euclidean and Mahalanobian distances. This procedure ends with the lifting of the curve of the Receiver Operating Characteristic (ROC), where the thresholds defined on the parameter H are chosen according to the acceptable rates of false positives and false negatives.

- by Ernande Ernande_Melo and +2
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- Telecommunications Engineering, Image Processing, Signal Processing, Principal Component Analysis

Fingerprint biometrics provides identity verification with a strong degree of confidence over past few
decades. Present work focuses on special branch of fingerprint recognition namely, touch-less fingerprint recognition
which has fundamental advantage in terms of better hygiene, safety and latent fingerprints over traditional touch-based
systems. Such systems find applications in numerous fields such as secure access to laptops and computer systems,
cellular phones, banking, ATMs etc. Although lot of work have been done on touch-less fingerprint recognition
systems, still people are looking for more accuracy. The proposed touch-less fingerprint recognition system opt digital
camera as the device to acquire the fingerprint image and it consists of three main steps: Pre-processing, Feature
extraction and Verification. Current work presents a comparative performance evaluation of two widely used
classifiers: Support Vector Machine (SVM) and Gaussian Mixture Model (GMM). Experimental results illustrates that
GMM shows slightly better accuracy than SVM.

Exploring the misguided CSI effect and examining how famous miscarriages of justice have affected fingerprint analysis in the UK.

- by dario maio
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- Information Systems, Algorithms, Artificial Intelligence, Photography
- by Kawser Nafi
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- Fingerprint Recognition, Computer Applications, Minutiae Extraction
- by Maya Halaseh
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- RFID Technology, Fingerprint Recognition, Biometric Identification

The security of biometric fingerprint is a big challenge now-a-days, as it has worldwide acceptance. Compromised fingerprint templates may raise terrible threats to its owner. Because of the vulnerabilities of fingerprint authentication system, security issues about fingerprint have been a matter of great concern. This study summarizes the vulnerabilities of fingerprint authentication system and highlights the type of securities available against those challenges. It includes much classified knowledge about security of fingerprint template. This work is an endeavor to provide a compact knowledge to the research community about the security issues regarding fingerprint authentication system.

Türkiye’de eğitim alan genç nesilin çokluğu ve sınıfların doluluğu nedeniyle sınıflarda yoklamanın alınması oldukça uzun sürebilmektedir. Ayrıca yoklamalar öğrenciler tarafından manipüle de edilebilmektedir. Her ne kadar eğitimciler yoklama için farklı yöntemler geliştirse de özellikle zaman konusunda kısıtlamalar olabilmekte ve öğrencilerin dikkatini toplamak zorlaşabilmektedir.
Bu proje tasarımının amacı, yoklamada yaşanan düzensizlikleri ve zaman kayıplarını en aza indirgeyerek yüksek doğrulukta bir otomatik yoklama sistemi geliştirmektir. Bunu sağlamak için yoklamada, güvenilir ve çağdaş olması için parmak izi okuyucu sisteminin kullanılmasının uygun olduğu değerlendirilmiştir.
Biyometrik parmak izi sisteminin kullanılması sayesinde imza kâğıdı veya yoklama listesinin yerine yoklama kayıtları elektronik ortamda online olarak kaydedilebilecektir. Bu özellik tasarladığımız projenin en özgün yönüdür. Ayrıca, klasik sistemde alınan yoklama, dersin ardından teker teker sisteme girilmektedir. Ancak, tasarladığımız proje sayesinde, otomatik olarak alınacak yoklama direk olarak mail adresine yönlendirilecek veya ana bilgisayarda tutulabilecektir. Bu sistem sayesinde hızlı, güvenilir ve kolay bir şekilde yoklama alınması sağlanacaktır.

- by Lukasz Wieclaw
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- Fingerprint Recognition

The university system in the Kingdom of Saudi Arabia is concerned with student attendance for lectures, and it is the responsibility of lecturers to monitor student attendance for each lecture. By the end of the semester, students get an attendance register indicating which lectures the student has attended and it reports the calculated percentage for each student's attendance in each course. Universities have regulated the mechanisms and the acceptable percentages of student absence. The process for a lecturer to manually check student attendance consumes a lot of time and effort, either during the lecture or when in the process of emptying absenteeism and inserting it into the university's electronic system. Therefore, Saudi universities compete to find modern methods of checking student attendance that will avoid the disadvantages of manually taking attendance. For this reason, they have produced electronic attendance systems, for example, using a student's fingerprint, an eye recognition system, or a mobile phone system to read a QR code designed for the same purpose. All of these systems have the disadvantage that they consume a lot of time, as all students have to line up at the fingerprint reader or the eye detector for identification. Therefore, the problem of the consumption of lecture time is still present, even with these modern systems. Therefore, the aim of this research is to propose a smart mobile application that is able to check the attendance of students without having to consume lecture time or require any effort from the lecturer. The system automatically recognizes the attendance of students through their university ID cards. Each lecturer would use his/ her own mobile phone to use the proposed system to check the attendance of students instead of using manual method to register the attendance of students and the students' ID cards that are detected by coming within range of the lecturer reader would represent present students, and missing student ID cards represent absent students