scholarly journals Decision Fusion based Person Identification System using Fingerprints and Facial Image with Template Matching

2018 ◽  
Vol 6 (3) ◽  
Author(s):  
A. K. M. Akhtar Hossain
Keyword(s):  
Face Recognition ◽  
Response Time ◽  
Template Matching ◽  
Recognition System ◽  
Decision Fusion ◽  
Fingerprint Recognition ◽  
Identification System ◽  
Prototype System ◽  
Recognition Systems ◽  
Fusion Scheme

In this research, it has been developed a prototype biometric system which integrates facial images and fingerprints. The system overcomes the limitations of face recognition systems as well as fingerprint recognition systems. The integrated prototype system operates in the identification mode with an admissible response time. The identity established by the system is more reliable than the identity established by a face recognition system. In addition, the proposed decision fusion scheme enables performance improvement by integrating multiple features with different confidence measures. Experimental results demonstrate that the system performs  well. It meet up the response time as well as the accuracy requirements.

scholarly journals Face Recognition by Reconstructing A 2.5 D Face using Photometric Stereo

2020 ◽  
Vol 9 (7) ◽  
pp. 944-949
Keyword(s):  
Face Recognition ◽  
Low Cost ◽  
Three Dimensional ◽  
Recognition System ◽  
Photometric Stereo ◽  
Identification System ◽  
2D Systems ◽  
3D Face Recognition ◽  
3D Face ◽  
Recognition Systems

Face recognition is an important application of image analysis and it has received a lot of interest in the last decade. There is a critical need for a reliable identification system. As of now, face recognition is not reliable enough in the majority of security applications, therefore a low cost, accurate, and viable identification method are required for face recognition. Two dimensional (2D) face recognition systems that are already existing are often not reliable. Three dimensional (3D) face recognition systems produce more accurate and robust than 2D systems but they are very costly due to large scanning and coded light and also consume a lot of time in the recognition process. This paper aims to produce a low-cost 3D face recognition system (2.5D) using photometric stereo which is less explored in face recognition systems. The capabilities of photometric stereo for use in face recognition are evaluated using a number of experiments conducted using the photometric stereo system and it is implemented and shown to be better than our traditional 2D systems. This system is aimed to solve a number of issues we see in face recognition systems like illumination, distance from the camera and pose and thus, it could be a useful application for biometric authentications in homes, governmental organizations and financial institutions

scholarly journals Spectral Minutiae Fingerprint Recognition System

2014 ◽  
pp. 103-108
Author(s):  
S. Shanawaz Basha ◽  
N. Musrat Sultana
Keyword(s):  
Large Scale ◽  
Reduction Rate ◽  
Principal Component ◽  
Rejection Rate ◽  
Recognition System ◽  
Feature Reduction ◽  
Fingerprint Recognition ◽  
Identification System ◽  
Behavioral Characteristics ◽  
Template Size

Biometrics refers to the automatic recognition of individuals based on their physiological and/or behavioral characteristics, such as faces, finger prints, iris, and gait. In this paper, we focus on the application of finger print recognition system. The spectral minutiae fingerprint recognition is a method to represent a minutiae set as a fixedlength feature vector, which is invariant to translation, and in which rotation and scaling become translations, so that they can be easily compensated for. Based on the spectral minutiae features, this paper introduces two feature reduction algorithms: the Column Principal Component Analysis and the Line Discrete Fourier Transform feature reductions, which can efficiently compress the template size with a reduction rate of 94%.With reduced features, we can also achieve a fast minutiae-based matching algorithm. This paper presents the performance of the spectral minutiae fingerprint recognition system, this fast operation renders our system suitable for a large-scale fingerprint identification system, thus significantly reducing the time to perform matching, especially in systems like, police patrolling, airports etc,. The spectral minutiae representation system tends to significantly reduce the false acceptance rate with a marginal increase in the false rejection rate.

scholarly journals A multimodal biometric identification system based on cascade advanced of fingerprint, fingervein and face images

2020 ◽  
Vol 17 (3) ◽  
pp. 1562
Author(s):  
El mehdi Cherrat ◽  
Rachid Alaoui ◽  
Hassane Bouzahir
Keyword(s):  
Gabor Filter ◽  
Regression Line ◽  
Histogram Equalization ◽  
Recognition System ◽  
Fingerprint Recognition ◽  
Identification System ◽  
Fusion Algorithm ◽  
Decision Level ◽  
Face Images ◽  
Level Method

<p>In this paper, we present a multimodal biometric recognition system that combines fingerprint, fingervein and face images based on cascade advanced and decision level fusion. First, in fingerprint recognition system, the images are enhanced using gabor filter, binarized and passed to thinning method. Then, the minutiae points are extracted to identify that an individual is genuine or impostor. In fingervein recognition system, image processing is required using Linear Regression Line, Canny and local histogram equalization technique to improve better the quality of images. Next, the features are obtained using Histogram of Oriented Gradient (HOG). Moreover, the Convolutional Neural Networks (CNN) and the Local Binary Pattern (LBP) are applied to detect and extract the features of the face images, respectively. In addition, we proposed three different modes in our work. At the first, the person is identified when the recognition system of one single biometric modality is matched. At the second, the fusion is achieved at cascade decision level method based on AND rule when the recognition system of both biometric traits is validated. At the last mode, the fusion is accomplished at decision level method based on AND rule using three types of biometric. The simulation results have demonstrated that the proposed fusion algorithm increases the accuracy to 99,43% than the other system based on unimodal or bimodal characteristics.</p>

Application of Fingerprint-Matching Algorithm in Smart Gun Using Touch-Less Fingerprint Recognition System

2020 ◽  
pp. 122-128
Author(s):  
Saifullah Khalid
Keyword(s):  
Recognition System ◽  
Fingerprint Recognition ◽  
Fingerprint Matching ◽  
Fingerprint Image ◽  
Matching Algorithm ◽  
Latent Fingerprint ◽  
Recognition Systems

Fingerprint recognition systems are widely used in the field of biometrics. Many existing fingerprint sensors acquire fingerprint images as the user's fingerprint is contacted on a solid flat sensor. Because of this contact, input images from the same finger can be quite different and there are latent fingerprint issues that can lead to forgery and hygienic problems. For these reasons, a touchless fingerprint recognition system has been investigated, in which a fingerprint image can be captured without contact. While this system can solve the problems which arise through contact of the user's finger, other challenges emerge.

A survey of liveness detection methods for face biometric systems

Sensor Review ◽  
2017 ◽  
Vol 37 (3) ◽  
pp. 346-356 ◽  
Author(s):  
Yang Xin ◽  
Yi Liu ◽  
Zhi Liu ◽  
Xuemei Zhu ◽  
Lingshuang Kong ◽  
...  
Keyword(s):  
Face Recognition ◽  
Future Development ◽  
Recognition System ◽  
Fingerprint Recognition ◽  
Detection Methods ◽  
Content Type ◽  
Liveness Detection ◽  
Biometric Systems ◽  
The Future ◽  
Face Biometric

Purpose Biometric systems are widely used for face recognition. They have rapidly developed in recent years. Compared with other approaches, such as fingerprint recognition, handwriting verification and retinal and iris scanning, face recognition is more straightforward, user friendly and extensively used. The aforementioned approaches, including face recognition, are vulnerable to malicious attacks by impostors; in such cases, face liveness detection comes in handy to ensure both accuracy and robustness. Liveness is an important feature that reflects physiological signs and differentiates artificial from real biometric traits. This paper aims to provide a simple path for the future development of more robust and accurate liveness detection approaches. Design/methodology/approach This paper discusses about introduction to the face biometric system, liveness detection in face recognition system and comparisons between the different discussed works of existing measures. Originality/value This paper presents an overview, comparison and discussion of proposed face liveness detection methods to provide a reference for the future development of more robust and accurate liveness detection approaches.

scholarly journals Formal Implementation of a Performance Evaluation Model for the Face Recognition System

2008 ◽  
Vol 2008 ◽  
pp. 1-10 ◽  
Author(s):  
Yong-Nyuo Shin ◽  
Jason Kim ◽  
Yong-Jun Lee ◽  
Woochang Shin ◽  
Jin-Young Choi
Keyword(s):  
Performance Evaluation ◽  
Face Recognition ◽  
Evaluation System ◽  
Performance Test ◽  
Evaluation Model ◽  
Recognition System ◽  
Performance Evaluation Model ◽  
Face Recognition System ◽  
Recognition Systems ◽  
A Performance

Due to usability features, practical applications, and its lack of intrusiveness, face recognition technology, based on information, derived from individuals' facial features, has been attracting considerable attention recently. Reported recognition rates of commercialized face recognition systems cannot be admitted as official recognition rates, as they are based on assumptions that are beneficial to the specific system and face database. Therefore, performance evaluation methods and tools are necessary to objectively measure the accuracy and performance of any face recognition system. In this paper, we propose and formalize a performance evaluation model for the biometric recognition system, implementing an evaluation tool for face recognition systems based on the proposed model. Furthermore, we performed evaluations objectively by providing guidelines for the design and implementation of a performance evaluation system, formalizing the performance test process.

scholarly journals Performance Improvement of Face Recognition System using Selective Local Feature Vectors

2013 ◽  
Vol 10 (2) ◽  
pp. 1330-1338
Author(s):  
Vasudha S ◽  
Neelamma K. Patil ◽  
Dr. Lokesh R. Boregowda
Keyword(s):  
Face Recognition ◽  
Performance Improvement ◽  
Recognition Rate ◽  
Recognition System ◽  
Image Splicing ◽  
Feature Vectors ◽  
Face Recognition System ◽  
Prime Concern ◽  
Wide Range ◽  
Recognition Systems

Face recognition is one of the important applications of image processing and it has gained significant attention in wide range of law enforcement areas in which security is of prime concern. Although the existing automated machine recognition systems have certain level of maturity but their accomplishments are limited due to real time challenges. Face recognition systems are impressively sensitive to appearance variations due to lighting, expression and aging. The major metric in modeling the performance of a face recognition system is its accuracy of recognition. This paper proposes a novel method which improves the recognition accuracy as well as avoids face datasets being tampered through image splicing techniques. Proposed method uses a non-statistical procedure which avoids training step for face samples thereby avoiding generalizability problem which is caused due to statistical learning procedure. This proposed method performs well with images with partial occlusion and images with lighting variations as the local patch of the face is divided into several different patches. The performance improvement is shown considerably high in terms of recognition rate and storage space by storing train images in compressed domain and selecting significant features from superset of feature vectors for actual recognition.

scholarly journals Individual identification of Japanese macaques (Macaca fuscata) using a face recognition system and a limited number of learning images

2020 ◽  
Author(s):  
Yosuke Otani ◽  
Hitoshi Ogawa
Keyword(s):  
Face Recognition ◽  
Macaca Fuscata ◽  
Field Research ◽  
Recognition System ◽  
Japanese Macaques ◽  
Individual Identification ◽  
System Construction ◽  
Face Recognition System ◽  
Recognition Systems ◽  
High Degree

AbstractIndividual identification is an important technique in animal research that requires researcher training and specialized skillsets. Face recognition systems using artificial intelligence (AI) deep learning have been put into practical use to identify in humans and animals, but a large number of annotated learning images are required for system construction. In wildlife research cases, it is difficult to prepare a large amount of learning images, which may be why systems using AI have not been widely used in field research. To investigate the development of a system that identifies individuals using a small number of learning images, we constructed a system to identify individual Japanese macaques (Macaca fuscata yakui) with a low error rate from an average of 20 images per individual. The characteristics of this system were augmentation of data, simultaneous determination by four individual identification models and identification from a majority of five frames to ensure reliability. This technology has a high degree of utility for various stakeholders and it is expected that it will advance the development of individual identification systems by AI that can be widely used in field research.

scholarly journals Real-Time Attendance and Feedback System

2021 ◽  
pp. 1135-1139
Author(s):  
Piyush Manish Sonar ◽  
Aniket Nitin Chaudhari ◽  
Mehul Deepak Sethi ◽  
Tejaswini Sanjay Gadakh
Keyword(s):  
Face Recognition ◽  
Principal Component ◽  
Feedback System ◽  
Recognition System ◽  
Fingerprint Recognition ◽  
Student Attendance ◽  
Feedback Form ◽  
Face Recognition System ◽  
User Friendly ◽  
Facial Images

Face is the representation of one’s identity. Hence, we have proposed an automated student attendance system based on face recognition. Face recognition system is very useful in life applications especially for attendance system. In our proposed approach, firstly, video framing is performed by activating the camera through a user-friendly interface. In the pre-processing stage, scaling of the size of images is performed, if necessary, in order to prevent loss of information. In face recognition stage, enhanced local binary pattern (LBP) and principal component analysis (PCA) is applied correspondingly in order to extract the features from facial images. Another way of marking the attendance is fingerprint recognition. To mark the attendance students simply have to give the fingerprint impression in fingerprint scanner module. Finally, the attendance of the recognized student will be marked and saved in the excel file. The student who is not registered will also be able to register on the spot and notification will be given if students sign in more than once. Whenever seminar is completed then a link is sent on email. It includes the information in terms of feedback. When student fills the feedback form then analysis of overall session is done.

scholarly journals Railway Access Control System using Face Recognition

2020 ◽  
Vol 9 (3) ◽  
pp. 444-448
Keyword(s):  
Face Recognition ◽  
Recognition System ◽  
Modern World ◽  
Qr Code ◽  
Quick Response ◽  
Code System ◽  
Railway Station ◽  
Face Recognition System ◽  
Access Control System ◽  
Recognition Systems

Nowadays booking tickets and getting inside a railway station is adifficult task. Manual checking becomes a burden and time consuming. Also as everything is getting digitized in this modern world introduce face recognition and Quick Response (QR) code system for entry helps in passenger convenience.Face recognition is a method of identifying or verifying the identity of an individual using their face. Face recognition systems can be used to identify people in photos, video, or in real-time.So this system focuses on passengers’ convenience through allowing them to book tickets online and by introducing face recognition system and QR code system for entry to a railway station.This system helps inidentifying people who try to travel without buying tickets and also helps toapprehend the blacklisted person which increases security in the railway station. Online booking is one of the convenient ways tobook the ticket. This system also provides the convenience to passenger by issuing the digital ticket in the form of QR code thus avoiding any fuss due to the loss of the physical ticket.

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