scholarly journals A Dual Security Scheme Based on DWT for Personnel Authentication

2019 ◽  
Vol 9 (1) ◽  
pp. 598-602
Keyword(s):  
Rejection Rate ◽  
Recognition System ◽  
Fingerprint Recognition ◽  
Identification System ◽  
Discrete Wavelet ◽  
Number Systems ◽  
Biometric Systems ◽  
The Face ◽  
Authentication System ◽  
Facial Recognition System

A biometric identification system that audits the presence of a person using real or behavioral features is safer than passwords and number systems. Present applications are mostly recognize an individual using the single modal biometric system. However, a single characteristic sometimes fails to authenticate accurately. Multimodal biometric technologies solve the problems that exist in the single biometric systems. It is very hard to identify images with low lighting environments using facial recognition system. By utilizing fingerprint recognition, this issue can be better addressed. This paper presents a dual personnel authentication system that incorporates face and fingerprint to improve security. For face identification, the Discrete Wavelet Transform (DWT) algorithm is used to acquire features from the face and fingerprint pictures. The technique used to integrate fingerprint and face is decision level fusion. By adding fingerprint recognition to the scheme, the proposed algorithm decreases the false rejection rate (FRR) in the face and fingerprint recognition and hence increases the accuracy of the authentication.

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 Study on Machine Learning Approach for Fingerprint Recognition System

2019 ◽  
Vol 5 (11) ◽  
Author(s):  
Aayushi Tamrakar ◽  
Neetesh Gupta
Keyword(s):  
Rejection Rate ◽  
Recognition System ◽  
Extraction Methods ◽  
Acceptance Rate ◽  
Fingerprint Recognition ◽  
Fingerprint Classification ◽  
Machine Learning Approach ◽  
Optimum Approach ◽  
Authentication System ◽  
Recognition Technique

A biometric system is an evolving technology that is used in various fields like forensics, secured area and security system. Authentication system like fingerprint recognition is most commonly used biometric authentication system. Fingerprint method of identification is the oldest and widely used method of authentication used in biometrics. There are several reasons like displacement of finger during scanning, environmental conditions, behavior of user, etc., which causes the reduction in acceptance rate during fingerprint recognition. The result and accuracy of fingerprint recognition depends on the presence of valid minutiae. Fingerprint Recognition system designed uses various techniques in order to reduce the False Acceptance Rate (FAR) and False Rejection Rate (FRR) and to enhance the performance of the system. This paper reviews the fingerprint classification including feature extraction methods and learning models for proper classification to label different fingerprints. A comparative study of different recognition technique along with their limitations is also summarized and optimum approach is proposed which may enhance the performance of the system.

scholarly journals DATABASE MANAGEMENT FOR FACIAL RECOGNITION SYSTEM

2020 ◽  
pp. 128-131
Author(s):  
Sk. Naveed ◽  
N.Ramya ◽  
D.Manasa ◽  
N. Ramya Sri
Keyword(s):  
Face Recognition ◽  
Personal Characteristics ◽  
Recognition System ◽  
Personal Identification ◽  
Identification System ◽  
Training Images ◽  
The Face ◽  
Facial Recognition System ◽  
The Individual ◽  
And Training

The face is one of the easiest ways to differentiate the individual identity of each other. Face recognition is a personal identification system that uses personal characteristics or facial features of a person to identify the person's identity. The most used human face recognition process is face detection ,where this procedure takes place very quickly in humans, except under certain conditions where the object is located at close distance. The purpose of this project is to develop face recognition based automated student attendance system. In order to achieve high quality performance, the test images and training images of this proposed approach are limited to frontal and upright facial images that consist of a single face only. The test images and training images have to be captured by using the same device to ensure no quality difference. In addition, the students have to register in the database to be recognized. The enrolment can be done on the spot through the user-friendly interface.

scholarly journals Usability Evaluation Model for Biometric System considering Privacy Concern Based on MCDM Model

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Junhyoung Oh ◽  
Ukjin Lee ◽  
Kyungho Lee
Keyword(s):  
Iris Recognition ◽  
Evaluation Model ◽  
Recognition System ◽  
Usability Evaluation ◽  
Fingerprint Recognition ◽  
Privacy Concern ◽  
Biometric Systems ◽  
Quantitative Score ◽  
Integral Role ◽  
Facial Recognition System

Biometric devices play an integral role in consumer’s daily life, providing a seamless environment. However, it is essential to measure the usability of biometrics, owing to the elements of biometrics satisfying both usability and security. This study redefines the elements of biometrics pertaining to usability determined in previous studies and adds elements of psychological relevance, such as privacy concerns. To organize the interrelated usability structure systemically, this paper applies the DEcision MAking Trial and Evaluation Laboratory (DEMATEL) to derive the usability structure. Thereupon, the established structure is applied in the clustered weighted Analytical Network Processes (ANP) to generate the proposed usability evaluation model. By these methods, the pertinent relationships between the factors are clarified and the weight of each element is determined. In the empirical study, 106 students measured usability of the fingerprint recognition system, iris recognition system, and facial recognition system employing our usability evaluation model. The results of this model generate the quantitative score of usability for biometric systems and suggest strategies to increase the score. The proposed usability evaluation model can comprehensively assist usability practitioners to evaluate biometric systems.

scholarly journals Facial Recognition System for People with and without Face Mask in Times of the COVID-19 Pandemic

2021 ◽  
Vol 13 (12) ◽  
pp. 6900
Author(s):  
Jonathan S. Talahua ◽  
Jorge Buele ◽  
P. Calvopiña ◽  
José Varela-Aldás
Keyword(s):  
Facial Recognition ◽  
Face Mask ◽  
Recognition System ◽  
Classification Model ◽  
World Health ◽  
The Face ◽  
Recognition Systems ◽  
Facial Recognition System ◽  
Health Organization ◽  
Face Detector

In the face of the COVID-19 pandemic, the World Health Organization (WHO) declared the use of a face mask as a mandatory biosafety measure. This has caused problems in current facial recognition systems, motivating the development of this research. This manuscript describes the development of a system for recognizing people, even when they are using a face mask, from photographs. A classification model based on the MobileNetV2 architecture and the OpenCv’s face detector is used. Thus, using these stages, it can be identified where the face is and it can be determined whether or not it is wearing a face mask. The FaceNet model is used as a feature extractor and a feedforward multilayer perceptron to perform facial recognition. For training the facial recognition models, a set of observations made up of 13,359 images is generated; 52.9% images with a face mask and 47.1% images without a face mask. The experimental results show that there is an accuracy of 99.65% in determining whether a person is wearing a mask or not. An accuracy of 99.52% is achieved in the facial recognition of 10 people with masks, while for facial recognition without masks, an accuracy of 99.96% is obtained.

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>

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 Design and Implementation of Facial Recognition System for Visually Impaired using Image Processing

2019 ◽  
Vol 8 (4) ◽  
pp. 4803-4807
Keyword(s):  
Image Processing ◽  
Face Recognition ◽  
Face Detection ◽  
Visually Impaired ◽  
Recognition System ◽  
Raspberry Pi ◽  
Design And Implementation ◽  
The Face ◽  
Visually Impaired Students ◽  
Facial Recognition System

One of the most difficult tasks faced by the visually impaired students is identification of people. The rise in the field of image processing and the development of algorithms such as the face detection algorithm, face recognition algorithm gives motivation to develop devices that can assist the visually impaired. In this research, we represent the design and implementation of a facial recognition system for the visually impaired by using image processing. The device developed consists of a programmed raspberry pi hardware. The data is fed into the device in the form of images. The images are preprocessed and then the input image captured is processed inside the raspberry pi module using KNN algorithm, The face is recognized and the name is fed into text to speech conversion module. The visually impaired student will easily recognize the person before him using the device. Experiment results show high face detection accuracy and promising face recognition accuracy in suitable conditions. The device is built in such a way to improve cognition, interaction and communication of visually impaired students in schools and colleges. This system eliminates the need of a bulk computer since it employs a handy device with high processing power and reduced costs.

Fingerprint Recognition in Wavelet Domain

2012 ◽  
Author(s):  
Wan Azizun Wan Adnan ◽  
Tze Siang Lim ◽  
Salasiah Hitam
Keyword(s):  
Image Processing ◽  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Low Cost ◽  
Recognition System ◽  
Fingerprint Recognition ◽  
Fingerprint Identification ◽  
Small Computer ◽  
Identification System ◽  
Identification Algorithm

Teknik cetak ibujari merupakan satu daripada teknologi biometrik yang paling boleh diharapkan. Beberapa pendekatan terhadap pemadanan ibujari secara automatik telah dicadangkan dalam saranan. Dalam pengecaman ibujari, pra–prosesan seperti pelicin, binarization dan thinning diperlukan. Kemudian, ciri–ciri cetak ibujari yang terperinci diambil berdasarkan algoritma pengecaman cetak ibujari (seperti dengan menggunakan Fast Fourier Transform (FFT)) mungkin memerlukan teknik–teknik pengkomputeran yang banyak sehingga menjadikannya tidak praktikal. Algoritma berdasarkan wavelet mungkin merupakan kunci untuk membina sistem pengecaman cetak ibujari kos rendah yang boleh dioperasi dalam sistem komputer bermodul kecil. Di sini, satu sistem pengecaman cetak ibujari yang boleh menjalankan pemadanan cetak ibujari berdasarkan kepada ciri–ciri yang diperolehi daripada domain jelmaan wavelet diperkenalkan. Kajian ini adalah berdasarkan kepada perisian MATLAB dan aplikasinya dalam toolbox seperti Wavelet and Image Processing Toolbox. Kata kunci: Biometrik, wavelet, cetaksekuriti, pengecaman cetak ibujari Fingerprint technique is one of the most reliable biometric technologies. In the fingerprint recognition, pre-processing such as smoothing, binarization, and thinning are needed. Then, fingerprint minutia feature is extracted. Some fingerprint identification algorithm (such as using Fast Fourier Transform, (FFT)) may require so much computation as to be impractical. Wavelet based algorithm may be the key to making a low cost fingerprint identification system that would operate on a small computer. We present a fingerprint recognition system that can match the fingerprint images based on features extracted in the wavelet transform domain. This study is implemented based on MATLAB Software and their toolbox applications, such as Wavelet and Image Processing Toolbox. Key words: Biometrics, wavelet, security, fingerprint recognition

The Design of Library Management System Based on Internet of Things and Hand Lines Recognition System

2014 ◽  
Vol 672-674 ◽  
pp. 1985-1990 ◽  
Author(s):  
Wang Fang
Keyword(s):  
Management System ◽  
Iris Recognition ◽  
Recognition Performance ◽  
Recognition System ◽  
Recognition Algorithm ◽  
Fingerprint Recognition ◽  
Library Management ◽  
Material Resources ◽  
Library Management System ◽  
Biometric Systems

For an ordinary individual biometric systems and technology, such as fingerprint recognition, palm recognition, face recognition or iris recognition, or late detection from a single object has crippled so that they have the characteristics of unity and limitations, this paper combining fingerprint and hand palm pattern recognition technology, taking into account the complexity of the image pattern and diversity, we propose a dual recognition algorithm, which greatly makes up for lack of a single fingerprint or palm print recognition method. The technology used in library management system than traditional card-borrowed books have higher efficiency and save manpower and material resources. After the experimental statistics, and achieved the desired results, not only improve the recognition efficiency, but also to ensure the accuracy of the recognition performance.

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