scholarly journals Adaptive Threshold for Fingerprint Recognition System Based on Threat Level and System Load

2020 ◽  
Vol 171 ◽  
pp. 498-507
Author(s):  
Vaibhav B Joshi ◽  
Mehul S Raval
Keyword(s):  
Recognition System ◽  
Adaptive Threshold ◽  
Fingerprint Recognition ◽  
System Load ◽  
Threat Level

scholarly journals Adaptive Threshold for Fingerprint Recognition System Based on Threat Level and System Load

2019 ◽  
Author(s):  
Mehul Raval ◽  
Vaibhav B Joshi
Keyword(s):  
Fuzzy Inference ◽  
Rejection Rate ◽  
Recognition System ◽  
Fingerprint Recognition ◽  
Inference System ◽  
Acceptance Threshold ◽  
System Load ◽  
Threat Level ◽  
Artificial Neural Network Ann ◽  
Matching Score

Fingerprint is widely used trait for person recognition in civilian applications. A user is authenticated when matching score is greater than acceptance threshold. The performance of fingerprint system (FS) is evaluated based on false acceptance rate (FAR) and false rejection rate (FRR). Usually the FS is set to work at a rate where FAR and FRR are equal (EER). However, operating at EER allows finite FAR which is risky during critical threat. In response acceptance threshold must shifts towards zero FAR to mitigate threat. This increases FRR, system load and user inconvenience. In civilian application acceptance threshold is set by vendor and currently there is no research attempt to change it dynamically. This is necessary as; 1) system must respond to external parameters like load and threat level; 2) system must balance security and user convenience due to high traffic?c. This paper describes a method to change acceptance threshold over the interval EER to zero FAR based on system load and threat level. The proposed method is based on fuzzy inference system (FIS) and artificial neural network (ANN).

Analysis of Fingerprint Recognition System Using Neural Network

2020 ◽  
Author(s):  
Ganesh Awasthi ◽  
Dr. Hanumant Fadewar ◽  
Almas Siddiqui ◽  
Bharatratna P. Gaikwad
Keyword(s):  
Neural Network ◽  
Recognition System ◽  
Fingerprint Recognition

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>

scholarly journals School Debit Transaction Using Fingerprint Recognition System

2019 ◽  
Vol 1 (2) ◽  
Author(s):  
Wai Kit Wong ◽  
Thu Soe Min ◽  
Shi Enn Chong
Keyword(s):  
Labour Force ◽  
Recognition System ◽  
Payment System ◽  
Fingerprint Recognition ◽  
Biometric Technology ◽  
Cash Payment ◽  
User Need ◽  
Minutiae Matching

This paper proposed a fingerprint based school debit transaction system using minutiae matching biometric technology. This biometric cashless transaction system intensely shortens the luncheon line traffic and labour force compared to conventional cash payment system. Furthermore, contrast with card cashless transaction system, fingerprint cashless transaction system with benefit that user need not carry additional identification object and remember lengthy password. The implementation of this cashless transaction system provides a more organize, reliable and efficient way to operate the school debit transaction system. 

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