ROTATED WAVELET FILTERS-BASED FINGERPRINT RECOGNITION

2012 ◽  
Vol 26 (03) ◽  
pp. 1256008 ◽  
Author(s):  
SANGITA D. BHARKAD ◽  
MANESH KOKARE
Keyword(s):  
Acceptance Rate ◽  
Fingerprint Recognition ◽  
Discrete Wavelet ◽  
Fingerprint Matching ◽  
False Acceptance Rate ◽  
Fingerprint Image ◽  
Significant Information ◽  
Wavelet Filters ◽  
Novel Approach

A novel approach for feature extraction of fingerprint matching is proposed by using two-dimensional (2D) rotated wavelet filters (RWF). 2D RWF are used to capture the characterization of diagonally oriented information present in fingerprint image. Proposed method extracts the significant information from small area of fingerprint image. Experimental results conducted on standard database of Bologna University and FVC2002 indicate that the proposed method improves the genuine acceptance rate (GAR) from 92.14% to 96.12% and reduces false acceptance rate (FAR) from 25.2% to 21.2% on Bologna University database and it reduces FAR from 36.71% to 22.79% on FVC2002 database compared with discrete wavelet transform-based approach.

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.

scholarly journals Pencocokan Citra Sidik Jari Menggunakan Korelasi Silang Ternormalisasi

2015 ◽  
Vol 11 (4) ◽  
pp. 144
Author(s):  
Bulkis Kanata
Keyword(s):  
Image Matching ◽  
Cross Correlation ◽  
Region Of Interest ◽  
Fingerprint Recognition ◽  
Fingerprint Matching ◽  
Fingerprint Image ◽  
Image Capture ◽  
Matching Algorithm ◽  
Specific Part ◽  
Finger Pressure

<p>Fingerprint image matching is an important procedure in fingerprint recognition. Robust fingerprint image matching under a variety of different image capture conditions is difficult to achieve, because of changes in finger pressure, variation of the angle, etc. Fingerprint matching is very important for the development of fingerprint system recognition that is sensitive to finger pressure. This paper proposes a fingerprint matching algorithm that enables the so-called fingerprint template (extracted specific part (region of interest (ROI)) of a person’s fingerprints to be matched to the different fingerprint of the same person or different people taken on different time, angle and a different finger pressure using normalized cross-correlation (NCC). This algorithm was implemented in MATLAB. The results showed that the maximum NCC value for ROI of the source fingerprints and targets that was greater than 0.62 indicates a strong correlation or similarity.</p><p> </p>

Research of Automatic Fingerprint Recognition Essential Algorithms

2011 ◽  
Vol 135-136 ◽  
pp. 739-742
Author(s):  
Jin Hai Zhang
Keyword(s):  
Identity Authentication ◽  
Fingerprint Recognition ◽  
Theoretical Research ◽  
Identification System ◽  
Fingerprint Matching ◽  
Significant Progress ◽  
Fingerprint Image ◽  
Matching Algorithm ◽  
Minutiae Extraction ◽  
Extraction Algorithm

Fingerprint recognition has wide application prospect in all fields which contain identity authentication. Construction of accurate and reliable，safe and Practical automatic fingerprint identification system(AFIS) has become researc hotspot. Although theoretical research and application developmen of AFIS have got a significant Progress，accuracy of the algorithm and proeessing speeds till need to be improved. In this paper, fingerprint image preprocessing algorithms，fingerprint singular Points and minutiae extraction algorithm and fingerprint matching algorithm are analyzed and discussed in detail.

scholarly journals Application of Innovative TGA/Chemometric Approach for Forensic Purposes: The Estimation of the Time since Death in Contaminated Specimens

Diagnostics ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 121
Author(s):  
Roberta Risoluti ◽  
Giuseppina Gullifa ◽  
Vittorio Fineschi ◽  
Paola Frati ◽  
Stefano Materazzi
Keyword(s):  
Multidisciplinary Approach ◽  
Vitreous Humor ◽  
Classification Model ◽  
Forensic Sciences ◽  
Time Since Death ◽  
Time Of Death ◽  
Novel Approach ◽  
Chemometric Approach ◽  
Postmortem Examinations

Chronothanatology has always been a challenge in forensic sciences. Therefore, the importance of a multidisciplinary approach for the characterization of matrices (organs, tissues, or fluids) that respond linearly to the postmortem interval (PMI) is emerging increasingly. The vitreous humor is particularly suitable for studies aimed at assessing time-related modifications because it is topographically isolated and well-protected. In this work, a novel approach based on thermogravimetry and chemometrics was used to estimate the time since death in the vitreous humor and to collect a databank of samples derived from postmortem examinations after medico–legal evaluation. In this study, contaminated and uncontaminated specimens with tissue fragments were included in order to develop a classification model to predict time of death based on partial least squares discriminant analysis (PLS-DA) that was as robust as possible. Results demonstrate the possibility to correctly predict the PMI even in contaminated samples, with an accuracy not lower than 70%. In addition, the correlation coefficient of the measured versus predicted outcomes was found to be 0.9978, confirming the ability of the model to extend its feasibility even to such situations involving contaminated vitreous humor.

scholarly journals Efficiently Updating ECG-Based Biometric Authentication Based on Incremental Learning

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1568
Author(s):  
Junmo Kim ◽  
Geunbo Yang ◽  
Juhyeong Kim ◽  
Seungmin Lee ◽  
Ko Keun Kim ◽  
...  
Keyword(s):  
Incremental Learning ◽  
Physical State ◽  
Acceptance Rate ◽  
Support Vector ◽  
Ecg Signal ◽  
Biometric Authentication ◽  
False Acceptance Rate ◽  
Ecg Signals ◽  
Using Data ◽  
False Acceptance

Recently, the interest in biometric authentication based on electrocardiograms (ECGs) has increased. Nevertheless, the ECG signal of a person may vary according to factors such as the emotional or physical state, thus hindering authentication. We propose an adaptive ECG-based authentication method that performs incremental learning to identify ECG signals from a subject under a variety of measurement conditions. An incremental support vector machine (SVM) is adopted for authentication implementing incremental learning. We collected ECG signals from 11 subjects during 10 min over six days and used the data from days 1 to 5 for incremental learning, and those from day 6 for testing. The authentication results show that the proposed system consistently reduces the false acceptance rate from 6.49% to 4.39% and increases the true acceptance rate from 61.32% to 87.61% per single ECG wave after incremental learning using data from the five days. In addition, the authentication results tested using data obtained a day after the latest training show the false acceptance rate being within reliable range (3.5–5.33%) and improvement of the true acceptance rate (70.05–87.61%) over five days.

3D crustal-scale structure of the West Iberia margin: a novel approach to integrated structural characterization of passive margins

2021 ◽  
Vol 42 (2) ◽  
Author(s):  
Cristina Granado ◽  
Alfonso Muñoz-Martín ◽  
Antonio J. Olaiz ◽  
Oscar Fernández ◽  
María Druet
Keyword(s):  
Structural Characterization ◽  
Scale Structure ◽  
The West ◽  
Passive Margins ◽  
Novel Approach

Multimodal score level fusion for recognition using face and palmprint

2020 ◽  
pp. 002072092092966
Author(s):  
Milind E Rane ◽  
Umesh S Bhadade
Keyword(s):  
Recognition System ◽  
Acceptance Rate ◽  
Face Database ◽  
Biometric Recognition ◽  
False Acceptance Rate ◽  
Score Level Fusion ◽  
Score Fusion ◽  
Matching Score ◽  
Level Fusion ◽  
Fusion Approach

The paper proposes a t-norm-based matching score fusion approach for a multimodal heterogenous biometric recognition system. Two trait-based multimodal recognition system is developed by using biometrics traits like palmprint and face. First, palmprint and face are pre-processed, extracted features and calculated matching score of each trait using correlation coefficient and combine matching scores using t-norm based score level fusion. Face database like Face 94, Face 95, Face 96, FERET, FRGC and palmprint database like IITD are operated for training and testing of algorithm. The results of experimentation show that the proposed algorithm provides the Genuine Acceptance Rate (GAR) of 99.7% at False Acceptance Rate (FAR) of 0.1% and GAR of 99.2% at FAR of 0.01% significantly improves the accuracy of a biometric recognition system. The proposed algorithm provides the 0.53% more accuracy at FAR of 0.1% and 2.77% more accuracy at FAR of 0.01%, when compared to existing works.

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