scholarly journals Security and Accuracy of Fingerprint-Based Biometrics: A Review

Symmetry ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 141 ◽  
Author(s):  
Wencheng Yang ◽  
Song Wang ◽  
Jiankun Hu ◽  
Guanglou Zheng ◽  
Craig Valli
Keyword(s):  
Recognition Accuracy ◽  
Research Work ◽  
Research Topic ◽  
Foreseeable Future ◽  
Biometric System ◽  
Systems Security ◽  
Biometric Systems ◽  
High Recognition Accuracy ◽  
Future Work ◽  
Shed Light

Biometric systems are increasingly replacing traditional password- and token-based authentication systems. Security and recognition accuracy are the two most important aspects to consider in designing a biometric system. In this paper, a comprehensive review is presented to shed light on the latest developments in the study of fingerprint-based biometrics covering these two aspects with a view to improving system security and recognition accuracy. Based on a thorough analysis and discussion, limitations of existing research work are outlined and suggestions for future work are provided. It is shown in the paper that researchers continue to face challenges in tackling the two most critical attacks to biometric systems, namely, attacks to the user interface and template databases. How to design proper countermeasures to thwart these attacks, thereby providing strong security and yet at the same time maintaining high recognition accuracy, is a hot research topic currently, as well as in the foreseeable future. Moreover, recognition accuracy under non-ideal conditions is more likely to be unsatisfactory and thus needs particular attention in biometric system design. Related challenges and current research trends are also outlined in this paper.

Multimodal biometric system using deep learning based on face and finger vein fusion

2021 ◽  
pp. 1-13
Author(s):  
Shikhar Tyagi ◽  
Bhavya Chawla ◽  
Rupav Jain ◽  
Smriti Srivastava
Keyword(s):  
High Performance ◽  
Recognition Accuracy ◽  
Error Rates ◽  
Facial Features ◽  
Biometric System ◽  
Deep Convolutional Neural Networks ◽  
Finger Vein ◽  
Biometric Systems ◽  
Overall Performance ◽  
Recognition Systems

Single biometric modalities like facial features and vein patterns despite being reliable characteristics show limitations that restrict them from offering high performance and robustness. Multimodal biometric systems have gained interest due to their ability to overcome the inherent limitations of the underlying single biometric modalities and generally have been shown to improve the overall performance for identification and recognition purposes. This paper proposes highly accurate and robust multimodal biometric identification as well as recognition systems based on fusion of face and finger vein modalities. The feature extraction for both face and finger vein is carried out by exploiting deep convolutional neural networks. The fusion process involves combining the extracted relevant features from the two modalities at score level. The experimental results over all considered public databases show a significant improvement in terms of identification and recognition accuracy as well as equal error rates.

scholarly journals Biometrics in a data stream context

2018 ◽  
Author(s):  
Paulo Henrique Pisani ◽  
André C. P. L. F. De Carvalho
Keyword(s):  
Data Stream ◽  
Recognition Performance ◽  
Biometric System ◽  
Change Over Time ◽  
Biometric Systems ◽  
Future Work ◽  
Biometric Features ◽  
Modular Framework ◽  
Over Time

Biometric systems can provide safer authentication. However, biometric features may change over time, impacting the recognition performance due to outdated biometric references. It raises the need to automatically adapt the references over time, by using adaptive biometric systems. This thesis studied several aspects of adaptive biometric systems in a data stream context. Based on this investigation, it was observed that the best choice for each aspect can be user dependent. This motivated the proposal of a modular adaptive biometric system, which can select a different configuration for each user. It also generalizes several baselines and proposals into a single modular framework, while opening numerous opportunities for future work.

Character Reorganization and Categorization using Hybrid Algorithms by Scanned Documents

2019 ◽  
Vol 8 (6S2) ◽  
pp. 943-948
Keyword(s):  
Research Work ◽  
Hybrid Algorithms ◽  
Research Topic ◽  
Image Processing Techniques ◽  
Digital Books ◽  
Otsu Method ◽  
Challenging Research ◽  
Processing Techniques ◽  
Scanned Documents ◽  
Day By Day

Detection and reorganization of text may save a lot of time while reproducing old books text and its chapters. This is really challenging research topic as different books may have different font types and styles. The digital books and eBooks reading habit is increasing day by day and new documents are producing every day. So in order to boost the process the text reorganization using digital image processing techniques can be used. This research work is using hybrid algorithms and morphological algorithms. For sample we have taken an letter pad where the text and images are separated using algorithms. The another objective of this research is to increase the accuracy of recognized text and produce accurate results. This research worked on two different concepts, first is concept of Pixel-level thresholding processing and another one is Otsu Method thresholding.

The Association between Depression and Gastroesophageal Reflux based on Phylogenetic Analysis of miRNA Biomarkers

2020 ◽  
Vol 27 (38) ◽  
pp. 6536-6547 ◽  
Author(s):  
Yi-Hau Chen ◽  
Hsiuying Wang
Keyword(s):  
Phylogenetic Analysis ◽  
Major Depression ◽  
Gastroesophageal Reflux Disease ◽  
Gastroesophageal Reflux ◽  
Reflux Disease ◽  
Research Work ◽  
Epidemiological Evidence ◽  
The Relationship ◽  
Global Population ◽  
Shed Light

A number of clinical studies have revealed that there is an association between major depression (MD) and gastroesophageal reflux disease (GERD). Both the diseases are shown to affect a large proportion of the global population. More advanced studies for understanding the comorbidity mechanism of these two diseases can shed light on developing new therapies of both diseases. To the best of our knowledge, there has not been any research work in the literature investigating the relationship between MD and GERD using their miRNA biomarkers. We adopt a phylogenetic analysis to analyze their miRNA biomarkers. From our analyzed results, the association between these two diseases can be explored through miRNA phylogeny. In addition to evidence from the phylogenetic analysis, we also demonstrate epidemiological evidence for the relationship between MD and GERD based on Taiwan biobank data.

Machete

2021 ◽  
Vol 28 (1) ◽  
pp. 1-46
Author(s):  
Eugene M. Taranta II ◽  
Corey R. Pittman ◽  
Mehran Maghoumi ◽  
Mykola Maslych ◽  
Yasmine M. Moolenaar ◽  
...  
Keyword(s):  
Video Game ◽  
Recognition Accuracy ◽  
Training Sample ◽  
Low Latency ◽  
Computationally Efficient ◽  
Extensive Evaluation ◽  
Segmentation Accuracy ◽  
Alternative Techniques ◽  
High Recognition Accuracy ◽  
Continuous Dynamic

We present Machete, a straightforward segmenter one can use to isolate custom gestures in continuous input. Machete uses traditional continuous dynamic programming with a novel dissimilarity measure to align incoming data with gesture class templates in real time. Advantages of Machete over alternative techniques is that our segmenter is computationally efficient, accurate, device-agnostic, and works with a single training sample. We demonstrate Machete’s effectiveness through an extensive evaluation using four new high-activity datasets that combine puppeteering, direct manipulation, and gestures. We find that Machete outperforms three alternative techniques in segmentation accuracy and latency, making Machete the most performant segmenter. We further show that when combined with a custom gesture recognizer, Machete is the only option that achieves both high recognition accuracy and low latency in a video game application.

Ion-gating synaptic transistors with long-term synaptic weight modulation

2021 ◽  
Vol 9 (16) ◽  
pp. 5396-5402
Author(s):  
Youngjun Park ◽  
Min-Kyu Kim ◽  
Jang-Sik Lee
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Synaptic Weight ◽  
Recognition Accuracy ◽  
Artificial Neural ◽  
High Recognition Accuracy

This paper presents synaptic transistors that show long-term synaptic weight modulation via injection of ions. Linear and symmetric weight update is achieved, which enables high recognition accuracy in artificial neural networks.

El Concepto De La lingüística Cognitiva En La Poesía Traducida Análisis Semántico Según La Teoría del Esquema Básico De La Referencia

2021 ◽  
Vol 29 ◽  
Author(s):  
Ahmed Hameed Abdulmajeed Abeer Hussein Abid
Keyword(s):  
Cognitive Linguistics ◽  
Semantic Analysis ◽  
Research Work ◽  
Speech Community ◽  
Search For Meaning ◽  
Basic Scheme ◽  
Scheme Theory ◽  
The Common ◽  
Symmetry Relations ◽  
Shed Light

This research work is part of a project to get an M.A. degree. Some of the linguistic sciences specialized in the search for meaning in the text, such as semantics, pragmatics, cognitive linguistics and etc. will be clarified. Besides, we shed light on the elements of semantic analysis with examples according to the basic scheme theory of reference, which indicates that the language is of a fictional nature. As it is a variety of similarity and symmetry relations between the form of the word and its meaning, whether it is phonetic or written or related to metaphor, metonymy or analogy, and it is not a random relationship. In all these genres, a very important role is played by imaginative comprehension, which subsequently acquires a traditional character and spreads due to the common collective understanding of the word among speakers of the speech community.

scholarly journals Biometric Systems De-Identification: Current Advancements and Future Directions

2021 ◽  
Vol 1 (3) ◽  
pp. 470-495
Author(s):  
Md Shopon ◽  
Sanjida Nasreen Tumpa ◽  
Yajurv Bhatia ◽  
K. N. Pavan Kumar ◽  
Marina L. Gavrilova
Keyword(s):  
Information Security ◽  
System Development ◽  
User Profile ◽  
Information Privacy ◽  
Biometric System ◽  
Comprehensive Overview ◽  
Future Directions ◽  
Behavioral Biometrics ◽  
Open Questions ◽  
Biometric Systems

Biometric de-identification is an emerging topic of research within the information security domain that integrates privacy considerations with biometric system development. A comprehensive overview of research in the context of authentication applications spanning physiological, behavioral, and social-behavioral biometric systems and their privacy considerations is discussed. Three categories of biometric de-identification are introduced, namely complete de-identification, auxiliary biometric preserving de-identification, and traditional biometric preserving de-identification. An overview of biometric de-identification in emerging domains such as sensor-based biometrics, social behavioral biometrics, psychological user profile identification, and aesthetic-based biometrics is presented. The article concludes with open questions and provides a rich avenue for subsequent explorations of biometric de-identification in the context of information privacy.

AMELOGLYPHICS-AN UPDATED REVIEW

2021 ◽  
pp. 44-46
Author(s):  
Linda Christabel. S ◽  
Merrylda Claribel. S ◽  
Sushmitha. M ◽  
Mohammed Haroon. A. L ◽  
Karpagam. S ◽  
...  
Keyword(s):  
Soft Tissues ◽  
Forensic Odontology ◽  
Vital Role ◽  
Biometric System ◽  
Hard Tissue ◽  
Gas Leakage ◽  
Biometric Systems ◽  
Stored Information ◽  
Mass Disasters ◽  
Modern Era

In this modern era equipped with technologies, the crime rates are increasing exponentially. This requires newer methodologies to identify a person who is a victim as well as the perpetruator. Automated biometric systems helps in identifying the individuals by the stored information in the database which are unique for each individual. Some of the important methods are ngerprint biometrics and iris scanning.As these methods involves soft tissues they cant be relied upon during mass disasters like burn accidents and gas leakage accidents. Hence, a biometric system using the hard tissue is required for better identication of the individuals. Thus, Ameloglyphics is introduced to aid in identication of individuals died during mass disasters and it plays a vital role in forensic odontology. This review highlights this technology in detail.

Visual Attention for Behavioral Biometric Systems

2010 ◽  
pp. 290-316 ◽  
Author(s):  
Concetto Spampinato
Keyword(s):  
Computational Models ◽  
Careful Analysis ◽  
Recognition System ◽  
Biometric System ◽  
The Third ◽  
Morphological Aspects ◽  
The People ◽  
Face Recognition System ◽  
Biometric Systems ◽  
State Of Art

The chapter is so articulated: the first section will tackle the state of art of the attention theory, with the third paragraph related to the computational models that implement the attention theories, with a particular focus on the model that is the basis for the proposed biometric systems. Such an algorithm will be used for describing the first biometric system. The following section will tackle the people recognition algorithms carried out by evaluating the FOAs distribution. In detail, two different systems are proposed: 1) a face recognition system that takes into account both the behavioral and morphological aspects, and 2) a pure behavioral biometric system that recognizes people according to their actions evaluated by a careful analysis of the extracted FOAs.

Sign in / Sign up

Export Citation Format

Share Document