scholarly journals Face Liveness Detection : An Overview

2021 ◽  
pp. 22-29
Author(s):  
Shweta Policepatil ◽  
Sanjeevakumar M. Hatture
Keyword(s):  
Face Recognition ◽  
Literature Survey ◽  
The Other ◽  
Detection Methods ◽  
Fundamental Properties ◽  
Liveness Detection ◽  
Use Of Technology ◽  
The World ◽  
Recognition Systems ◽  
User Friendly

As the world becomes more and more digitized, the threat to security grows at an alarming rate. The mass usage of technology has garnered the attention and curiosity of people with foul intentions, whose aim is to exploit this use of technology to commit theft and other heinous crimes. One such technology used for security purposes is “Facial Recognition”. Face recognition is a popular biometric technique. Face recognition technology has advanced fast in recent years, and when compared to other ways, it is more direct, user-friendly, and convenient. Face recognition systems, on the other hand, are vulnerable to spoof assaults by non-real faces. To protect against spoofing, a secure system requires liveness detection. This study examines researchers' attempts to address the problem of spoofing and liveness detection, including mapping the research overview from the literature survey into a suitable taxonomy, exploring the fundamental properties of the field, motivation for using liveness detection methods in face recognition, and problems that may limit the benefits.

scholarly journals Insight on face liveness detection: A systematic literature review

2019 ◽  
Vol 9 (6) ◽  
pp. 5865
Author(s):  
Enas A. Raheem ◽  
Sharifah Mumtazah Syed Ahmad ◽  
Wan Azizun Wan Adnan
Keyword(s):  
Face Recognition ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Web Of Science ◽  
Literature Survey ◽  
Detection Methods ◽  
Basic Properties ◽  
General Overview ◽  
Liveness Detection ◽  
Different Types

<p>To review researcher’s attempts in response to the problem of spoofing and liveness detection, mapping the research overview from the literature survey into a suitable taxonomy, exploring the basic properties of the field, motivation of using liveness detection methods in face recognition, and Problems that may restrain the advantages. We presented a subjected search on face recognition with liveness detection and its synonyms in four main databases: Web of science, Science Direct, Scopus and IEEE Xplore. We believe that these databases are widely inclusive enough to cover the literature.<em> </em>The final number of articles considered is 65 articles. 4 of them where review and survey articles that described a general overview about liveness detection and anti-spoofing methods. Since 2012, and despite of leaving some areas unestablished and needs more attention, researchers tried to keep track of liveness detection in several ways. No matter what their category is, articles concentrated on challenges that faces the full utility of anti-spoofing methods and recommended some solutions to overcome these challenges. In this paper, different types of liveness detection and face anti-spoofing techniques are investigated to keep researchers updated with what is being developed in this field.</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 Face Spoof Attack Recognition Using Discriminative Image Patches

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Zahid Akhtar ◽  
Gian Luca Foresti
Keyword(s):  
Detection Methods ◽  
Support Vector ◽  
Border Crossings ◽  
Replay Attack ◽  
Mobile Payments ◽  
Liveness Detection ◽  
Video Frames ◽  
Image Patches ◽  
Wide Scale ◽  
Recognition Systems

Face recognition systems are now being used in many applications such as border crossings, banks, and mobile payments. The wide scale deployment of facial recognition systems has attracted intensive attention to the reliability of face biometrics against spoof attacks, where a photo, a video, or a 3D mask of a genuine user’s face can be used to gain illegitimate access to facilities or services. Though several face antispoofing or liveness detection methods (which determine at the time of capture whether a face is live or spoof) have been proposed, the issue is still unsolved due to difficulty in finding discriminative and computationally inexpensive features and methods for spoof attacks. In addition, existing techniques use whole face image or complete video for liveness detection. However, often certain face regions (video frames) are redundant or correspond to the clutter in the image (video), thus leading generally to low performances. Therefore, we propose seven novel methods to find discriminative image patches, which we define as regions that are salient, instrumental, and class-specific. Four well-known classifiers, namely, support vector machine (SVM), Naive-Bayes, Quadratic Discriminant Analysis (QDA), and Ensemble, are then used to distinguish between genuine and spoof faces using a voting based scheme. Experimental analysis on two publicly available databases (Idiap REPLAY-ATTACK and CASIA-FASD) shows promising results compared to existing works.

scholarly journals Innovative and sustainable toothpaste packaging design

2020 ◽  
Vol 11 (2) ◽  
pp. 19-29
Author(s):  
Anastasia Malea ◽  
◽  
Anastasios Tzotzis ◽  
Athanasios Manavis ◽  
Panagiotis Kyratsis ◽  
...  
Keyword(s):  
Environmental Impact ◽  
Market Research ◽  
Oral Care ◽  
Literature Survey ◽  
Tooth Brushing ◽  
The Other ◽  
Packaging Design ◽  
Environmental Friendly ◽  
Other Hand ◽  
User Friendly

Oral care products and especially toothpastes, are vital for the human daily hygiene. Nowadays tooth brushing is, without a doubt, an integral part of pre-ventative dentistry, but on the other hand the extensive use of toothpastes has a great impact on the environment. Traditional toothpaste tubes have many negative aspects, in terms of usage and recycling. Their modest size, mixed and merged materials, remnant toothpaste inside toothpaste tubes and other tube based containers, make them difficult to disassemble and recycling almost impossible. The main objective of this study, is to investi-gate the disadvantages of the toothpaste packaging and the proposal of new innovative packaging solutions, which will not only reduce the environmental impact that traditional toothpaste tubes cause, but will also be user-friendly. In this paper, a combination of literature survey and market research is being presented. Finally, based on the findings and well-established techniques, a number of innovative, user and environmental friendly toothpaste packaging is proposed.

scholarly journals Workshop, Cost-Effective and Streamlined Fabrications of Re-Usable World-To-Chip Connectors for Handling Sample of Limited Volume and for Assembling Chip Array

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4223
Author(s):  
Jiann-Hwa Lue ◽  
Yu-Sheng Su ◽  
Tai-Chih Kuo
Keyword(s):  
Fluorescent Protein ◽  
Microfluidic Devices ◽  
Cost Effective ◽  
The Other ◽  
Microfluidic Chips ◽  
Zebra Fish ◽  
Limited Volume ◽  
The World ◽  
Green Fluorescent ◽  
User Friendly

The world-to-chip interface is an essential yet intriguing part of making and employing microfluidic devices. A user-friendly connector could be expensive or difficult to make. We fabricated two ports of microfluidic chips with easily available materials including Teflon blocks, double adhesive films, coverslips, and transparency films. By using a mini grinder, coverslips were drilled to form small holes for the fluid passages between port and chip. Except for the double adhesive films, the resultant ports are durable and re-useable. The DK1 port, contains a mini three-way switch which allows users to handle fluid by a tube-connected pump, or by a manual pipette for the sample of trace amount. The other port, the DK2 port, provides secured tube-connections. Importantly, we invented a bridge made of craft cutter-treated transparency films and double adhesive films to mediate liquid flow between DK2 port and chip. With the use of a bridge, users do not need to design new ports for new chips. Also, individual chips could be linked by a bridge to form a chip array. We successfully applied DK1 port on a microfluidic chip where green fluorescent protein was immobilized. We used DK2 port on an array of fish chips where the embryos of zebra fish developed.

Time and classification

2004 ◽  
Author(s):  
T.S. Kemp
Keyword(s):  
Fossil Record ◽  
The Other ◽  
Before Present ◽  
Unfinished Business ◽  
Evolutionary Patterns ◽  
Fundamental Properties ◽  
The World ◽  
Geological Timescale ◽  
Different Parts

The age and the classification of a particular fossil are the two fundamental properties necessary to begun understanding how it fits into the evolutionary patterns revealed by the fossil record. There are often misunderstandings of one or other of these by specialists. Evolutionary biologists on occasion express far too optimistic a view of how accurately fossils can actually be dated, both absolutely and relative to one another. Geologists have been known to have a rather limited view of how modern systematic methods are used to infer relationships from large amounts of information, be it morphological or molecular. In this chapter, a brief outline of the principles underlying the construction of the geological timescale, and of a classification are given, along with reference timescales and classifications for use throughout the following chapters. The creation of a timescale for dating the events recorded in the rocks since the origin of the Earth is one of the greatest achievements of science, unspectacular and taken for granted as it may often be. It is also unfinished business insofar as there are varying degrees of uncertainty and inaccuracy about the dates of many rock exposures, none more so than among the mostly continental, rather than marine sediments containing the fossils with which this work is concerned. A geological timescale is actually a compilation of the results of two kinds of study. One is recognising the temporal sequence of the rocks, and agreeing arbitrarily defined boundaries between the named rock units, the result of which is a chronostratic timescale. The other is calibration of the sequence and its divisions in absolute time units of years before present, a chronometric timescale. It is simple in principle to list the relative temporal order of events, such as the occurrence of fossils, in a single rock unit, although even here the possibility of missing segments, known as hiatuses, in local parts of the unit, or of complex folding movements of the strata disturbing the order must not be forgotten. The biggest problem is correlating relative dates between different units in different parts of the world.

scholarly journals Improving Deep-Learning-based Face Recognition to Increase Robustness against Morphing Attacks

2020 ◽  
Author(s):  
Una M. Kelly ◽  
Luuk Spreeuwers ◽  
Raymond Veldhuis
Keyword(s):  
Deep Learning ◽  
Face Recognition ◽  
State Of The Art ◽  
Detection Methods ◽  
Identity Document ◽  
Recognition Systems

State-of-the-art face recognition systems (FRS) are vulnerable to morphing attacks, in which two photos of different people are merged in such a way that the resulting photo resembles both people. Such a photo could be used to apply for a passport, allowing both people to travel with the same identity document. Research has so far focussed on developing morphing detection methods. We suggest that it might instead be worthwhile to make face recognition systems themselves more robust to morphing attacks. We show that deep-learning-based face recognition can be improved simply by treating morphed images just like real images during training but also that, for significant improvements, more work is needed. Furthermore, we test the performance of our FRS on morphs of a type not seen during training. This addresses the problem of overfitting to the type of morphs used during training, which is often overlooked in current research.

Finding Facial Emotions From the Clutter Scenes Using Zernike Moments-Based Convolutional Neural Networks

2021 ◽  
pp. 241-265
Author(s):  
Wencan Zhong ◽  
Vijayalakshmi G. V. Mahesh ◽  
Alex Noel Joseph Raj ◽  
Nersisson Ruban
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Face Recognition ◽  
Facial Expression ◽  
Convolutional Neural Networks ◽  
Zernike Moments ◽  
The Other ◽  
Recognition Systems ◽  
Facial Images ◽  
Surveillance Applications

Finding faces in the clutter scenes is a challenging task in automatic face recognition systems as facial images are subjected to changes in the illumination, facial expression, orientation, and occlusions. Also, in the cluttered scenes, faces are not completely visible and detecting them is essential as it is significant in surveillance applications to study the mood of the crowd. This chapter utilizes the deep learning methods to understand the cluttered scenes to find the faces and discriminate them into partial and full faces. The work proves that MTCNN used for detecting the faces and Zernike moments-based kernels employed in CNN for classifying the faces into partial and full takes advantage in delivering a notable performance as compared to the other techniques. Considering the limitation of recognition on partial face emotions, only the full faces are preserved, and further, the KDEF dataset is modified by MTCNN to detect only faces and classify them into four emotions. PatternNet is utilized to train and test the modified dataset to improve the accuracy of the results.

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