A survey of Techniques for Face Liveness Recognition (original) (raw)
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—Face recognition is a widely used biometric approach. Face recognition technology has developed rapidly in recent years and it is more direct, user friendly and convenient compared to other methods. But face recognition systems are vulnerable to spoof attacks made by non-real faces. It is an easy way to spoof face recognition systems by facial pictures such as portrait photographs. A secure system needs Liveness detection in order to guard against such spoofing. In this work, face liveness detection approaches are categorized based on the various types techniques used for liveness detection. This categorization helps understanding different spoof attacks scenarios and their relation to the developed solutions. A review of the latest works regarding face liveness detection works is presented. The main aim is to provide a simple path for the future development of novel and more secured face liveness detection approach.
To detect duplication of identity during authentication of online payment on mobile or personal computer, the automatic face recognition is widely used now days. The biometric presentation attacks can be performed to gain access to these systems. It is performed by presenting the authorized person"s photo or video. Hence it is important to study the various face spoof attacks. Currently proposed face spoof detection techniques have less generalization ability as these are not considering all factors and do not detect the spoofing medium.The four features such as specular reflection, blurriness, chromatic moment and color diversity are used to analyze the image distortion. The different classifiers are trained for printed photo attack and video replay attack to differentiate between genuine and spoof faces. We also propose an approach to detect the spoofing medium by checking the boundary of the captured image during the photo attack and video attack and an approach to detect the blinking of eye for detecting liveness. It gives us high efficiency rather than existing methods.
Face Liveness Detection : An Overview
International Journal of Scientific Research in Science and Technology, 2021
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.
Survey of Various Face Liveness Detection Techniques for Biometric Antispoofing Applications
International Journal Of Engineering And Computer Science, 2017
Face recognition is a widely used biometric approach. Face recognition technology has developed rapidly in recent years and it is more direct, user friendly and convenient compared to other methods. But face recognition systems are vulnerable to spoof attacks made by non-real faces. It is an easy way to spoof face recognition systems by facial pictures such as portrait photographs. A secure system needs Liveness detection in order to guard against such spoofing. In this work, face liveness detection approaches are categorized based on the various types techniques used for liveness detection. This categorization helps understanding different spoof attacks scenarios and their relation to the developed solutions. A review of the latest works regarding face liveness detection works is presented. The main aim is to provide a simple path for the future development of novel and more secured face liveness detection approach.
Face Spoof Attack Recognition Using Discriminative Image Patches
Journal of Electrical and Computer Engineering, 2016
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 ...
A Case Study on Face Spoof Detection
IRJET, 2022
User authentication is a vital step in protecting information, and facial bio metrics might assist in this regard. Face bio metrics seems to be more natural, simple to use, and less intrusive to humans. Unfortunately, emerging research has revealed that face bio metrics are extremely sensitive to spoofing assaults. A spoofing attack occurs when a person tries to masquerade as someone else by falsifying data and thereby gaining illegitimate access. Inspired by image quality assessment, characterization of printing artifacts, and differences in light reflection, we propose to approach the problem of spoofing detection from texture analysis point of view. This report discusses many types of assaults against visual spectrum facial recognition systems. We propose comprehensive data sets for assessing the susceptibility of recognition systems and the effectiveness of countermeasures. Finally, we give a brief overview of anti-spoofing strategies for visual spectrum face identification, as well as a viewpoint on difficulties that remain unresolved.
Implementation of Face Spoof Recognization by Using Image Distortion Analysis
2018
Automatic face recognition is now widely used in applications ranging from deduplication of identity to authentication of mobile payment. This popularity of face recognition has raised concerns about face spoof attacks (also known as biometric sensor presentation attacks), where a photo or video of an authorized person’s face could be used to gain access to facilities or services. While a number of face spoof detection techniques have been proposed, their generalization ability has not been adequately addressed. We proposed an efficient and rather robust face spoof detection algorithm based on image distortion analysis (IDA). In this work we proposed Template matching algorithm for face recognization. Here we perform Face recognization by live streaming to improve the performance of the system. Here the image is given as input and facial features like eyes, nose, and mouth are extracted from the image. The proposed algorithm compares input images with stored patterns of face or feat...
Face Spoofing Detection Techniques using Biometrics
The modern biometric technologies provides us better convenience and security features. Face Recognition Biometric systems are being used and deployed in applications such as surveillance, forensic investigation etc., but it is vulnerable mostly in case of face spoofing attacks. Such spoofing can be done by means of video frames, printed photo. To detect these types of attacks, the liveness of face detection is being developed, and also being deployed in face recognition biometric systems. If these methods don't exist in the face recognition biometric systems, it may give permission to a malicious person to masquerade as authentic users to the data file system. To address these problems, it's important to develop a secure biometric recognition system. The current method and approach to detect the liveness within the facial biometrics by making use of the feature extraction methods, includes Local Binary Pattern (LBP), Color Moment Features (CMF). In the proposed system combining two or three features proposed mainly, Histogram of Oriented Gradients (HOG), Spectral Information Divergence (SID), Binarized Statistical Image Features (BSIF), Weber Local Descriptor (WLD) and Local Phase Quantization (LPQ). Support Vector Machine (SVM) classifier gives the result as whether the image is spoofed or real. Done detailed survey on face spoof detection methods, feature methods and algorithms that are existing today and being used for the detection of spoof images. Based on the facts gathered, the execution with minimum and simple use of hardware makes biometric systems better secured and robust.
An Overview of Face Liveness Detection
International Journal on Information Theory, 2014
Face recognition is a widely used biometric approach. Face recognition technology has developed rapidly in recent years and it is more direct, user friendly and convenient compared to other methods. But face recognition systems are vulnerable to spoof attacks made by non-real faces. It is an easy way to spoof face recognition systems by facial pictures such as portrait photographs. A secure system needs Liveness detection in order to guard against such spoofing. In this work, face liveness detection approaches are categorized based on the various types techniques used for liveness detection. This categorization helps understanding different spoof attacks scenarios and their relation to the developed solutions. A review of the latest works regarding face liveness detection works is presented. The main aim is to provide a simple path for the future development of novel and more secured face liveness detection approach.
Face Spoofing and Counter-Spoofing: A Survey of State-of-the-art Algorithms
Transactions on Machine Learning and Artificial Intelligence, 2017
In the current scenario of biometric-based identity verification, a face is still being proved to be an essential physiological evidence for successful person identification without letting know the target. Nevertheless, repeated attacks of intruders can cause the face recognition system insecure because of easy availability of face images or pictures of a person in social networks or in other networked resources. Spoofing facial identity in a biometric system is not a difficult task for intruders. When an intruder presents a photograph or a video containing a face of a person in front of a networked camera which is integrated with a face biometric system, spoofing is referred to as presentation attack. Without anti-spoofing mechanisms, biometric systems are at high risk in case of susceptible attacks. Thus, detecting face spoof in a face biometric system is a challenging research field. The aim of this book is to summarize some of the most popular face spoof detection techniques wh...