scholarly journals Verifying the Effectiveness of New Face Spoofing DB with Capture Angle and Distance

Electronics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 661
Author(s):  
Jin Yeong Bok ◽  
Kun Ha Suh ◽  
Eui Chul Lee
Keyword(s):  
Image Analysis ◽  
Face Recognition ◽  
Three Dimensional ◽  
Image Sensor ◽  
Detection Accuracy ◽  
Lighting Conditions ◽  
Additional Equipment ◽  
Recognition Systems ◽  
Face Spoofing ◽  
Better Than

Face recognition is a representative biometric that can be easily used; however, spoofing attacks threaten the security of face biometric systems by generating fake faces. Thus, it is not advisable to only consider sophisticated spoofing cases, such as three-dimensional masks, because they require additional equipment, thereby increasing the implementation cost. To prevent easy face spoofing attacks through print and display, the two-dimensional (2D) image analysis method using existing face recognition systems is reasonable. Therefore, we proposed a new database called the “pattern recognition-face spoofing advancement database” that can be used to prevent such attacks based on 2D image analysis. To the best of our knowledge, this is the first face spoofing database that considers the changes in both the angle and distance. Therefore, it can be used to train various positional relationships between a face and camera. We conducted various experiments to verify the efficiency of this database. The spoofing detection accuracy of our database using ResNet-18 was found to be 96.75%. The experimental results for various scenarios demonstrated that the spoof detection performances were better for images with pinch angle, near distance images, and replay attacks than those for front images, far distance images, and print attacks, respectively. In the cross-database verification result, the performance when tested with other databases (DBs) after training with our DB was better than the opposite. The results of cross-device verification in terms of camera type showed negligible difference; thus, it was concluded that the type of image sensor does not affect the detection accuracy. Consequently, it was confirmed that the proposed DB that considers various distances, capture angles, lighting conditions, and backgrounds can be used as a training DB to detect spoofing attacks in general face recognition systems.

scholarly journals Implementing CCTV-Based Attendance Taking Support System Using Deep Face Recognition: A Case Study at FPT Polytechnic College

Symmetry ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 307 ◽  
Author(s):  
Ngo Tung Son ◽  
Bui Ngoc Anh ◽  
Tran Quy Ban ◽  
Le Phuong Chi ◽  
Bui Dinh Chien ◽  
...  
Keyword(s):  
Face Recognition ◽  
Motion Blur ◽  
Security Monitoring ◽  
Flexible System ◽  
Lighting Conditions ◽  
Satisfactory Performance ◽  
Measurement Results ◽  
The Face ◽  
Recognition Systems

Face recognition (FR) has received considerable attention in the field of security, especially in the use of closed-circuit television (CCTV) cameras in security monitoring. Although significant advances in the field of computer vision are made, advanced face recognition systems provide satisfactory performance only in controlled conditions. They deteriorate significantly in the face of real-world scenarios such as lighting conditions, motion blur, camera resolution, etc. This article shows how we design, implement, and conduct the empirical comparisons of machine learning open libraries in building attendance taking (AT) support systems using indoor security cameras called ATSS. Our trial system was deployed to record the appearances of 120 students in five classes who study on the third floor of FPT Polytechnic College building. Our design allows for flexible system scaling, and it is not only usable for a school but a generic attendance system with CCTV. The measurement results show that the accuracy is suitable for many different environments.

scholarly journals ILLUMINATION PROCESSING IN FACE RECOGNITION

2014 ◽  
Vol 28 (05) ◽  
pp. 1456011 ◽  
Author(s):  
ZHENXUE CHEN ◽  
CHENGYUN LIU ◽  
FALIANG CHANG ◽  
XUZHEN HAN ◽  
KAIFANG WANG
Keyword(s):  
Adverse Effect ◽  
Face Recognition ◽  
Light Intensity ◽  
Negative Impact ◽  
Processing Method ◽  
Dark Region ◽  
Light Region ◽  
The Face ◽  
Recognition Systems ◽  
Better Than

Changes in light intensity and angle present a major challenge to the creation of reliable face recognition systems. The existence of bright regions and dark regions has been shown to have a serious negative impact on the performance of face recognition systems. This paper proposes a solution to this problem based on self-quotient image (SQI) processing method. In this method, bright and dark areas are processed separately without changing the essential characteristics of the image of the face. The dark and light areas are processed separately by SQI. Experimental results indicate that this Single-Light-Region and Single-Dark-Region SQI method removes the adverse effect of multi-bright and multi-dark areas better than competing methods.

scholarly journals An Analysis of Face Recognition under Face Mask Occlusions

2021 ◽  
Author(s):  
Susith Hemathilaka ◽  
Achala Aponso
Keyword(s):  
Face Recognition ◽  
Rapid Development ◽  
Face Mask ◽  
Large Area ◽  
Daily Lives ◽  
Lighting Conditions ◽  
Intractable Problems ◽  
The Face ◽  
Recognition Systems ◽  
Pose Variation

The face mask is an essential sanitaryware in daily lives growing during the pandemic period and is a big threat to current face recognition systems. The masks destroy a lot of details in a large area of face and it makes it difficult to recognize them even for humans. The evaluation report shows the difficulty well when recognizing masked faces. Rapid development and breakthrough of deep learning in the recent past have witnessed most promising results from face recognition algorithms. But they fail to perform far from satisfactory levels in the unconstrained environment during the challenges such as varying lighting conditions, low resolution, facial expressions, pose variation and occlusions. Facial occlusions are considered one of the most intractable problems. Especially when the occlusion occupies a large region of the face because it destroys lots of official features.

scholarly journals Nonorthogonal Aerial Optoelectronic Platform Based on Triaxial and Control Method Designed for Image Sensors

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 10
Author(s):  
Quanchao Li ◽  
Shuyan Xu ◽  
Yulei Xu ◽  
Lei Li ◽  
Liu Zhang
Keyword(s):  
Optical Sensors ◽  
Control Method ◽  
Three Dimensional ◽  
Voice Coil Motor ◽  
Image Sensor ◽  
Dimensional Structure ◽  
Internal Space ◽  
Drive Control ◽  
The Stability ◽  
Better Than

A traditional aerial optoelectronic platform consists of inside and outside multilayer gimbals, while an internal gimbal and drive components occupy the internal space where optical sensors are located. In order to improve the replaceability of optical sensors and to increase their available space, this paper introduces a nonorthogonal aerial optoelectronic platform based on three axes; we carried out research on its drive control method. A three-dimensional structure of an aerial optoelectronic platform was designed. A noncontact drive of a linear voice coil motor was introduced, and a drive control scheme of a proportional integral and a disturbance observer was adopted. Finally, simulations and experiments were carried out. Results showed that the aerial optoelectronic platform could effectively release three times the image sensor space, and the servo bandwidth was 60.2 Hz, which was much better than that of traditional two-axis and four-gimbal platforms. The stability accuracy of the system reached 4.9958 micron rad, which was obviously better than that of traditional gimbals. This paper provides a reference for the design of new optoelectronic platforms.

scholarly journals A Review on Face Anti-Spoofing

2021 ◽  
Vol 5 (1) ◽  
pp. 29
Author(s):  
Rizky Naufal Perdana ◽  
Igi Ardiyanto ◽  
Hanung Adi Nugroho
Keyword(s):  
Face Recognition ◽  
Access Control ◽  
Real World ◽  
Biometric System ◽  
Security Issue ◽  
Security Technology ◽  
The Face ◽  
Paper Review ◽  
Recognition Systems ◽  
Face Spoofing

The biometric system is a security technology that uses information based on a living person's characteristics to verify or recognize the identity, such as facial recognition. Face recognition has numerous applications in the real world, such as access control and surveillance. But face recognition has a security issue of spoofing. A face anti-spoofing, a task to prevent fake authorization by breaching the face recognition systems using a photo, video, mask, or a different substitute for an authorized person's face, is used to overcome this challenge. There is also increasing research of new datasets by providing new types of attack or diversity to reach a better generalization. This paper review of the recent development includes a general understanding of face spoofing, anti-spoofing methods, and the latest development to solve the problem against various spoof types.

scholarly journals Robust 3D Hand Detection from a Single RGB-D Image in Unconstrained Environments

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6360
Author(s):  
Chi Xu ◽  
Jun Zhou ◽  
Wendi Cai ◽  
Yunkai Jiang ◽  
Yongbo Li ◽  
...  
Keyword(s):  
State Of The Art ◽  
Three Dimensional ◽  
Detection Accuracy ◽  
Light Conditions ◽  
Hand Detection ◽  
Lighting Conditions ◽  
Detection Approach ◽  
Dark Conditions ◽  
Bounding Boxes ◽  
Human Hands

Three-dimensional hand detection from a single RGB-D image is an important technology which supports many useful applications. Practically, it is challenging to robustly detect human hands in unconstrained environments because the RGB-D channels can be affected by many uncontrollable factors, such as light changes. To tackle this problem, we propose a 3D hand detection approach which improves the robustness and accuracy by adaptively fusing the complementary features extracted from the RGB-D channels. Using the fused RGB-D feature, the 2D bounding boxes of hands are detected first, and then the 3D locations along the z-axis are estimated through a cascaded network. Furthermore, we represent a challenging RGB-D hand detection dataset collected in unconstrained environments. Different from previous works which primarily rely on either the RGB or D channel, we adaptively fuse the RGB-D channels for hand detection. Specifically, evaluation results show that the D-channel is crucial for hand detection in unconstrained environments. Our RGB-D fusion-based approach significantly improves the hand detection accuracy from 69.1 to 74.1 comparing to one of the most state-of-the-art RGB-based hand detectors. The existing RGB- or D-based methods are unstable in unseen lighting conditions: in dark conditions, the accuracy of the RGB-based method significantly drops to 48.9, and in back-light conditions, the accuracy of the D-based method dramatically drops to 28.3. Compared with these methods, our RGB-D fusion based approach is much more robust without accuracy degrading, and our detection results are 62.5 and 65.9, respectively, in these two extreme lighting conditions for accuracy.

scholarly journals Deep Discriminative Restricted Boltzmann Machine (DDRBM) for Robust Face Spoofing Detection

2018 ◽  
Vol 1 (3) ◽  
Author(s):  
Gustavo Botelho de Souza ◽  
Joao Paulo Papa ◽  
Aparecido Nilceu Marana
Keyword(s):  
Neural Networks ◽  
Face Recognition ◽  
Attack Detection ◽  
Restricted Boltzmann Machine ◽  
Digital Cameras ◽  
Boltzmann Machine ◽  
Robust Solution ◽  
Spoofing Detection ◽  
Recognition Systems ◽  
Face Spoofing

Biometrics emerged as a robust solution for security systems. Despite, nowadays criminals are developing techniques to accurately simulate biometric traits of valid users, process known as spoofing attack, in order to circumvent the biometric applications. Face is among the main biometric characteristics, being extremely convenient for users given its non-intrusive capture by means of digital cameras. However, face recognition systems are the ones that most suffer with spoofing attacks since such cameras, in general, can be easily fooled with common printed photographs. In this sense, countermeasure techniques should be developed and integrated to the traditional face recognition systems in order to prevent such frauds. Among the main neural networks for face spoofing detection is the discriminative Restricted Boltzmann Machine (RBM) which, besides of efficiency, achieves great results in attack detection by learning the distributions of real and fake facial images. However, it is known that deeper neural networks present better accuracy results in many tasks. In this context, we propose a novel model called Deep Discriminative Restricted Boltzmann Machine (DDRBM) applied to face spoofing detection. Results on the NUAA dataset show a significative improvement in performance when compared to the accuracy rates of a traditional discriminative RBM on attack detection.

scholarly journals Face Recognition by Reconstructing A 2.5 D Face using Photometric Stereo

2020 ◽  
Vol 9 (7) ◽  
pp. 944-949
Keyword(s):  
Face Recognition ◽  
Low Cost ◽  
Three Dimensional ◽  
Recognition System ◽  
Photometric Stereo ◽  
Identification System ◽  
2D Systems ◽  
3D Face Recognition ◽  
3D Face ◽  
Recognition Systems

Face recognition is an important application of image analysis and it has received a lot of interest in the last decade. There is a critical need for a reliable identification system. As of now, face recognition is not reliable enough in the majority of security applications, therefore a low cost, accurate, and viable identification method are required for face recognition. Two dimensional (2D) face recognition systems that are already existing are often not reliable. Three dimensional (3D) face recognition systems produce more accurate and robust than 2D systems but they are very costly due to large scanning and coded light and also consume a lot of time in the recognition process. This paper aims to produce a low-cost 3D face recognition system (2.5D) using photometric stereo which is less explored in face recognition systems. The capabilities of photometric stereo for use in face recognition are evaluated using a number of experiments conducted using the photometric stereo system and it is implemented and shown to be better than our traditional 2D systems. This system is aimed to solve a number of issues we see in face recognition systems like illumination, distance from the camera and pose and thus, it could be a useful application for biometric authentications in homes, governmental organizations and financial institutions

YÜZ TANIMA TABANLI DUYURU SİSTEMİ TASARIMI VE KULLANILABİLİRLİĞİ

2021 ◽  
Vol 8 (16) ◽  
pp. 21-35
Author(s):  
Berk YILMAZER ◽  
Serdar SOLAK
Keyword(s):  
Cloud Computing ◽  
Face Recognition ◽  
Large Scale ◽  
Facial Recognition ◽  
Experimental Studies ◽  
Shopping Mall ◽  
Person Recognition ◽  
Additional Equipment ◽  
Recognition Systems ◽  
The Cost

The rapid developments in technology have an increasing impact and use on biometric person recognition systems. Facial recognition-based systems, one of the biometric person recognition systems, have been widely used in recent years thanks to their easy implementation, fast integration and simple usage as they do not require any additional equipment. Especially the widespread use of computer vision and cloud-computing based applications, smart face recognition systems have become an indispensable part of our lives in recent years. The use of these systems, which have become widespread in security, health, education, military, shopping mall and industrial areas, has increased more during the pandemic period. Institutions and organizations do not want to allocate time and cost to write their own software for face recognition based systems. The services offered by major cloud computing providers can be used to solve this problem. In this context, the article presents a smart announcement system design using cloud computing based face recognition technology. In the past, making an announcement has been seen as a difficult task. It was thought to be a time consuming task, both because of the cost of printing and because all the operations had to be repeated when there were changes in the announcement. Today, signs have left their places to digital screens. It will especially ensure that announcements, warnings, promotions, and notifications are performed effectively at the developed system for large scale institutions, organizations, factories, universities, shopping malls and health institutions. Facial recognition based smart announcement system detects features such as person recognition, gender, and age estimation at a rate of 100% and displays personal announcements according to their priority status. In addition, according to the experimental studies, it was observed that the person recognition and the presentation of the announcements on the screen took an average of 1.3 seconds. According to the announcement system survey, 85% of those who use the system stated that it is useful and user-friendly.

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