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.

scholarly journals Face Recognition Based on Statistical Texture Features

2021 ◽  
Vol 7 (1) ◽  
pp. 10-15
Author(s):  
Lama Akram Ibrahim ◽  
Nasser Nasser ◽  
Majd Ali
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Face Recognition ◽  
Processing Time ◽  
Facial Recognition ◽  
Texture Features ◽  
Memory Consumption ◽  
Methods And Techniques ◽  
Recognition Systems ◽  
Occurrence Matrix

Facial recognition has attracted the attention of researchers and has been one of the most prominent topics in the fields of image processing and pattern recognition since 1990. This resulted in a very large number of recognition methods and techniques with the aim of increasing the accuracy and robustness of existing systems. Many techniques have been developed to address the challenges and reliable recognition systems have been reached but require considerable processing time, suffer from high memory consumption and are relatively complex. The focus of this paper is on extracting subset of descriptors (less correlated and less calculations) from the co-occurrence matrix with the goal of enhancing the performance of Haralick’s descriptors. Improvements are achieved by adding the image pre-processing and selecting the proper method according to the database problem and by extracting features from image local regions.

Age-Invariant Face Recognition Using Triangle Geometric Features

2015 ◽  
Vol 29 (05) ◽  
pp. 1556006 ◽  
Author(s):  
Amal Seralkhatem Osman Ali ◽  
Vijanth Sagayan Asirvadam ◽  
Aamir Saeed Malik ◽  
Mohamed Meselhy Eltoukhy ◽  
Azrina Aziz
Keyword(s):  
Face Recognition ◽  
State Of The Art ◽  
Facial Recognition ◽  
Research Network ◽  
Facial Features ◽  
Age Difference ◽  
Facial Aging ◽  
The Face ◽  
Recognition Systems ◽  
Mathematical Relationships

Whilst facial recognition systems are vulnerable to different acquisition conditions, most notably lighting effects and pose variations, their particular level of sensitivity to facial aging effects is yet to be researched. The face recognition vendor test (FRVT) 2012's annual statement estimated deterioration in the performance of face recognition systems due to facial aging. There was about 5% degradation in the accuracies of the face recognition systems for each single year age difference between a test image and a probe image. Consequently, developing an age-invariant platform continues to be a significant requirement for building an effective facial recognition system. The main objective of this work is to address the challenge of facial aging which affects the performance of facial recognition systems. Accordingly, this work presents a geometrical model that is based on extracting a number of triangular facial features. The proposed model comprises a total of six triangular areas connecting and surrounding the main facial features (i.e. eyes, nose and mouth). Furthermore, a set of thirty mathematical relationships are developed and used for building a feature vector for each sample image. The areas and perimeters of the extracted triangular areas are calculated and used as inputs for the developed mathematical relationships. The performance of the system is evaluated over the publicly available face and gesture recognition research network (FG-NET) face aging database. The performance of the system is compared with that of some of the state-of-the-art face recognition methods and state-of-the-art age-invariant face recognition systems. Our proposed system yielded a good performance in term of classification accuracy of more than 94%.

Similarity Measures for Face Recognition

2015 ◽  
Keyword(s):  
Computer Vision ◽  
Face Recognition ◽  
Facial Recognition ◽  
Similarity Measures ◽  
Corrective Surgery ◽  
Mahalanobis Distances ◽  
Computer Scientists ◽  
Criminal Suspects ◽  
Recognition Systems ◽  
Minkowski Distances

Similarity Measures for Face Recognition Face recognition has several applications, including security, such as (authentication and identification of device users and criminal suspects), and in medicine (corrective surgery and diagnosis). Facial recognition programs rely on algorithms that can compare and compute the similarity between two sets of images. This eBook explains some of the similarity measures used in facial recognition systems in a single volume. Readers will learn about various measures including Minkowski distances, Mahalanobis distances, Hansdorff distances, cosine-based distances, among other methods. The book also summarizes errors that may occur in face recognition methods. Computer scientists "facing face" and looking to select and test different methods of computing similarities will benefit from this book. The book is also useful tool for students undertaking computer vision courses.

scholarly journals Face Detection & Recognition using Tensor Flow: A Review

2018 ◽  
Vol 18 ◽  
pp. 7381-7388
Author(s):  
Ishaan Chawla
Keyword(s):  
Social Media ◽  
Face Recognition ◽  
Access Control ◽  
Face Detection ◽  
Facial Recognition ◽  
Rapid Development ◽  
Standard Form ◽  
Surveillance Systems ◽  
Security Systems ◽  
Recognition Systems

Face recognition has become a popular topic of research recently due to increases in demand for security as well as the rapid development of mobile devices. There are many applications which face recognition can be applied to such as access control, identity verification, security systems, surveillance systems, and social media networks. Access control includes offices, computers, phones, ATMs, etc. Most of these forms currently do not use face recognition as the standard form of granting entry, but with advancing technologies in computers along with more refined algorithms, facial recognition is gaining some traction in replacing passwords and fingerprint scanners. Ever since the events of 9/11 there has been a more concerned emphasis on developing security systems to ensure the safety of innocent citizens. Namely in places such as airports and border crossings where identification verification is necessary, face recognition systems potentially have the ability to mitigate the risk and ultimately prevent future attacks from occurring. As for surveillance systems, the same point can be made if there are criminals on the loose. Surveillance cameras with face recognition abilities can aide in efforts of finding these individuals. Alternatively, these same surveillance systems can also help identify the whereabouts of missing persons, although this is dependent on robust facial recognition algorithms as well as a fully developed database of faces. And lastly, facial recognition has surfaced in social media applications on platforms such as Facebook which suggest users to tag friends who have been identified in pictures. It is clear that there are many applications the uses for facial recognition systems. In general, the steps to achieve this are the following: face detection, feature extraction, and lastly training a model.

scholarly journals A review of current bracken control and associated vegetation strategies in Great Britain

Web Ecology ◽  
2002 ◽  
Vol 3 (1) ◽  
pp. 6-11 ◽  
Author(s):  
R. J. Pakeman ◽  
M. G. Le Duc ◽  
R. Marrs
Keyword(s):  
Great Britain ◽  
Large Scale ◽  
Control Strategies ◽  
Experimental Studies ◽  
Calluna Vulgaris ◽  
Cost Effective ◽  
Control Programme ◽  
Vegetation Restoration ◽  
The Cost ◽  
Set Of Points

Abstract. Bracken is a major problem for livestock-based, extensive agriculture in many parts of the world. It also causes problems for conservation, recreation, game management and forestry and is hence subject to management in order to control it. This paper reviews current bracken control strategies in Great Britain to assess whether they can be improved, and reviews recent work on combining bracken control with vegetation restoration to derive guidelines for maximising the cost-effectiveness of these measures to increase biodiversity. Bracken control in Great Britain is currently, mainly undertaken by aerial spraying of herbicide. A large-scale survey showed that only a small proportion (25%) of sites were likely to show long-term control, the developing vegetation was not that desired by the instigator of control, and there was a large geographic variation in success. The major conclusion was that large-scale treatment often exceeded the area that could be adequately treated by follow-up measures. Experimental studies demonstrate that to obtain “desirable” vegetation (usually Calluna vulgaris-dominated heath in Great Britain) a number of steps usually have to be followed. However, the steps that have to be taken may differ between sites. Deep litter sites, where stock numbers are low, need the litter disturbed in some way and seed of suitable species added. On sites with higher stock numbers, litter disturbance has in effect already been carried out, so that management must involve seed addition and the exclusion/reduction of stock. It is not yet known how long or to what level stock must be removed before the vegetation is able to withstand grazing. It should be noted that management to reverse succession could prove less cost-effective than management that accelerates succession to woodland or forestry. A set of points which highlight the considerations necessary at the commencement of an “integrated” bracken control programme are outlined. Targeting sites in western Britain or sites with residual vegetation present would provide the greatest gains for biodiversity in the short term. However, in many situations management for vegetation restoration must be seen as a key part of this strategy, not as something that will proceed unaided after bracken control has taken place.

Application of 3D face recognition in the access control system

Robotica ◽  
2021 ◽  
pp. 1-19
Author(s):  
Quoc Dien Le ◽  
Tran Thanh Cong Vu ◽  
Tuong Quan Vo
Keyword(s):  
Control System ◽  
Face Recognition ◽  
Access Control ◽  
Facial Recognition ◽  
Recognition Algorithm ◽  
User Cooperation ◽  
Web Based ◽  
Access Control System ◽  
Recognition Systems ◽  
And Storage

Abstract Over the years, face recognition has been the research topic that has attracted many researchers around the world. One of the most significant applications of face recognition is the access control system. The access control system allows authorized persons to enter or exit certain or restricted areas. As a result, it will increase the security situation without over-investment in staff security. The access information can be the identification, time, and location, etc. It can be used to carry out human resource management tasks such as attendance and inspection of employees in a more fair and transparent manner. Although face recognition has been widely used in access control systems because of its better accuracy and convenience without requiring too much user cooperation, the 2D-based face recognition systems also retain many limitations due to the variations in pose and illumination. By analyzing facial geometries, 3D facial recognition systems can theoretically overcome the disadvantages of prior 2D methods and improve robustness in different working conditions. In this paper, we propose the 3D facial recognition algorithm for use in an access control system. The proposed algorithm includes the preprocessing, feature extraction, and classification stages. The application of the proposed access control system is the automatic sliding door, the controller of the system, the web-based monitoring, control, and storage of data.

Biometric Spoofing and Anti-Spoofing

2017 ◽  
pp. 121-139
Author(s):  
Zahid Akhtar
Keyword(s):  
Large Scale ◽  
Security Requirements ◽  
Security Systems ◽  
Comprehensive Overview ◽  
Research Directions ◽  
Person Recognition ◽  
Biometric Systems ◽  
Prime Objective ◽  
Recognition Systems ◽  
Multimodal Biometric Systems

The demand for reliable and robust person recognition systems has expanded due to intense security requirements in today's highly intertwined network society. The advantages of biometrics over traditional security systems have triggered large-scale deployment of biometrics as an authentic technique to determine the identity of an individual. The prime objective of such methods is to assure that the systems are only accessed by genuine users. Since, biometric traits are overt, leading thus to a threat of them being captured, copied, and forged. Numerous techniques have been developed over the years for biometric spoofing and anti-spoofing. The goal of this chapter is to provide a comprehensive overview on works in the field of spoofing and anti-spoofing with special attention to three mainly accepted biometric traits (i.e., fingerprint, face and iris) and multimodal biometric systems. We also present the key challenges, major issues and point out some of the salient and useful research directions.

scholarly journals Learning Meta Model for Zero- and Few-Shot Face Anti-Spoofing

2020 ◽  
Vol 34 (07) ◽  
pp. 11916-11923 ◽  
Author(s):  
Yunxiao Qin ◽  
Chenxu Zhao ◽  
Xiangyu Zhu ◽  
Zezheng Wang ◽  
Zitong Yu ◽  
...  
Keyword(s):  
Face Recognition ◽  
Supervised Learning ◽  
Large Scale ◽  
Training Data ◽  
Learning Problem ◽  
Meta Model ◽  
Meta Learning ◽  
Recognition Systems

Face anti-spoofing is crucial to the security of face recognition systems. Most previous methods formulate face anti-spoofing as a supervised learning problem to detect various predefined presentation attacks, which need large scale training data to cover as many attacks as possible. However, the trained model is easy to overfit several common attacks and is still vulnerable to unseen attacks. To overcome this challenge, the detector should: 1) learn discriminative features that can generalize to unseen spoofing types from predefined presentation attacks; 2) quickly adapt to new spoofing types by learning from both the predefined attacks and a few examples of the new spoofing types. Therefore, we define face anti-spoofing as a zero- and few-shot learning problem. In this paper, we propose a novel Adaptive Inner-update Meta Face Anti-Spoofing (AIM-FAS) method to tackle this problem through meta-learning. Specifically, AIM-FAS trains a meta-learner focusing on the task of detecting unseen spoofing types by learning from predefined living and spoofing faces and a few examples of new attacks. To assess the proposed approach, we propose several benchmarks for zero- and few-shot FAS. Experiments show its superior performances on the presented benchmarks to existing methods in existing zero-shot FAS protocols.

scholarly journals Fibonacci Series based Virtual Machine Selection for Load Balancing in Cloud Computing

2018 ◽  
Vol 7 (3.12) ◽  
pp. 1071
Author(s):  
Japman Kaur Dhaliwal ◽  
Mohd Naseem ◽  
Aadil Ahamad Lawaye ◽  
Ehtesham Husain Abbasi
Keyword(s):  
Cloud Computing ◽  
Execution Time ◽  
Large Scale ◽  
Virtual Machines ◽  
Fibonacci Sequence ◽  
Round Robin ◽  
Shared Resources ◽  
Process Data ◽  
Resource Saving ◽  
The Cost

The rapid advancement of the internet has given birth to many technologies. Cloud computing is one of the most emerging technology which aim to process large scale data by using the computational capabilities of shared resources. It gives support to the distributed parallel processing. Using cloud computing, we can process data by paying according to its uses which eliminates the requirement of device by individual users. As cloud computing grows, more users get attracted towards it. However, providing an efficient execution time and load distribution is a major challenging issue in the distributed systems. In our approach, weighted round robin algorithm is used and benefits of Fibonacci sequence is combined which results in better execution time than static round robin. Relevant virtual machines are chosen and jobs are assigned to them. Also, number of resources being utilized concurrently is reduced, which leads to resource saving thereby reducing the cost. There is no need to deploy new resources as resources such as virtual machines are already available.  

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