scholarly journals A Face Recognition Method in the Internet of Things for Security in Smart Recognition Places

2022 ◽  
Vol 10 (1) ◽  
pp. 687-690
Author(s):  
Prof. Kalpana Malpe
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Associate Degree ◽  
Human Life ◽  
Recognition System ◽  
Raspberry Pi ◽  
Living Things ◽  
Face Recognition System ◽  
The Face ◽  
Face Detection And Recognition

Abstract: In recent years, the safety constitutes the foremost necessary section of the human life. At this point, the price is that the greatest issue. This technique is incredibly helpful for reducing the price of watching the movement from outside. During this paper, a period of time recognition system is planned which will equip for handling pictures terribly quickly. The most objective of this paper is to safeguard home, workplace by recognizing individuals. The face is that the foremost distinctivea part of human’s body. So, it will replicate several emotions of associate degree Expression. A few years past, humans were mistreatment the non-living things like good cards, plastic cards, PINS, tokens and keys for authentication, and to urge grant access in restricted areas like ISRO, National Aeronautics and Space Administration and DRDO. The most necessary options of the face image are Eyes, Nose and mouth. Face detection and recognition system is simpler, cheaper, a lot of accurate, process. The system under two categories one is face detection and face recognition. Throughout this case, among the paper, the Raspberry Pi single-board computer is also a heart of the embedded face recognition system. Keywords: Raspberry Pi, Face recognition system

Research and Implementation of Face Detection Based on OpenCV

2014 ◽  
Vol 971-973 ◽  
pp. 1710-1713
Author(s):  
Wen Huan Wu ◽  
Ying Jun Zhao ◽  
Yong Fei Che
Keyword(s):  
Face Recognition ◽  
Detailed Analysis ◽  
Real Time ◽  
Face Detection ◽  
Recognition System ◽  
Detection Algorithm ◽  
High Accuracy ◽  
Accuracy Rate ◽  
Face Recognition System ◽  
The Face

Face detection is the key point in automatic face recognition system. This paper introduces the face detection algorithm with a cascade of Adaboost classifiers and how to configure OpenCV in MCVS. Using OpenCV realized the face detection. And a detailed analysis of the face detection results is presented. Through experiment, we found that the method used in this article has a high accuracy rate and better real-time.

scholarly journals Real time Implementation of Face Recognition System on Raspberry Pi

2018 ◽  
Vol 7 (2.17) ◽  
pp. 85
Author(s):  
K Raju ◽  
Dr Y.Srinivasa Rao
Keyword(s):  
Face Recognition ◽  
High Performance ◽  
Recognition Rate ◽  
Cost Effective ◽  
Recognition System ◽  
Raspberry Pi ◽  
Face Recognition System ◽  
Effective System ◽  
Face Detection And Recognition ◽  
Improved Accuracy

Face Recognition is the ability to find and detect a person by their facial attributes. Face is a multi dimensional and thus requires a considerable measure of scientific calculations. Face recognition system is very useful and important for security, law authorization applications, client confirmation and so forth. Hence there is a need for an efficient and cost effective system. There are numerous techniques that are as of now proposed with low Recognition rate and high false alarm rate. Hence the major task of the research is to develop face recognition system with improved accuracy and improved recognition time. Our objective is to implementing Raspberry Pi based face recognition system using conventional face detection and recognition techniques such as A Haar cascade classifier is trained for detection and Local Binary Pattern (LBP) as a feature extraction technique. With the use of the Raspberry Pi kit, we go for influencing the framework with less cost and simple to use, with high performance. 

FACE DETECTION AND RECOGNITION USING MAXIMUM LIKELIHOOD CLASSIFIERS ON GABOR GRAPHS

2009 ◽  
Vol 23 (03) ◽  
pp. 433-461 ◽  
Author(s):  
MANUEL GÜNTHER ◽  
ROLF P. WÜRTZ
Keyword(s):  
Face Recognition ◽  
Maximum Likelihood ◽  
Face Detection ◽  
Recognition System ◽  
Similarity Functions ◽  
Expression Variation ◽  
Face Recognition System ◽  
Face Detection And Recognition ◽  
Ml Estimator ◽  
Detection And Recognition

We present an integrated face recognition system that combines a Maximum Likelihood (ML) estimator with Gabor graphs for face detection under varying scale and in-plane rotation and matching as well as a Bayesian intrapersonal/extrapersonal classifier (BIC) on graph similarities for face recognition. We have tested a variety of similarity functions and achieved verification rates (at FAR 0.1%) of 90.5% on expression-variation and 95.8% on size-varying frontal images within the CAS-PEAL database. Performing Experiment 1 of FRGC ver2.0, the method achieved a verification rate of 72%.

scholarly journals Face recognition attendance system using Local Binary Pattern (LBP)

2019 ◽  
Vol 8 (1) ◽  
pp. 239-245 ◽  
Author(s):  
Shamsul J. Elias ◽  
Shahirah Mohamed Hatim ◽  
Nur Anisah Hassan ◽  
Lily Marlia Abd Latif ◽  
R. Badlishah Ahmad ◽  
...  
Keyword(s):  
Image Processing ◽  
Face Recognition ◽  
Face Detection ◽  
Local Binary Pattern ◽  
Recognition System ◽  
Automated System ◽  
Student Attendance ◽  
Recognition Method ◽  
Face Recognition System ◽  
The Face

Attendance is important for university students. However, generic way of taking attendance in universities may include various problems. Hence, a face recognition system for attendance taking is one way to combat the problem. This paper will present an automated system that will automatically saves student’s attendance into the database using face recognition method. The paper will elaborate on student attendance system, image processing, face detection and face recognition. The face detection part will be done by using viola-jones algorithm method while the face recognition part will be carried on by using local binary pattern (LBP) method. The system will ensure that the attendance taking process will be faster and more accurate.

scholarly journals Design and Implementation of Facial Recognition System for Visually Impaired using Image Processing

2019 ◽  
Vol 8 (4) ◽  
pp. 4803-4807
Keyword(s):  
Image Processing ◽  
Face Recognition ◽  
Face Detection ◽  
Visually Impaired ◽  
Recognition System ◽  
Raspberry Pi ◽  
Design And Implementation ◽  
The Face ◽  
Visually Impaired Students ◽  
Facial Recognition System

One of the most difficult tasks faced by the visually impaired students is identification of people. The rise in the field of image processing and the development of algorithms such as the face detection algorithm, face recognition algorithm gives motivation to develop devices that can assist the visually impaired. In this research, we represent the design and implementation of a facial recognition system for the visually impaired by using image processing. The device developed consists of a programmed raspberry pi hardware. The data is fed into the device in the form of images. The images are preprocessed and then the input image captured is processed inside the raspberry pi module using KNN algorithm, The face is recognized and the name is fed into text to speech conversion module. The visually impaired student will easily recognize the person before him using the device. Experiment results show high face detection accuracy and promising face recognition accuracy in suitable conditions. The device is built in such a way to improve cognition, interaction and communication of visually impaired students in schools and colleges. This system eliminates the need of a bulk computer since it employs a handy device with high processing power and reduced costs.

scholarly journals GSM based Face Recognition using Pir Sensor on Raspberry Pi 3

2019 ◽  
Vol 8 (12) ◽  
pp. 329-332
Keyword(s):  
Face Recognition ◽  
Recognition System ◽  
Raspberry Pi ◽  
Face Area ◽  
Detection And Identification ◽  
Face Recognition System ◽  
Characteristic Views ◽  
The Face ◽  
Area Unit ◽  
Human Faces

We Developed An Associate Approach To The Detection And Identification Of Human Faces And Describe A Operating, Near-Real-Time Face Recognition System That Tracks A Subject’s Face And So Acknowledges The Person By Comparison Characteristics Of The Face To Database. Our Approach Treats Face Recognition As A Two-Dimensional Recognition Downside, Taking Advantage Of The Very Fact That Faces Area Unit Area Unit Normally Upright And Therefore Is Also Delineate By A Small Set Of 2-D Characteristic Views. Face Pictures Are Projected Onto A Feature Area (“Face Space”) That Best Encodes The Variation Among Database Images. The Face Area Is Outlined By The “Eigenfaces”, That Area Unit The Eigenvectors Of The Set Of Faces; They Do Not Essentially Correspond To Isolated Options Like Eyes, Ears, And Noses. The Framework Provides The Flexibility To Be Told To Acknowledge New Faces

scholarly journals Automatic Student Attendance System using Face Recognition

2020 ◽  
Vol 9 (3) ◽  
pp. 93-99
Keyword(s):  
Face Recognition ◽  
Recognition System ◽  
Automated Systems ◽  
Student Attendance ◽  
Face Recognition System ◽  
The Face ◽  
Face Detection And Recognition ◽  
Class Room ◽  
Current Systems ◽  
Detection And Recognition

The most common difficulty that every teacher faces in class room is to take the attendance of the students one by one in each and every class. For the time being many automated systems has been proposed for taking student attendance. In this paper, I introduced an automated student attendance system based on the use of unique techniques for face detection and recognition. This system automatically detects the student when he or she enters the classroom and recognizes that specific student and marks the student's attendance. This method also focuses on the specific features of different attributes such as the face, eye and nose of humans. In order to evaluate the performance of different face recognition system, different real-time situations are considered. This paper also suggests the technique for handling the technique such as spoofing and avoiding student proxy. This system helps track students compared to traditional or current systems and thereby saves time.

scholarly journals Challenges in Face Detection and Recognition techniques

2020 ◽  
Vol 9 (8) ◽  
pp. 221-224
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Recognition System ◽  
Research Paper ◽  
Facial Features ◽  
Image Information ◽  
Public Crisis ◽  
Face Recognition System ◽  
Face Detection And Recognition ◽  
Detection And Recognition

Face Recognition System is popular topic in the biometric world .This system provide Features to detect the person’s face and identify on basis of existing records in database .The aim of this study is to described how to show various facial features of an image. Face Recognition system, based on Biometric AI, uniquely finds out a person by analyzing the person's facial textures and shape. In this paper, our aim is to study various face detect and recognition techniques such as Harr Like Feature Algorithm resulting to retort criminality and public crisis. Also, some facial recognition approaches PCA and LDA have been discussed in the research paper for abstracting the image information.

scholarly journals Attendance Posting Through Face Recognition

2019 ◽  
Vol 8 (4) ◽  
pp. 11652-11654
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Recognition System ◽  
Biometric Authentication ◽  
New Approach ◽  
Important Method ◽  
Security Issues ◽  
Detection Technology ◽  
Face Recognition System ◽  
The Face

Now a day’s face detection technology is widely used technique. It attracted attention for much valuable application in the market such as face recognition system. Biometric authentication is most important method in security system. Universally used Biometric fingerprint scanner can be bypassed quite easily. It can be broke easily. Biometric face recognition has been introduced to improve the security of a system. Methods such as Motion based and texture based are used for biometric face recognition. But these methods have less robustness and poor generalization ability. But apart from further security issues, this paper presents a new approach to make attendance of the student in class by the face recognition. Now a day’s attendance system is usually done manually or by the biometric fingerprint. Those are mistaken and tedious techniques. So this technique records the student’s participation in classroom consequently and provide facility for teachers for obtaining the data of the student effectively using log to check in and out time

scholarly journals IOT Based Automated Attendance with Face Recognition System

2019 ◽  
Vol 8 (6S4) ◽  
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Recognition System ◽  
Raspberry Pi ◽  
Human Intervention ◽  
Student Attendance ◽  
Face Recognition System

Our Paper involves the student attendance and faculty attendance. The student attendance is marked by face recognition. For face detection and face recognition the raspberry pi. If the camera is connected to Raspberry pi USB port then only images will capture of the students who are available in the class for face detection. The captured images recognises with stored images then in that images we will recognize the faces of every student and according to thatattendance will be given to that subject class. This process is carried out for every class and students are given attendance accordingly. Faculty attendance is monitored with this project. A unique RFID card is given to the faculty, when faculty enters the classroom swipes the RFID card attendance will be marked with date and time. ESP8266 is used along with OLED to display the faculty attendance. We can mark the attendance at any time without any human Intervention.

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