scholarly journals The IMPLEMENTATION OF SYSTEM DOOR ACCES USING FACE RECOGNITION AND FINGER PRINT FOR MUNITIONS WAREHOUSE WITH A BASE HAAR CASSCADE

2021 ◽  
Vol 2 (Oktober) ◽  
pp. 75-81
Author(s):  
M. Sofyan Asari ◽  
Desyderius Minggu ◽  
Isa Mahfudi
Keyword(s):  
Face Recognition ◽  
Experimental Method ◽  
Real Time ◽  
Quantitative Data ◽  
Research Method ◽  
Technological Innovations ◽  
Detection Distance ◽  
Haar Cascade ◽  
The Military ◽  
Limit Access

Abstract: Technology in the military world has been growing with the existence of technological innovations that are used to secure munitions warehouses. This is done to reduce the negligence of the munitions warehouse guard personnel if they lose the key from the munitions warehouse it can be monitored in real-time to find out who is around the munitions warehouse door. Thus, face recognition and fingerprint technology were created as a system for securing munitions warehouses, as well as the function is to be a CCTV. So, they can be monitored in real-time. This research method uses an experimental method to obtain quantitative data to prove the hypothesis data that use the Haar Cascade. The results of this study indicate that this security system has a very important role to limit access to and from the munitions warehouse and reduce the occurrence of theft or misuse of munitions. In the tests carried out, the minimum detection distance was 20 cm and the maximum distance that was able to detect was 110 cm. this is influenced by the focus of the camera and testing of the intensity of light in the morning, afternoon, evening, and night can be detected except detection at night without light and must use a fingerprint.

scholarly journals The IMPLEMENTATION OF TRACKING SYSTEM IN THE REAL TIME OF ANDROID FOR SENDING PERSONEL COORDINATION BASED ON MQTT.

2020 ◽  
Vol 2 (Oktober) ◽  
pp. 29-36
Author(s):  
Agus Faesol ◽  
Imam Ashar ◽  
Gatut Yulisusianto
Keyword(s):  
Real Time ◽  
Process Improvement ◽  
Communication Technology ◽  
Research Method ◽  
Tracking System ◽  
The World ◽  
Real Time Tracking ◽  
Access Rights ◽  
Point Data ◽  
The Military

Abstract: In the world of technology that is increasing, then as humans we will not be separated from the process improvement that occurs. From year to year, it is certain that this increase will certainly. Increasingly rapidly occurring in communication technology. Communication technology has also penetrated the military world, especially in MQTT-based communications. In this research, MQTT-based technology is applied to implement real time tracking system on android. This system is used to send the longitude and latitude coordinates of the personnel so that these points can be known directly via android. From this pure experimental research method, the coordinate point data will continue to be monitored and the existence can be known continuously. This system is designed on a VPS server or Virtual Private Server, so that all devices even though none of the networks can communicate with  each  other  as  long  as  they  have  access  rights  for application user.

A Real-time Face Recognition Smart Attendance System with Haar Cascade Classifiers

2021 ◽  
Author(s):  
Rupak Bairagi ◽  
Remon Ahmed ◽  
Sadia Afrin Tisha ◽  
Md. Sumon Sarder ◽  
Md. Sabiqul Islam ◽  
...  
Keyword(s):  
Face Recognition ◽  
Real Time ◽  
Cascade Classifiers ◽  
Haar Cascade ◽  
Haar Cascade Classifiers

scholarly journals Real Time Face Recognition in Group Images using LBPH

2019 ◽  
Vol 8 (2) ◽  
pp. 1362-1367
Keyword(s):  
Machine Learning ◽  
Computer Vision ◽  
Face Recognition ◽  
Real Time ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
Testing Dataset ◽  
Negative Images ◽  
The Face ◽  
Haar Cascade

Face recognition is a beneficial work in computer vision based applications. The goal of the proposed system is to provide complete face recognitions system capable of working a group of images. The faces are detected and verified the identity of an individual using a machine learning algorithm. The haar cascade detects the face from a group of images for training and testing dataset. The dataset contained positive and negative images for training and testing. The LBPH algorithm recognizes the faces from input images. The proposed system detects and recognizes faces with 98% accuracy

scholarly journals Multi-Object Face Recognition Using Local Binary Pattern Histogram and Haar Cascade Classifier on Low-Resolution Images

2021 ◽  
Vol 11 (1) ◽  
pp. 45-58
Author(s):  
R. Rizal Isnanto ◽  
Adian Rochim ◽  
Dania Eridani ◽  
Guntur Cahyono
Keyword(s):  
Face Recognition ◽  
Real Time ◽  
Local Binary Pattern ◽  
Video Data ◽  
Cascade Classifier ◽  
Low Resolution ◽  
The Face ◽  
Haar Cascade ◽  
Pattern Histogram ◽  
Low Resolution Images

This study aims to build a face recognition prototype that can recognize multiple face objects within one frame. The proposed method uses a local binary pattern histogram and Haar cascade classifier on low-resolution images. The lowest data resolution used in this study was 76 × 76 pixels and the highest was 156 × 156 pixels. The face images were preprocessed using the histogram equalization and median filtering. The face recognition prototype proposed successfully recognized four face objects in one frame. The results obtained were comparable for local and real-time stream video data for testing. The RR obtained with the local data test was 99.67%, which indicates better performance in recognizing 75 frames for each object, compared to the 92.67% RR for the real-time data stream. In comparison to the results obtained in previous works, it can be concluded that the proposed method yields the highest RR of 99.67%.

scholarly journals Implementation of Aadhaar Verified, face Recognition based Security Surveillance

2020 ◽  
Vol 9 (9) ◽  
pp. 415-420
Keyword(s):  
Face Recognition ◽  
Real Time ◽  
Human Face ◽  
Element Determination ◽  
Python Language ◽  
Cascade Calculation ◽  
Haar Cascade ◽  
Two Phases ◽  
Security Surveillance ◽  
Human Faces

Security and Authentication is a basic piece of any industry. In Real time, Human face acknowledgment can be acted in two phases, for example, Face discovery and Face acknowledgment. This paper actualizes "Haar-Cascade calculation" to distinguish human faces which are sorted out in Open CV by Python language. Gathering with other existing calculations, this classifier creates a high acknowledgment rate even with shifting articulations, effective element determination and low combination of bogus positive highlights. Haar highlight based course classifier framework uses just 200 highlights out of 6000 highlights to yield an acknowledgment pace of 85-95%.

scholarly journals Real time Face Detection and Optimal Face Mapping for Online Classes

2022 ◽  
Vol 2161 (1) ◽  
pp. 012063
Author(s):  
MCP Archana ◽  
CK Nitish ◽  
Sandhya Harikumar
Keyword(s):  
Face Recognition ◽  
Real Time ◽  
Face Detection ◽  
Local Binary Pattern ◽  
Online Classes ◽  
Web Based ◽  
Online Classrooms ◽  
Face Detection And Recognition ◽  
Haar Cascade ◽  
Improved Accuracy

Abstract The main objective of this paper is to provide a web-based tool for identifying faces in a real-time environment, such as Online Classes. Face recognition in real-time is now a fascinating field with an ever-increasing challenge such as light variations, occlusion, variation in facial expressions, etc. During the current pandemic scenario of COVID-19, the demand for online classrooms has rapidly increased. This has escalated the need for a real-time, economic, simple, and convenient way to track the attendance of the students in a live classroom. This paper addresses the aforementioned issue by proposing a real-time online attendance system. Two alternative face recognition algorithms are perceived in order to develop the tool for realtime face detection and recognition with improved accuracy. The algorithms adopted are Local Binary Pattern Histogram(LBPH) and Convolutional Neural Network (CNN) for face recognition as well as Haar cascade classifier with boosting for face detection. Experimental results show that CNN with an accuracy of 95% is better in this context than LBPH that yields an accuracy of 78%.

scholarly journals Real time face recognition of video surveillance system using haar cascade classifier

2021 ◽  
Vol 21 (3) ◽  
pp. 1389
Author(s):  
Adlan Hakim Ahmad ◽  
Sharifah Saon ◽  
Abd Kadir Mahamad ◽  
Cahyo Darujati ◽  
Sri Wiwoho Mudjanarko ◽  
...  
Keyword(s):  
Face Recognition ◽  
Real Time ◽  
Video Surveillance ◽  
Surveillance System ◽  
Raspberry Pi ◽  
Video Surveillance System ◽  
Cascade Classifier ◽  
Camera System ◽  
Surveillance Camera ◽  
Haar Cascade

<div>This project investigates the use of face recognition for a surveillance system. The normal video surveillance system uses in closed-circuit television (CCTV) to record video for security purpose. It is used to identify the identity of a person through their appearances on the recorded video, manually. Today’s video surveillance camera system usually not occupied with a face recognition system. With some modification, a surveillance camera system can be used as face detection and recognition that can be done in real-time. The proposed system makes use of surveillance camera system that can identify the identity of a person automatically by using face recognition of Haar cascade classifier. The hardware used for this project were Raspberry Pi as a processor and Pi Camera as a camera module. The development of this project consist of three main phases which were data gathering, training recognizer, and face recognition process. All three phases have been executed using Python programming and OpenCV library, which have been performed in a Raspbian operation system. From the result, the proposed system successfully displays the output result of human face recognition, with facial angle within ±40°, in medium and normal light condition, and within a distance of 0.4 to 1.2 meter. Targeted image are allowed to wear face accessory as long as not covering the face structure. In conclusion, this system considered, can reduce the cost of manpower in order to identify the identity of a person in real time situation.</div>

Real Time Person Recognition and Attendance Marking Using Holistic Based Approach

2017 ◽  
Vol 7 (7) ◽  
pp. 302
Author(s):  
Reshma P ◽  
Muneer VK ◽  
Muhammed Ilyas P
Keyword(s):  
Face Recognition ◽  
Real Time ◽  
High Accuracy ◽  
Efficient Technique ◽  
Human Face ◽  
Traditional Methods ◽  
Person Recognition ◽  
The Face

Face recognition is a challenging task for the researches. It is very useful for personal verification and recognition and also it is very difficult to implement due to all different situation that a human face can be found. This system makes use of the face recognition approach for the computerized attendance marking of students or employees in the room environment without lectures intervention or the employee. This system is very efficient and requires very less maintenance compared to the traditional methods. Among existing methods PCA is the most efficient technique. In this project Holistic based approach is adapted. The system is implemented using MATLAB and provides high accuracy.

State-Minority Contestations in Post-colonial Sri Lanka

2019 ◽  
Vol 9 (4) ◽  
pp. 157-165
Author(s):  
Mansoor Mohamed Fazil
Keyword(s):  
Qualitative Research ◽  
Sri Lanka ◽  
Research Method ◽  
The State ◽  
Social Forces ◽  
Social Force ◽  
State Structure ◽  
Post Colonial ◽  
State And Society ◽  
The Military

Abstract This research focuses on the issue of state-minority contestations involving transforming and reconstituting each other in post-independent Sri Lanka. This study uses a qualitative research method that involves critical categories of analysis. Migdal’s theory of state-in-society was applied because it provides an effective conceptual framework to analyse and explain the data. The results indicate that the unitary state structure and discriminatory policies contributed to the formation of a minority militant social force (the Liberation Tigers of Tamil Eelam – The LTTE) which fought with the state to form a separate state. The several factors that backed to the defeat of the LTTE in 2009 by the military of the state. This defeat has appreciably weakened the Tamil minority. This study also reveals that contestations between different social forces within society, within the state, and between the state and society in Sri Lanka still prevail, hampering the promulgation of inclusive policies. This study concludes that inclusive policies are imperative to end state minority contestations in Sri Lanka.

Pengaruh Penggunaan Media Belajar dan Minat Belajar terhadap Hasil Belajar Matematika (Eksperimen pada Siswa Kelas XI IPA SMA Negeri 8 Kota Tangerang Selatan Tahun Pelajaran 2010 / 2011)

2011 ◽  
Vol 1 (1) ◽  
Author(s):  
Tatan Zenal Mutakin ◽  
Teti Sumiati
Keyword(s):  
Factor Analysis ◽  
Experimental Method ◽  
Learning Outcomes ◽  
Research Method ◽  
Media Use ◽  
Mathematics Learning ◽  
Mathematics Students ◽  
Learning Mathematics

<p>The research is an experiment conducted in SMA Negeri 8 Tangerang City, Banten, on the influence of learning and use of media interest in learning of mathematics learning outcomes. The purpose of this study was to analyze the <br />influence of media use to learn and interest in learning mathematics learning <br />outcomes. (Experiment In Student Class XI IPA SMAN 8 Tangerang City Year <br />Lesson 2010/2011). The research method used is an experimental method using <br />the technique "factor analysis" with "Two Way Anova", aided by SPSS version <br />15.0. The results of the analysis studies suggest that: 1) There is the media's <br />influence on the learning outcomes of mathematics learning, 2) There is interest <br />in studying the influence on the results of studying mathematics, and 3) There is no interaction between the learning outcomes of students with interest in learning mathematics students. </p>

Sign in / Sign up

Export Citation Format

Share Document