scholarly journals Prevention of unauthorized door access using face recognition built with Haar Cascade Classifier and Histogram of Oriented Gradients

2020 ◽  
Author(s):  
Arun Kumar Nadikattu ◽  
Kundhan P ◽  
John Shahid Sk ◽  
Sunita Panda ◽  
Kamalanathan Chandran
Keyword(s):  
Face Recognition ◽  
Remote Monitoring ◽  
Cascade Classifier ◽  
Security Systems ◽  
Web Based ◽  
Traditional System ◽  
Novel Approach ◽  
Haar Cascade ◽  
Door Lock ◽  
Physically Challenged

With the emergence of Internet of Things (IoT) along with its development of advanced authentication, both security and remote monitoring have become imperative as well as essential, and the need for smarter security systems has only been growing. The traditional system needs an individual to use a key or an identification (ID) card or a password to access the security doors. However, they have many limitations such as keys can be forged, recreation of ID cards and passwords can be stolen. To overcome, the existing system issues, a novel approach is proposed with the design and development of face authenticated web-based smart door lock control system using facial recognition and remotely monitoring the door. In this proposed system OpenCVs self-trained Haar Cascade Classifier along with Histogram of Gradient is used for face Recognition. Door will be unlocked when users face is recognised else will remain closed. In case an unauthorised person is found, the time of intrusion and the intruders image will be captured and sent to a separate server on discord, so that the user or the admin can view them at their convenience. The main usage of this system is to assist users for improvement of the door security of sensitive locations by using face recognition and is also designed by considering the physically challenged persons also.

scholarly journals Development of a secured room access system based on face recognition using Raspberry Pi and Android based smartphone

2018 ◽  
Vol 197 ◽  
pp. 11008 ◽  
Author(s):  
Asep Najmurrokhman ◽  
Kusnandar Kusnandar ◽  
Arief Budiman Krama ◽  
Esmeralda Contessa Djamal ◽  
Robbi Rahim
Keyword(s):  
Face Recognition ◽  
Raspberry Pi ◽  
Cascade Classifier ◽  
Security Issues ◽  
Access System ◽  
The Face ◽  
Access Control System ◽  
Haar Cascade ◽  
Door Lock ◽  
Access Rights

Security issues are an important part of everyday life. A vital link in security chain is the identification of users who will enter the room. This paper describes the prototype of a secured room access control system based on face recognition. The system comprises a webcam to detect faces and a solenoid door lock for accessing the room. Every user detected by the webcam will be checked for compatibility with the database in the system. If the user has access rights then the solenoid door lock will open and the user can enter the room. Otherwise, the data will be sent to the master user via Android-based smartphone that installed certain applications. If the user is recognized by the master user, then the solenoid door lock will be opened through the signal sent from the smartphone. However, if the user is not recognized, then the buzzer will alert. The main control circuit on this system is Raspberry pi. The software used is OpenCV Library which is useful to display and process the image produced by webcam. In this paper, we employ Haar Cascade Classifier in an image processing of user face to render the face detection with high accuracy.

scholarly journals Physiological Traits (Face Recognition) Based Door Lock

2019 ◽  
Vol 8 (4) ◽  
pp. 5808-5812
Keyword(s):  
Face Recognition ◽  
Local Binary Pattern ◽  
Technological Advancement ◽  
Web Based ◽  
Prime Concern ◽  
New Development ◽  
Hardware Component ◽  
Door Lock ◽  
Live Image ◽  
Pattern Histogram

Security is now a prime concern for any individual in modern days. Theever-increasing graph of technological advancement in the field of Internet of things and other arenas have paved way for new development of smart web-based locking system which is based on face recognition for authentication. The proposed system uses a feature similar to Haar for the purpose of face detection and also Local Binary Pattern Histogram (LBPH). The project also extends its usability by sending live image of the guest which arrives and can even send a notification on the phone to the owner. The proposed system can be embedded along with other technologies to form a smart housing. The implementation of the project is done using Arduino board, python for programming, Open CV library is also included, and the hardware component also includes camera module for face recognition.

Human Face Recognition Applying Haar Cascade Classifier

2022 ◽  
pp. 143-157
Author(s):  
F. M. Javed Mehedi Shamrat ◽  
Anup Majumder ◽  
Probal Roy Antu ◽  
Saykot Kumar Barmon ◽  
Itisha Nowrin ◽  
...  
Keyword(s):  
Face Recognition ◽  
Human Face ◽  
Cascade Classifier ◽  
Human Face Recognition ◽  
Haar Cascade

scholarly journals Visitor/Intruder Monitoring System using Haar-cascade Classifier Algorithm

2020 ◽  
pp. 229-231
Author(s):  
Jenifa G ◽  
Yuvaraj N ◽  
SriPreethaa K R
Keyword(s):  
Machine Learning ◽  
Face Recognition ◽  
Monitoring System ◽  
Face Detection ◽  
Security System ◽  
Machine Learning Algorithms ◽  
Advanced Technology ◽  
Cascade Classifier ◽  
Home Security ◽  
Haar Cascade

Home security system plays a predominant role in the modern era. The purpose of the security systems is to protect the members of the family from intruders. The main idea behind this system is to provide security for residential areas. In today’s world securing our home takes a major role in the society. Surveillance from home to huge industries, plays a significant role in the fulfilment of our security. There are many machine learning algorithms for home security system but Haar-cascade classifier algorithm gives a better result when compared with other machine learning algorithm This system implements a face recognition and face detection using Haar-cascade classifier algorithm, OpenCV libraries are used for training and testing of the face detection process. In future, face recognition will be everywhere in the world. Face recognition is creating a magic in every field with its advanced technology. Visitor/Intruder monitoring system using Machine Learning is used to monitor the person and find whether the person is a known or unknown person from the captured picture. Here LBPH (Local Binary Pattern Histogram) Face Recognizer is used. After capturing the image, it is compared with the available dataset then their respective name and picture is sent to the specified email to alert the owner.

scholarly journals An Improved Local Binary Patterns Histograms Technique for Face Recognition for Real Time Applications

2019 ◽  
Vol 8 (2S7) ◽  
pp. 524-529 ◽  
Keyword(s):  
Face Recognition ◽  
Local Binary Patterns ◽  
Recognition System ◽  
Facial Features ◽  
Cascade Classifier ◽  
The Past ◽  
Face Recognition System ◽  
Unique System ◽  
Haar Cascade ◽  
Python Programming

Recently, face recognition and its applications has been considered as one of the image analysis most successful applications, especially over the past several years. Face Recognition is a unique system that can be used by using unique facial features for identification or verification of a person from a digital image. In a face recognition system, there are many technique that can be used. This paper provides an efficient of the Local Binary Patterns Histograms (LBPH) based technique provided by OpenCV library which is implemented in Python programming language which is well suitable for realistic scenarios. In this paper we also provide visual qualitative outcome with existing algorithm (Haar-cascade classifier and Local Binary Patterns Histograms (LBPH)). As a result, the proposed technique outperform better in terms of visual qualitative analysis.

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 Face Recognition using Haar Cascade Classifier

2021 ◽  
Vol 7 (01) ◽  
pp. 85-87
Author(s):  
Arnav Madan
Keyword(s):  
Machine Learning ◽  
Face Recognition ◽  
High Efficiency ◽  
Learning Technology ◽  
Cascade Classifier ◽  
Haar Cascade ◽  
Security Application

With development of machine learning technology many applications have been revolutionized which earlier usedto utilize high amoun to fresources. Face recognition is a crucial security application. Though this paper we present this application using optimized amount of resources and high efficiency.

scholarly journals Implementation of security system for bank using open CV and RFID

2018 ◽  
Vol 7 (2.7) ◽  
pp. 187 ◽  
Author(s):  
Kona Neeraja ◽  
Potu Rama Chandra Rao ◽  
Dr Suman Maloji ◽  
Dr Mohammed Ali Hussain
Keyword(s):  
Face Recognition ◽  
Banking Sector ◽  
Security Policies ◽  
Human Face ◽  
Cascade Classifier ◽  
Biometric System ◽  
Time Period ◽  
Proposed Model ◽  
Locker Room ◽  
Haar Cascade

Security is one of the major concerns in banking sector where we can adapt the latest techniques like face recognition and RFID we can provide better security policies. In this paper we have proposed a model with two major security techniques. The First method provides security for the locker room door by face recognition using OpenCV. Face recognition is a particular type of biometric system that can be used to analyze the obtained information and identify the user uniquely by the trained images. In this proposed model the images of customers are trained. A Microsoft Lifecam HD-3000 is placed outside the locker room. This camera detects the human face using Haar Cascade Classifier and recognizes a customer using LBPH Algorithm. If a trained customer tries to enter then door is unlocked. The customer name is uploaded to cloud. The second method provides security to the cashier cabin by using MFRC522 RFID Module which is very easy to access which consumes less time and more secured compared to the existing system. When an authorized tag is recognized the door is unlocked for certain time period and the userid is uploaded to the cloud. By using these two techniques we can provide security for locker room and cashier cabins in any banking sector.

Sign in / Sign up

Export Citation Format

Share Document