Intruder Detection Using Face Recognition for Home and Pet Security System (original) (raw)
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2020
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...
ARTIFICIALLY INTELLIGENT FACE DETECTION AND INVESTIGATION SYSTEM BASED ON OPENCV-FINAL-THESIS-2019
ARTIFICIALLY INTELLIGENT FACE DETECTION AND INVESTIGATION SYSTEM BASED ON OPENCV-FINAL-THESIS-2019, 2019
This research project aimed at designing and developing an artificially intelligent forensic face detection and identification system. The researchers used the Design science approach as the methodology. System requirements were collected by using interviews and document reviews for the artificially intelligent forensic face identification system. Data was analyzed using Microsoft word 2010. The findings from data analysis were used to design the core functionalities of the system. For system design, the researchers used Microsoft Visio 2007 to model architectural designs and data flow diagrams that were used to develop the system. Implementation of the project the researchers used the following technologies: Python, OpenCV, and IDL As a result, the researchers developed a system to help combat the abnormal increase in crime rates and a number of criminals has caused a great impact of insecurity in the nation. Crime prevention and criminal identification are the primary issue-challenges before security organizations because property and life protection are basic concerns. Physical human security interventions are limited, hence the advent of security technology specifically cameras especially CCTV that have been installed in many public and private areas to ensure surveillance. Footage from the CCTV can be used to detect, Recognize &identify wanted criminals on scene. In this paper, an automated facial recognition system with a criminal database was proposed using known Haar feature-based cascade classifier. This system will be able to detect and recognize faces in real-time. Accurate identification of faces is still a challenging task though the Viola-Jones framework has been widely used by researchers in order to detect the faces and objects in a given image. Face detection classifiers are shared by public communities, such as OpenCV, Tensor-Flow. Keywords: Criminal Identification; CCTV; facial recognition; Haar classifier; real-time; Viola-Jones; OpenCV.
Real time face recognition of video surveillance system using haar cascade classifier
2021
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 programm...
IJSRST173180 | Human Face Detection System for Door Security
Face detection is challenging problems up to date; there is no technique that provides a robust solution to all situations. This paper presents a new technique for human face detection. Face detection is concerned with finding real image. Most face detection algorithms are designed in the software domain and have a high detection rate, but they often require several seconds to detect faces in a single image, a processing speed that is insufficient for realtime applications. This describes a simple and easy hardware implementation of face detection system using Raspberry Pi, which itself is a minicomputer of a credit card size. The system will program using Python programming language. Both real time face detection and detection from specific images, i.e. Object Recognition, will be carried out and the proposed system will test across various standard face databases, with and without noise and blurring effects.
Facial Recognition Based Automated Door
IRJCS:: AM Publications,India, 2024
To ensure the accuracy and efficiency of intruder identification, the proposed method is combined with Haar classifier technology for face detection. When someone comes to the door, the Pi camera captures the image and starts the face detection process. In this research, we implement a facial recognition component to capture human images, comparing them with stored data in a database. Upon a match with an authorized individual, the system unlocks the door through an electromagnetic lock. The demand for a rapid and accurate face recognition system persists, continuously evolving to swiftly identify intruders and restrict unauthorized access to highly secure areas, thereby reducing human error. Facial recognition stands as a crucial component within secure systems, surpassing biometric pattern recognition methods, and finds widespread application across various domains.
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika)
Some people are very easy to open the door lock with just a small wire. This causes the house to be vulnerable to burglary and theft. In previous studies, there were still shortcomings such as the accuracy of facial recognition was not good, the time for the facial recognition process was very long and no action was taken if the camera caught an unknown person. This raises the need for solutions related to security systems that can monitor homes when something suspicious happens so that it can be prevented immediately. This study aims to create a home door security system using ESP32-CAM as face recognition. This face recognition can unlock the door automatically and if someone is caught on camera who is not known, the system will send a notification to the owner to follow up on this. The results of the face detection test using the Haar Cascade Classifier method that can distinguish a known face and an unknown face. The results of facial accuracy at a distance of 30 cm, 40 cm, and ...
Surveillance System for Intruder Detection Using Facial Recognition
Intelligent Computing and Networking
Facial recognition system is used widely to identify and verify the person's face from image or video source. With the continuous expansion of the surveillance system, surveillance cameras not only bring convenience, but also produce a massive amount of monitoring data, which poses huge challenges to storage, analytics, and retrieval. The smart monitoring system equipped with intelligent video analytics technology can monitor as well as pre-alarm abnormal events or behaviors. Here, propose system will detect the intruder and inform the security within seconds. The Nvidia Jetson Nano board will be used to compute convolutional neural network algorithm for the facial recognition process. The basic idea will be to use this system where a database can be stored of the existing faces. The system will then take the data from the surveillance camera and run facial recognition algorithm on it. It will match all the faces with the ones already stored in the database and if it finds any face which is new, it will send an alert to the security personnel. This will help to increase the security of the place where there are many people gathered at a time, for example, schools, colleges, universities, etc.
Implementation of Facial Recognition for Home Security Systems
International Journal of Engineering & Technology, 2018
In this paper, the design and development of a home security system has been detailed which uses facial recognition to conform the identity of the visitor and taking various security measures when an unauthorized personnel tries accessing the door. It demonstrates the implementation of one of the most popular algorithm for face recognition i.e. principal component analysis for the purpose of security door access. Since PCA converts the images into a lower dimension without losing on the important features, a huge set of training data can be taken. If the face is recognized as known then the door will open otherwise it will be categorized as unknown and the microcontroller (Arduino Uno) will command the buzzer to start ringing.
Face Detection System for Smart Security Application
Advances in Transdisciplinary Engineering
Face detection and recognition can be applied to numerous fields, and it is primarily used for improving security. For security purposes, facial recognition is considered to be the most reliable and accurate technology for identifying a person. Improvements in security systems can be made through this technology without causing any inconvenience. This article discusses several systems, such as smart home security systems, autonomous face detection systems, automotive security-based systems, face detection for surveillance applications, and multi-face recognition systems. Various detection mechanisms include such as Local Binary Pattern Histogram (LBPH), Support Vector Machine (SVM), AdaBoost learning algorithm, Haar Classifier Algorithm, and Principal component Analysis (PCA). A detailed study is carried out with these advanced techniques and their advantages, disadvantages and accuracies are compared and contrasted. According to the investigations, the Haar classifier appears to be...
Real-Time Face Detection Security System using Haar Classifier Method
International Journal of Trend in Scientific Research and Development, 2018
Face Detection is concerned with finding whether or not there are any faces in a given images. Security and surveillance are the two important aspects of human being. Face detection is very important because it is not being safe in human environment. So, F Detection Security System is essential between individual in life. In the modern world everything is changed to provide a better life. So we were decided to develop the Real Time Face detection system. The importance of the face detection as it is esse surveillance and real user interfaces security to the country. Face differ in skin colour, nose, eyebrows, chin between different people in humanity. In this paper we effort is to develop system about face detection security system in the real time.