Perancangan Sistem Keamanan Brangkas Menggunakan Pengenalan Wajah Berbasis Android

The level of security in terms of access is one of the main priorities of everyone to improve the security system that feels the need for improvement following the development of modern technology. This study discusses a security system using Android-based face recognition. The aim of this research is that the safe safety system has a better level of security than the previous system. The initial stage to build this system, the authors do the literature data collection stage as a basis for the theory and system development methods used by software designers before is the waterfall method, in general this method is divided into several stages, including: Analysis, Design, Program Code and Unit Testing. For the method used in the research of this system is the eigenfaces algorithm method for the detection of facial objects in the initial process of image training. As well as the Local Binary Patterns algorithm method and Histrogram Equalization at the stage of reading the user's face recognition image accurately which has an accuracy of face reading up to 95.56%. The results of the user's face data will be processed in Wemos D1 and the data will be sent and stored in a database. The results of data from face recognition data will be used again as user data to open the safe. The conclusion, the system can read the user's face in real time and can work well for safe security systems

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Face recognition using viola-jones depending on python

Indonesian Journal of Electrical Engineering and Computer Science ◽

10.11591/ijeecs.v20.i3.pp1513-1521 ◽

2020 ◽

Vol 20 (3) ◽

pp. 1513

Author(s):

Khansaa Dheyaa Ismael ◽

Stanciu Irina

Keyword(s):

Computer Vision ◽

Face Recognition ◽

Facial Recognition ◽

Local Binary Patterns ◽

Recognition System ◽

Security System ◽

Software System ◽

Human Face ◽

Smart Buildings ◽

Smart Building

In this paper, the proposed software system based on face recognition the proposed system can be implemented in the smart building or any VIP building need security interring in general, The human face will be recognized from a stream of pictures or video feed, this technology recognizes the person according to the specific algorithm, the algorithm that employed in this paper is the Viola–Jones object detection framework by using Python. The task of the proposed facial recognition system consists of two steps, the first one was detected the human face from live video using the webcamera in the computer, and the second step recognizes if this face allowed to enter the building or not by comparing it with the existing database, the two steps depending on the OpenCV python by importing cv2 method for detecting the human face, the frames can be read or written to file with the cv2.imread and cv2.imwrite functions respectively Finally, this proposed software system can be used to control access in smart buildings as a rule and the advancement of techniques connected around there, Providing a security system is one of the most important features must be achieved in the smart buildings, this proposed system can be used as an application in a smart building as a security system. Face recognition is one of the most important applications using today for practical facial recognition, The proposed software system, depending on using OpenCV (Open Source Computer Vision) is a popular computer vision library, in 1999 this library started by Intel. The platform library sets its focus on real-time image processing and includes patent-free implementations of the latest computer vision algorithms. OpenCV 2.3.1 now comes with a programming interface to C, C++, Python, and Android. OpenCV library of python, the three algorithms that will be used in this proposed system. The currently available algorithms are:Eigenfaces → createEigenFaceRecognizer()Fisherfaces → createFisherFaceRecognizer()Local Binary Patterns Histograms → createLBPHFaceRecognizer()Finally the proposed system provide entering to the building just for the authorized person according to face recognition algorithem.

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Improvised Guard for Next Level Security Automated Vehicle Security System using Artificial Intelligence and Convolutional Neural Network

Volume 5 - 2020, Issue 9 - September - International Journal of Innovative Science and Research Technology ◽

10.38124/ijisrt20jul121 ◽

2020 ◽

Vol 5 (7) ◽

pp. 84-88

Author(s):

Joel M John ◽

Noel Phillip Issac ◽

Jerin Thomas ◽

Subin Alexander ◽

Syamraj B S

Keyword(s):

Neural Network ◽

Face Recognition ◽

Security System ◽

Vehicle Model ◽

Deep Convolutional Neural Networks ◽

Automated Vehicle ◽

The Core ◽

Core Technology ◽

User Data ◽

Vehicle Security

This paper details fully automated vehicle security system involving vehicle model, make detection, driver face recognition and parking system guided by a virtual assistant. The core technology of the system is built using a sequence of deep Convolutional Neural Networks (CNNs). This system performs face recognition of the driver and vehicle model, make detection and permit access by opening barrier gate. This allows bigger organizations to control and monitor vehicle traffic as well as gain user data for security purpose. For quantitive analysis, we show that our system outperforms the leading vehicle security system. Proposed paper project website is also available at http://www.astound.ga/igns.

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