Open AccessHuman Detection and Identification for Home Monitoring System
Author(s) -
Dedy Arisandi,
Marischa Elveny,
Rusnai Rahayu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1898/1/012026
Subject(s) - computer science , histogram , object (grammar) , artificial intelligence , computer vision , object detection , histogram of oriented gradients , process (computing) , identification (biology) , computer security , pattern recognition (psychology) , botany , image (mathematics) , biology , operating system
Currently, a monitoring system is needed to improve security and productivity in various sectors, for example in public services such as education centers, offices, banking, stations, roads, and the industrial sector. With a monitoring system, public service activities can be well monitored. Apart from public services, a home surveillance system can be implemented, making it easier for household members to monitor home security. The monitoring system camera will record the object, the human object detection process is carried out with the Histogram of Oriented Gradient, after the object is detected, the facial recognition process of the object is carried out whether it is a member of the house or not by using Learning Vector Quantization. If the object is not a member of the house, the system will send a notification in the form of a photo of the object’s face to the user’s email. For object detection with the Histogram of Oriented Gradient, an average accuracy of 90% is obtained and Learning Vector Quantization for facial recognition is 85%.