Abstract:
The increase in the number of elderly people in
Indonesia is quite high. One thing that must be considered is
that there are elderly people who live alone without family at
home. This has a high risk, especially for biological aspects,
that is, if something unwanted happens, one of them is falling,
so a fall detection system is needed to monitor the condition of
the elderly at home. In this study, a human fall detection
system has been designed using image processing with input
from the camera to detect falls using the Human Posture
Recognition Algorithm. To obtain digital images using the
Image Acquisition technique and using the Human Posture
Recognition Algorithm algorithm to detect falls in the video. In
this research, a human fall detection system has been designed
using image processing with input from the camera, the Motion
History Image (MHI) method and the Approximated Ellipse.
This method will produce parameter values C_motion,
Sigma_theta, and Sigma_rho which will be used as a reference
for fall detectors. The results of this study indicate an accuracy
of 95.33% for data on conditions of falling or not falling.
