Earth Image Classification Design Using Unmanned Aerial Vehicle
Abstract: The research aims to
build software that can perform the classification of earth image from UAV (Unmanned
Aerial Vehicle) monitoring. The Image converted into YUV format then classified
using Fuzzy Support Vector Machine (FSVM). UAVs will be used for monitoring as
follows: (1) the control station, which used to send or receive data, and
display the data in graphical form, (2) payload, camera captured images and
send to the control station, (3) communication system using TCP/IP protocol,
and (4) UAV, using X650 quad copter products. The image of the monitoring
carried out on the UAV sized 256 x 256 pixels with 450 training data. It is
16x16 pixel image data. Tests performed to classify the image into 3 classes,
namely agricultural area, residential area, and water area. The highest
accuracy value of 77.69% obtained by the number of training data as much as
375.
Author: Barlian Henryranu
Prasetio
Journal Code: jptkomputergg150118
