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.
Keywords: image transformation, embedded system, FSVM, YUV format
Author: Barlian Henryranu Prasetio
Journal Code: jptkomputergg150118

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