DocumentCode
714465
Title
Plant counting by using k-NN classification on UAVs images
Author
Tavus, Mustafa Resit ; Eker, Muhammed Emin ; Senyer, Nurettin ; Karabulut, Bunyamin
Author_Institution
Bilgisayar Muhendisligi Bolumu, Ondokuz Mayis Univ., Samsun, Turkey
fYear
2015
fDate
16-19 May 2015
Firstpage
1058
Lastpage
1061
Abstract
In this study, Plant Counting was implemented by appling k-NN classification to images obtained from Unnamed Air Vehicle (UAV). Firstly, The images were subjected to erosion process by transforming different colour levels. The objects in the images were classified as plant and soil by means of k-NN classification. It was observed that plants can be counted with 87,7% of accuracy and 86,6% of precision by being performed last processing of the morphology of the binary image.
Keywords
autonomous aerial vehicles; image classification; pattern recognition; surveying; UAV images; binary image; k-NN classification; plant counting; unnamed air vehicle; Accuracy; Image color analysis; Remote sensing; Soil; Vegetation; Vehicles; image processing; k-NN algorithm; plant counting;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing and Communications Applications Conference (SIU), 2015 23th
Conference_Location
Malatya
Type
conf
DOI
10.1109/SIU.2015.7130015
Filename
7130015
Link To Document