Plant Counting By Using k-NN Classification on UAVs Images

被引：0

作者：

Tavus, Mustafa Resit ^{[1
]}

Eker, Muhammed Emin ^{[1
]}

Senyer, Nurettin ^{[1
]}

Karabulut, Bunyamin ^{[1
]}

机构：

[1] Ondokuz Mayis Univ, Bilgisayar Muhendisligi Bolumu, Samsun, Turkey

来源：

2015 23RD SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | 2015年

关键词：

k-NN algorithm; plant counting; image processing;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：1058 / 1061

页数：4

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