Radon transform based real-time weed classifier

被引：0

作者：

Haq, Muhammad Inam ul ^{[1
]}

Naeem, Abdul Muhamin ^{[2
]}

Ahmad, Irshad ^{[3
]}

Islam, Muhammad ^{[4
]}

机构：

[1] Ctr IT, Inst Management Sci, Peshawar, Pakistan

[2] Farabi Coll Peshawar, Dept Comp Sci, Peshawar, Pakistan

[3] Islamia Coll Peshawar, Dept Comp Sci, Peshawar, Pakistan

[4] FASTNU, Dept Telecommun Engn, Peshawar, Pakistan

来源：

COMPUTER GRAPHICS, IMAGING AND VISUALISATION: NEW ADVANCES | 2007年

关键词：

ecology; image processing; radon transform; real-time recognition; weed detection;

D O I：

暂无

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

A machine vision system to detect and discriminate crop and weed plants in a commercial agricultural environment was developed and tested. Images are acquired in agricultural fields under natural illumination were studied extensively, and a weed classifier based on Radon Transform is developed. This classifier is specifically developed to classify images into broad (having broad leaves) and narrow (having narrow leaves) classes for real-time selective herbicide application. The developed system has been tested on weeds in the lab; the results shows reliable performance and significantly less computational efforts on images of weeds taken under varying field conditions. The analysis of the results shows over 93.5% classification accuracy over a database of 200 sample images with 100 samples from each category of weeds.

引用

页码：245 / +

页数：3

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