Identification of Plant Textures in Agricultural Images by Principal Component Analysis

被引：8

作者：

Montalvo, Martin ^{[1
]}

Guijarro, Maria ^{[2
]}

Miguel Guerrero, Jose ^{[1
]}

Ribeiro, Angela ^{[3
]}

机构：

[1] Univ Complutense Madrid, Sch Comp Sci, Dept Software Engn & Artificial Intelligence, Madrid, Spain

[2] Univ Complutense Madrid, Sch Comp Sci, Dept Comp Architecture & Automat, Madrid, Spain

[3] UPM, CSIC, Ctr Automat & Robot, Madrid 28500, Spain

来源：

HYBRID ARTIFICIAL INTELLIGENT SYSTEMS | 2016年 / 9648卷

关键词：

Segmentation image; Principal component analysis; Thresholding; Agricultural images; Precision agriculture; WEEDS; COLOR; SEGMENTATION;

D O I：

10.1007/978-3-319-32034-2_33

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In precision agriculture the extraction of green parts is a very important task. One of the biggest issues, when it comes to computer vision, is image segmentation, which has motivated the research conducted in this work. Our goal is the segmentation of vegetative and soil parts in the images. For this proposal a novel method of segmentation is defined in which different vegetation indices are calculated and through the reduction of components by principal component analysis (PCA) we obtain an enhanced greyscale image. Finally, by Otsu thresholding, we binarize the grayscale image isolating the green parts from the other elements in the image.

引用

页码：391 / 401

页数：11

共 24 条

[1] Classification of crops and weeds from digital images: A support vector machine approach [J].

Ahmed, Faisal ;

Al-Mamun, Hawlader Abdullah ;

Bari, A. S. M. Hossain ;

Hossain, Emam ;

Kwan, Paul .

CROP PROTECTION, 2012, 40 :98-104

[2]

Anderson T. W., 1962, INTRO MULTIVARIATE S

[3]

Davies G., 1998, PRECISION AGR INTRO

[4] Crop/weed discrimination in perspective agronomic images [J].

Gee, Ch. ;

Bossu, J. ;

Jones, G. ;

Truchetet, F. .

COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2008, 60 (01) :49-59

[5] Support Vector Machines for crop/weeds identification in maize fields [J].

Guerrero, J. M. ;

Pajares, G. ;

Montalvo, M. ;

Romeo, J. ;

Guijarro, M. .

EXPERT SYSTEMS WITH APPLICATIONS, 2012, 39 (12) :11149-11155

[6] Automatic segmentation of relevant textures in agricultural images [J].

Guijarro, M. ;

Pajares, G. ;

Riomoros, I. ;

Herrera, P. J. ;

Burgos-Artizzu, X. P. ;

Ribeiro, A. .

COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2011, 75 (01) :75-83

[7] Automated crop and weed monitoring in widely spaced cereals [J].

Hague, T. ;

Tillett, N. D. ;

Wheeler, H. .

PRECISION AGRICULTURE, 2006, 7 (01) :21-32

[8]

Hanh N.T.T., 2013, APPL PRINCIPAL COMPO

[9] Crop growth estimation system using machine vision [J].

Kataoka, T ;

Kaneko, T ;

Okamoto, H ;

Hata, S .

PROCEEDINGS OF THE 2003 IEEE/ASME INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT MECHATRONICS (AIM 2003), VOLS 1 AND 2, 2003, :1079-1083

[10]

MathWorks, ACC PAC ENG SCI

← 1 2 3 →