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Applications of Image Processing in Agriculture: A Survey

by Anup Vibhute, S. K. Bodhe
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 52 - Number 2
Year of Publication: 2012
Authors: Anup Vibhute, S. K. Bodhe
10.5120/8176-1495

Anup Vibhute, S. K. Bodhe . Applications of Image Processing in Agriculture: A Survey. International Journal of Computer Applications. 52, 2 ( August 2012), 34-40. DOI=10.5120/8176-1495

@article{ 10.5120/8176-1495,
author = { Anup Vibhute, S. K. Bodhe },
title = { Applications of Image Processing in Agriculture: A Survey },
journal = { International Journal of Computer Applications },
issue_date = { August 2012 },
volume = { 52 },
number = { 2 },
month = { August },
year = { 2012 },
issn = { 0975-8887 },
pages = { 34-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume52/number2/8176-1495/ },
doi = { 10.5120/8176-1495 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:51:16.267822+05:30
%A Anup Vibhute
%A S. K. Bodhe
%T Applications of Image Processing in Agriculture: A Survey
%J International Journal of Computer Applications
%@ 0975-8887
%V 52
%N 2
%P 34-40
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image processing has been proved to be effective tool for analysis in various fields and applications. Agriculture sector where the parameters like canopy, yield, quality of product were the important measures from the farmers' point of view. Many times expert advice may not be affordable, majority times the availability of expert and their services may consume time. Image processing along with availability of communication network can change the situation of getting the expert advice well within time and at affordable cost since image processing was the effective tool for analysis of parameters. This paper intends to focus on the survey of application of image processing in agriculture field such as imaging techniques, weed detection and fruit grading. The analysis of the parameters has proved to be accurate and less time consuming as compared to traditional methods. Application of image processing can improve decision making for vegetation measurement, irrigation, fruit sorting, etc.

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Index Terms

Computer Science
Information Sciences

Keywords

agronomy Remote Sensing hyper-spectral fuzzy logic neural network Genetic algorithm wavelet PCA fruit grading

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