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Non-Destructive Quality Analysis of JIRASAR Oryza Sativa SSP Indica (Indian Rice) using Feed Forward Neural Network

by Niky K. Jain, Samrat O. Khanna, Chetna K. Shah
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 172 - Number 7
Year of Publication: 2017
Authors: Niky K. Jain, Samrat O. Khanna, Chetna K. Shah
10.5120/ijca2017915186

Niky K. Jain, Samrat O. Khanna, Chetna K. Shah . Non-Destructive Quality Analysis of JIRASAR Oryza Sativa SSP Indica (Indian Rice) using Feed Forward Neural Network. International Journal of Computer Applications. 172, 7 ( Aug 2017), 35-39. DOI=10.5120/ijca2017915186

@article{ 10.5120/ijca2017915186,
author = { Niky K. Jain, Samrat O. Khanna, Chetna K. Shah },
title = { Non-Destructive Quality Analysis of JIRASAR Oryza Sativa SSP Indica (Indian Rice) using Feed Forward Neural Network },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2017 },
volume = { 172 },
number = { 7 },
month = { Aug },
year = { 2017 },
issn = { 0975-8887 },
pages = { 35-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume172/number7/28266-2017915186/ },
doi = { 10.5120/ijca2017915186 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:19:45.034870+05:30
%A Niky K. Jain
%A Samrat O. Khanna
%A Chetna K. Shah
%T Non-Destructive Quality Analysis of JIRASAR Oryza Sativa SSP Indica (Indian Rice) using Feed Forward Neural Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 172
%N 7
%P 35-39
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The Carrying out compelling and reasonable agriculture product has turned into an important issue in recent years. Agricultural production needs to stay aware with an ever-increasing population. A key to this is the utilization of present day strategies (for precision agriculture) to exploit the quality in the market. Classification of rice seeds from the exposed human hands is neither savvy nor prescribed. The automatic grading for examination of quality has turned into the need of great importance. This paper prescribes an extra way to deal with quality specialists for the quality investigation of INDIAN JIRASAR Rice using computer vision and soft computing techniques. Computer Vision gives a grading methodology, non-destructive technique, along with multi-layer feed forward neural networking which achieves high degree of quality than human vision inspection.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Computer Vision Soft Computing technique digital image processing Indian Jirasar rice seeds non-destructive.

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