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Reseach Article

Graphical User Interface Approach for Quality Evaluation of Indian Rice

by Niky K. Jain, Samrat O. Khanna, Chetna K. Shah
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 176 - Number 4
Year of Publication: 2017
Authors: Niky K. Jain, Samrat O. Khanna, Chetna K. Shah
10.5120/ijca2017915562

Niky K. Jain, Samrat O. Khanna, Chetna K. Shah . Graphical User Interface Approach for Quality Evaluation of Indian Rice. International Journal of Computer Applications. 176, 4 ( Oct 2017), 12-17. DOI=10.5120/ijca2017915562

@article{ 10.5120/ijca2017915562,
author = { Niky K. Jain, Samrat O. Khanna, Chetna K. Shah },
title = { Graphical User Interface Approach for Quality Evaluation of Indian Rice },
journal = { International Journal of Computer Applications },
issue_date = { Oct 2017 },
volume = { 176 },
number = { 4 },
month = { Oct },
year = { 2017 },
issn = { 0975-8887 },
pages = { 12-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume176/number4/28539-2017915562/ },
doi = { 10.5120/ijca2017915562 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:41:37.033902+05:30
%A Niky K. Jain
%A Samrat O. Khanna
%A Chetna K. Shah
%T Graphical User Interface Approach for Quality Evaluation of Indian Rice
%J International Journal of Computer Applications
%@ 0975-8887
%V 176
%N 4
%P 12-17
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Modernization with automization incorporated makes a system more powerful. In the present world quality inspection of food products is a very important factor for evaluating the grade of food. In agricultural field, image processing is also used to evaluate the quality of rice. Major problem of rice industry for quality assessment is manual assessment done by human inspector. In this paper a method is presented to evaluate the quality of rice. Proposed method is an application of computer vision technique. Computer Vision provides an alternative for non-destructive and cost effective technique for Grading and Classification of rice using framework and neural network techniques. Some Geometrics features are useful for quality evaluation. In this paper proposed method is used to increase the accuracy of the rice quality detection by using such features with GUI (Graphical User Interface) and feed forward neural network. Artificial neural network detects the quality of rice by using features provided at the time of training and also the extracted features of rice and provides the result by comparing these features. It grades and classifies rice images based on obtained features.

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Index Terms

Computer Science
Information Sciences

Keywords

Feature extraction GUI (Graphical user interface) Image processing Quality analysis.