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Reseach Article

Quality evaluation of apple fruit: A Survey

by Komal Sindhi, Jaymit Pandya, Sudhir Vegad
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 136 - Number 1
Year of Publication: 2016
Authors: Komal Sindhi, Jaymit Pandya, Sudhir Vegad

Komal Sindhi, Jaymit Pandya, Sudhir Vegad . Quality evaluation of apple fruit: A Survey. International Journal of Computer Applications. 136, 1 ( February 2016), 32-36. DOI=10.5120/ijca2016908340

@article{ 10.5120/ijca2016908340,
author = { Komal Sindhi, Jaymit Pandya, Sudhir Vegad },
title = { Quality evaluation of apple fruit: A Survey },
journal = { International Journal of Computer Applications },
issue_date = { February 2016 },
volume = { 136 },
number = { 1 },
month = { February },
year = { 2016 },
issn = { 0975-8887 },
pages = { 32-36 },
numpages = {9},
url = { },
doi = { 10.5120/ijca2016908340 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T23:35:53.058247+05:30
%A Komal Sindhi
%A Jaymit Pandya
%A Sudhir Vegad
%T Quality evaluation of apple fruit: A Survey
%J International Journal of Computer Applications
%@ 0975-8887
%V 136
%N 1
%P 32-36
%D 2016
%I Foundation of Computer Science (FCS), NY, USA

Disease recognition has been huge research area nowadays because inspection of quality of fruits at an early stage prevents spreading of disease to the other areas of fruit as well as helps to reduce great economic losses in agricultural sectors and industries. Different types of diseases exist in different fruits. The focus of the present research work is on quality evaluation of apple fruit. The basic process for defect detection in fruits is basically divided into two major steps; feature extraction and classification .Feature extraction involves extracting features like color, texture and shape from fruit image. The output of this are feature vectors which are given as an input to the classifier. Finally, the classifier categorizes them into appropriate classes. The accuracy of this process depends on many factors like number of input images, method chosen for pre processing, features extracted, classifier chosen, etc.

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Index Terms

Computer Science
Information Sciences


Digital image processing Quality Evaluation apple disease feature extraction classification