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ANN based quality assessment of pomegranate.

Authors :
Utpat, Vaishnavi B.
Karande, Kailash J.
Surwase, Sudha V.
Source :
AIP Conference Proceedings; 2022, Vol. 2494 Issue 1, p1-7, 7p
Publication Year :
2022

Abstract

Agriculture and horticulture have vital role in total GDP of India. Grading of fruits is important to evaluate agricultural production, obtain quality standards and increase market value. Mostly the external appearance of the fruit decides the quality of fruit. In India, quality assessment is performed manually by observing appearance of the fruit. The traditional method of grading is more time-consuming and also not focuses on quality of the fruit. The present system eliminates drawbacks associated with traditional method of quality assessment by combining Artificial Intelligence and Digital Image Processing Techniques. The system extracts different features of the pomegranate fruit using image processing. ANN uses these extracted features as input to the system and grades the fruit as class 1, class 2, class 3 and class 4 with 98.50 % accuracy. Though the system classifies pomegranate fruits more accurately it has some limitations that it couldn't find out the freshness of fruit. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0094243X
Volume :
2494
Issue :
1
Database :
Complementary Index
Journal :
AIP Conference Proceedings
Publication Type :
Conference
Accession number :
159977140
Full Text :
https://doi.org/10.1063/5.0107565