ANN based quality assessment of pomegranate

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 perfor...

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Bibliographic Details
Published in:AIP Conference Proceedings 2022-10, Vol.2494 (1)
Main Authors: Utpat, Vaishnavi B., Karande, Kailash J., Surwase, Sudha V.
Format: Article
Language:English
Subjects:
Agricultural production
Artificial intelligence
Digital imaging
Feature extraction
Fruits
Image processing
Market value
Quality assessment
Quality standards
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Summary: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.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0107565