Automatic preharvest grading of Harumanis fruits / Khairul Adilah Ahmad and Sharifah Lailee Syed Abdullah

Ahmad, Khairul Adilah and Syed Abdullah, Sharifah Lailee (2016) Automatic preharvest grading of Harumanis fruits / Khairul Adilah Ahmad and Sharifah Lailee Syed Abdullah. Journal of Computing Research and Innovation, 1 (1): 11. pp. 74-79. ISSN 2600-8793

Abstract

Fruit size is one of the most important features for grading Harumanis fruits. However, harvesting the fruit at the correct size is problematic for fruits growers. The aim of this paper is to discuss the use of image processing technique to classify the grade of Harumanis fruits before harvesting. This research adopted a computer vision methodology which include image acquisition, image pre-processing, image segmentation, feature extraction and classification. The statistical analysis which used linear regression model showed that the size has high relationship with the Harumanis’ weights and grades. The results showed that it is possible to estimate the weight of fruits before harvesting using image processing technique thus enabling fruits grower to grade their products efficiently.

Metadata

Item Type: Article
Creators:
Creators
Email / ID Num.
Ahmad, Khairul Adilah
UNSPECIFIED
Syed Abdullah, Sharifah Lailee
UNSPECIFIED
Subjects: Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science
T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Electronics > Pattern recognition systems
Divisions: Universiti Teknologi MARA, Perlis > Arau Campus > Faculty of Computer and Mathematical Sciences
Journal or Publication Title: Journal of Computing Research and Innovation
UiTM Journal Collections: UiTM Journal > Journal of Computing Research and Innovation (JCRINN)
ISSN: 2600-8793
Volume: 1
Number: 1
Page Range: pp. 74-79
Keywords: Image processing, Feature Extraction, Size, Weight, Linear regression analysis, Harumanis Mango fruits
Date: 2016
URI: https://ir.uitm.edu.my/id/eprint/53986
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