Shape classification of harumanis mango using discriminant analysis (DA) and support vector machine (SVM)

Shape classification of harumanis mango using discriminant analysis (DA) and support vector machine (SVM). Journal of Engineering and Technology, 5 (2). pp. 93-104. ISSN 2180-3811 (2014)



Abstract

The perceived quality of fruits, such as mangoes, is greatly dependent on many parameters such as ripeness, shape, size, and is influenced by other factors such as harvesting time. Unfortunately, a manual fruit grading has several drawbacks such as subjectivity, tediousness and inconsistency. By automating the procedure, as well as developing new classification technique, it may solve these problems. This paper presents the novel work on the using visible Imaging as a Tool in Quality Monitoring of Harumanis Mangoes. A Fourier-Descriptor method was developed from CCD camera images to grade mango by its shape. Discriminant analysis (DA) and Support vector machine (SVM) were applied for classification process and able to correctly classify 98.3% for DA and 100% for SVM.

Item Type: Article
Keywords: Infrared imaging, Visible imaging, Machine vision, Fourier descriptor, Harumanis mango, Grading system, Automated inspection
Taxonomy: By Subject > College of Engineering > Electrical Engineering > Electronics
By Subject > College of Engineering > Electrical Engineering > Systems
Local Content Hub: Subjects > College of Engineering
Depositing User: Eza Eliana Abdul Wahid
Date Deposited: 19 Jul 2022 09:08
Last Modified: 19 Jul 2022 09:08
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