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Computer vision technique to classify dates based on hardness
Other Title(s)
استخدام تقنية تصوير الحاسوب في تصنيف التمور حسب الصلابة
Joint Authors
al-Shukayli, Nuaymah Harib
Annamalai, Manickavasagan
al-Muzayini, Nawal Khamis
Muhammad Shafir Rahman
Qizani, Najib
Source
Agricultural and Marine Sciences : Research Journal
Issue
Vol. 22, Issue 1 (31 Dec. 2017), pp.36-41, 6 p.
Publisher
Sultan Qaboos University College of Agricultural and Marine Sciences
Publication Date
2017-12-31
Country of Publication
Oman
No. of Pages
6
Main Subjects
Abstract EN
Hardness is one of the important attributes in determining the quality of dried fruits.
Hardness assessment is normally carried out by manual inspection.
This method is time consuming, laborious, expensive and subjective.
The objective of this study was to develop a computer vision system with a monochrome camera to classify dates based on hardness.
Date samples were obtained from three different growing regions in Oman and graded into soft, semi-hard, and hard classes based on hardness.
A total of 1800 date samples were imaged individually using a monochrome camera (600 dates / class).
Histogram and texture features were extracted from the acquired monochrome images and used in the classification models.
The overall classification accuracies in three class model (soft, semi-hard, and hard) were 66% and 71% for linear discriminant analysis (LDA) and artificial neural network (ANN), respectively.
It was improved to 84% and 77% in LDA and ANN, respectively while using two class model (soft and hard (semi-hard and hard together)).
The histogram features were more contributing in the date classification based on hardness than image texture features.
Computer vision technique has great potential to develop online quality monitoring systems for dates and other dried fruits.
American Psychological Association (APA)
al-Shukayli, Nuaymah Harib& Annamalai, Manickavasagan& al-Muzayini, Nawal Khamis& Muhammad Shafir Rahman& Qizani, Najib. 2017. Computer vision technique to classify dates based on hardness. Agricultural and Marine Sciences : Research Journal،Vol. 22, no. 1, pp.36-41.
https://search.emarefa.net/detail/BIM-798686
Modern Language Association (MLA)
al-Shukayli, Nuaymah Harib…[et al.]. Computer vision technique to classify dates based on hardness. Agricultural and Marine Sciences : Research Journal Vol. 22, no. 1 (2017), pp.36-41.
https://search.emarefa.net/detail/BIM-798686
American Medical Association (AMA)
al-Shukayli, Nuaymah Harib& Annamalai, Manickavasagan& al-Muzayini, Nawal Khamis& Muhammad Shafir Rahman& Qizani, Najib. Computer vision technique to classify dates based on hardness. Agricultural and Marine Sciences : Research Journal. 2017. Vol. 22, no. 1, pp.36-41.
https://search.emarefa.net/detail/BIM-798686
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 40-41
Record ID
BIM-798686