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Vision-based egg grade classifier

Coordinate measuring machines; Human computer interaction; Image classification; Image enhancement; Intelligent systems; Medical imaging; Military photography; Classification algorithm; Digital image processing technique; Human computer interfaces; Image filtering; Image processing technique; Indust...

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Main Authors: Zalhan M.Z., Sera Syarmila S., Mohd Nazri I., Mohd Taha I.
Other Authors: 36730188700
Format: Conference Paper
Published: Institute of Electrical and Electronics Engineers Inc. 2023
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id my.uniten.dspace-23281
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spelling my.uniten.dspace-232812023-05-29T14:39:04Z Vision-based egg grade classifier Zalhan M.Z. Sera Syarmila S. Mohd Nazri I. Mohd Taha I. 36730188700 36683226000 57217075866 57194007864 Coordinate measuring machines; Human computer interaction; Image classification; Image enhancement; Intelligent systems; Medical imaging; Military photography; Classification algorithm; Digital image processing technique; Human computer interfaces; Image filtering; Image processing technique; Industrial inspections; Object classification; Vision systems; Image processing Digital image processing techniques (DIP) have been widely used in various types of application recently. A variety of these techniques are now being used in many types of application area such as object classification, intelligent system, robotics, biometrics system, medical visualization, military, law enforcement, image enhancement and restoration, industrial inspection, artistic effect and human computer interfaces. This paper proposes the implementation of digital image processing techniques to classify three different categories of commercial eggs. The proposed system consists of the study on different types and sizes of commercial eggs, real size measurement of these eggs using Coordinate Measure Machine (CMM) and camera, classification algorithm and the development of vision based egg classification system. Image processing techniques such as image filtering and image enhancements have been applied in the system. Results have shown that the proposed system has been able to successfully classify three categories of commercial eggs with accuracy of more than 96%. � 2016 IEEE. Final 2023-05-29T06:39:04Z 2023-05-29T06:39:04Z 2017 Conference Paper 10.1109/ICICTM.2016.7890772 2-s2.0-85018365049 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85018365049&doi=10.1109%2fICICTM.2016.7890772&partnerID=40&md5=df019cd791ff51aa68ee5a15330adc17 https://irepository.uniten.edu.my/handle/123456789/23281 7890772 31 35 Institute of Electrical and Electronics Engineers Inc. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Coordinate measuring machines; Human computer interaction; Image classification; Image enhancement; Intelligent systems; Medical imaging; Military photography; Classification algorithm; Digital image processing technique; Human computer interfaces; Image filtering; Image processing technique; Industrial inspections; Object classification; Vision systems; Image processing
author2 36730188700
author_facet 36730188700
Zalhan M.Z.
Sera Syarmila S.
Mohd Nazri I.
Mohd Taha I.
format Conference Paper
author Zalhan M.Z.
Sera Syarmila S.
Mohd Nazri I.
Mohd Taha I.
spellingShingle Zalhan M.Z.
Sera Syarmila S.
Mohd Nazri I.
Mohd Taha I.
Vision-based egg grade classifier
author_sort Zalhan M.Z.
title Vision-based egg grade classifier
title_short Vision-based egg grade classifier
title_full Vision-based egg grade classifier
title_fullStr Vision-based egg grade classifier
title_full_unstemmed Vision-based egg grade classifier
title_sort vision-based egg grade classifier
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2023
_version_ 1806424540243296256
score 13.211869

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