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Vision-based egg grade classifier

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dc.citedby5
dc.contributor.authorZalhan M.Z.en_US
dc.contributor.authorSera Syarmila S.en_US
dc.contributor.authorMohd Nazri I.en_US
dc.contributor.authorMohd Taha I.en_US
dc.contributor.authorid36730188700en_US
dc.contributor.authorid36683226000en_US
dc.contributor.authorid57217075866en_US
dc.contributor.authorid57194007864en_US
dc.date.accessioned2023-05-29T06:39:04Z
dc.date.available2023-05-29T06:39:04Z
dc.date.issued2017
dc.descriptionCoordinate 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 processingen_US
dc.description.abstractDigital 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.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo7890772
dc.identifier.doi10.1109/ICICTM.2016.7890772
dc.identifier.epage35
dc.identifier.scopus2-s2.0-85018365049
dc.identifier.spage31
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85018365049&doi=10.1109%2fICICTM.2016.7890772&partnerID=40&md5=df019cd791ff51aa68ee5a15330adc17
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/23281
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitleICICTM 2016 - Proceedings of the 1st International Conference on Information and Communication Technology
dc.titleVision-based egg grade classifieren_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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