Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/2732
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dc.contributor.authorNor Hazlyna Harunen_US
dc.contributor.authorYusoff, N.en_US
dc.contributor.authorMohamad Ghozali Hassanen_US
dc.contributor.authorMaizatul Fatihah Mohd Salahen_US
dc.date.accessioned2022-01-17T06:42:23Z-
dc.date.available2022-01-17T06:42:23Z-
dc.date.issued2021-02-01-
dc.identifier.issn2773-5761-
dc.identifier.urihttp://hdl.handle.net/123456789/2732-
dc.descriptionOthersen_US
dc.description.abstractThe fish industry is a source of income for fish breeders. Fish egg selection is one of the important aspects in determining the quantity of fish eggs. The quantity of fish eggs purchased from practitioner may be insufficient due to undetected poor quality of fish eggs. Hence, this study focuses on automated fish egg counting system using image processing method utilizing k-means algorithm. The image of fish egg are captured and processed to calculate the total number of fish egg automatically. The results demonstrate good potential use of the proposed automated counting system with accuracy up to 99.41%. Furthermore, with the proposed automated counting, the manual counting time can be reduced to an average time of 1.29 seconds. This could benefit the fish breeding industry in screening good quality of eggs automatically.en_US
dc.publisherUUM Pressen_US
dc.subjectautomated counting systemen_US
dc.subjectimage processingen_US
dc.subjectfish eggen_US
dc.subjectk-means algorithmen_US
dc.titleAutomated Fish Egg Counting System using Image Processingen_US
dc.typeNationalen_US
dc.relation.conference10th Knowledge Management International Conference 2021 (KMICe 2021)en_US
dc.description.page250-256en_US
dc.description.researchareaArtificial Intelligenceen_US
dc.date.seminarstartdate2021-02-01-
dc.date.seminarenddate2021-02-01-
dc.description.typeIndexed Proceedingsen_US
item.openairetypeNational-
item.grantfulltextopen-
item.fulltextWith Fulltext-
crisitem.author.deptUniversiti Malaysia Kelantan-
crisitem.author.orcid0000-0003-2703-2531-
Appears in Collections:Faculty of Data Science and Computing - Proceedings
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