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http://hdl.handle.net/123456789/2732
Title: | Automated Fish Egg Counting System using Image Processing | Authors: | Nor Hazlyna Harun Yusoff, N. Mohamad Ghozali Hassan Maizatul Fatihah Mohd Salah |
Keywords: | automated counting system;image processing;fish egg;k-means algorithm | Issue Date: | 1-Feb-2021 | Publisher: | UUM Press | Conference: | 10th Knowledge Management International Conference 2021 (KMICe 2021) | Abstract: | The 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. |
Description: | Others |
URI: | http://hdl.handle.net/123456789/2732 | ISSN: | 2773-5761 |
Appears in Collections: | Faculty of Data Science and Computing - Proceedings |
Files in This Item:
File | Description | Size | Format | |
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04_WOS(KIV)_KMICE 2021.pdf | 1.25 MB | Adobe PDF | View/Open |
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