Shrimps clusterization by size using digital image processing with CCA and DBSCAN

The quality of farmed shrimps has several criteria, one of which is shrimp size. The shrimp selection was carried out by the contractor at the harvest time by grouping the shrimp based on their size. This study aims to apply digital image processing for shrimp clustering based on size using the conn...

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Bibliographic Details
Main Authors: Adri Priadana, Aris Wahyu Murdiyanto
Format: Article
Language:English
Published: Diponegoro University 2020-04-01
Series:Jurnal Teknologi dan Sistem Komputer
Subjects:
Online Access:https://jtsiskom.undip.ac.id/index.php/jtsiskom/article/view/13455
Description
Summary:The quality of farmed shrimps has several criteria, one of which is shrimp size. The shrimp selection was carried out by the contractor at the harvest time by grouping the shrimp based on their size. This study aims to apply digital image processing for shrimp clustering based on size using the connected component analysis (CCA) and density-based spatial clustering of applications with noise (DBSCAN) methods. Shrimp group images were taken with a digital camera at a light intensity of 1200-3200 lux. The clustering results were compared with clustering from direct observation by two experts, each of which obtained an accuracy of 79.81 % and 72.99 % so that the average accuracy of the method was 76.4 %.
ISSN:2338-0403