Shrimps clusterization by size using digital image processing with CCA and DBSCAN
| Main Authors: | Priadana, Adri, Murdiyanto, Aris Wahyu |
|---|---|
| Other Authors: | Kementerian Riset dan Pendidikan Tinggi Republik Indonesia, Kementerian Riset, Teknologi, dan Pendidikan Tinggi Republik Indonesia |
| Format: | Article info application/pdf eJournal |
| Bahasa: | ind |
| Terbitan: |
Departemen Teknik Komputer, Fakultas Teknik, Universitas Diponegoro
, 2020
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| Subjects: | |
| Online Access: |
https://jtsiskom.undip.ac.id/index.php/jtsiskom/article/view/13455 https://jtsiskom.undip.ac.id/index.php/jtsiskom/article/view/13455/12565 |
Daftar Isi:
- 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 %.
- Kualitas udang hasil panen memiliki beberapa kriteria, salah satunya adalah ukuran udang. Proses pemilihan udang yang dilakukan pemborong pada waktu panen salah satunya adalah mengelompokkan udang berdasarkan ukurannya. Penelitian ini bertujuan untuk menerapkan metode connected component analysis (CCA) dan metode density-based spatial clustering of applications with noise (DBSCAN) untuk klasterisasi udang berdasarkan ukuran menggunakan pengolahan citra digital. Citra kelompok udang diambil dengan kamera digital di intensitas cahaya lokasi 1200-3200 lux. Hasil klasterisasi dari metode dibandingkan dengan hasil pengamatan secara langsung oleh dua orang ahli yang masing-masing menghasilkan akurasi 79,81 % dan 72,99 % sehingga rata-rata akurasinya 76,4 %.