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Dinial Utami Nurul Qomariah
Sepuluh Nopember Institute of Technology
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AUTOMATIC DETERMINATION OF SEEDS FOR RANDOM WALKER BY SEEDED WATERSHED TRANSFORM FOR TUNA IMAGE SEGMENTATION Moch Zawaruddin Abdullah; Dinial Utami Nurul Qomariah; Lafnidita Farosanti; Agus Zainal Arifin
Jurnal Ilmu Komputer dan Informasi Vol 11, No 1 (2018): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information
Publisher : Faculty of Computer Science - Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (744.742 KB) | DOI: 10.21609/jiki.v11i1.468

Abstract

Tuna fish image classification is an important part to sort out the type and quality of the tuna based upon the shape. The image of tuna should have good segmentation results before entering the classification stage. It has uneven lighting and complex texture resulting in inappropriate segmentation. This research proposed method of automatic determination seeded random walker in the watershed region for tuna image segmentation. Random walker is a noise-resistant segmentation method that requires two types of seeds defined by the user, the seed pixels for background and seed pixels for the object. We evaluated the proposed method on 30 images of tuna using relative foreground area error (RAE), misclassification error (ME), and modified Hausdroff distances (MHD) evaluation methods with values of 4.38%, 1.34% and 1.11%, respectively. This suggests that the seeded random walker method is more effective than exiting methods for tuna image segmentation.
Co-Authors Agus Zainal Arifin Lafnidita Farosanti Moch Zawaruddin Abdullah