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description Journal article public Jurnal Buana Informatika

Segmentasi Citra Ikan Tuna Menggunakan Gradient-Barrier Watershed Berbasis Analisis Hierarki Klaster Dan Regional Credibility Merging

Arif Fadllullah, Agus Zainal Arifin, Dini Adni Navastara
Diterbitkan 19 Juli 2016

Abstrak

. The main issue of object identification in tuna image is the difficulty of extracting the entire contour of tuna physical features, because it is often influenced by uneven illumination and the ambiguity of object edges in tuna image. We propose a novel segmentation method to optimize the determination of tuna region using GBW-AHK and RCM. GBW-AHK is used to optimize the determination of adaptive threshold in order to reduce over-segmented watershed regions. Then, RCM merges the remaining regions based on two merging criteria, thus it produces two main areas of segmentation, the object extraction of tuna and the background. The experimental results on 25 tuna images demonstrate that the proposed method successfully produced an image segmentation with the average value of RAE by 4.77%, ME of 0.63%, MHD of 0.20, and the execution time was 11.61 seconds.

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  • visibility 192 kali dilihat
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