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Multilevel Thresholding Segmentasi Citra Warna Menggunakan Logarithmic Decreasing Inertia Weight Particle Swarm Optimization

Murinto Murinto, Adhi Prahara, Erik Iman Heri Ujianto

Abstract


Permasalahan utama dari segmentasi citra warna adalah tidak semua metode segmentasi citra yang ada saat ini dapat digunakan secara langsung seperti halnya pada citra gray scale. Maka dari itu diperlukan suatu teknik yang tepat untuk melakukan segmentasi warna. Teknik yang digunakan dalam penelitian ini adalah teknik segmentasi multilevel thresholding dengan menggunakan suatu bobot inersia logarithm decreasing particle swarm optimization (LogPSO). Bobot inersia Nilai threshold optimal diperoleh dengan cara memaksimalkan fungsi objektif Otsu. Teknik yang diusulkan mengurangi waktu perhitungan untuk perhitungan threshold optimum didasarkan pada multilevel thresholding yang diujikan pada 8 citra warna standar. Suatu analisis perbandingan secara detail dengan bobot inersia lainnya yang didasarkan pada multilevel thresholding yakni constant particle swarm optimization (CPSO), menunjukkan hasil kinerja yang lebih baik pada metode yang diusulkan. Kinerja segmentasi citra warna dalam penelitian ini didasarkan pada peak signal to noise ratio (PSNR), mean, standar deviasi fitness, structural similarity index measure (SSIM), mean square of error (MSE) serta waktu perhitungannya. Algoritma LogPSO menunjukkan hasil yang lebih baik pada keseluruhan parameter tersebut kecuali pada waktu penghitungan. Algoritma LogPSO lebih lama waktu perhitungannya dibandingkan dengan CPSO.


Keywords


Citra Warna; CPSO; LogPSO; Segmentasi

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DOI: 10.30595/sainteks.v19i1.13295

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ISSN: 2686-0546