Analisa Kinerja Algoritma Detektor Sudut pada Citra Noise Komparasi Operator (Moravec, Susan, Haris, FAST, Eigen dan Forstner)
Abstract
Algoritma detektor medeskripsikan komparasi kinerja dari masing-masing algoritma pendeteksi sudut pada citra noise. Citra yang digunakan sebagai masukan adalah citra dengan format grayscale (citra abu-abu) dan diberikan beberapa jenis noise. Algoritma yang dibandingkan adalah algoritma Moravec, Susan, Harris, FAST, Eigen dan Forstner. Jenis noise yang akan di gunakan adalah gaussian, poisson, salt & pepper dan speckle. Hasil pengujian didapatkan sebagai berikut; detektor Moravec mengahasilkan 1.000 titik sudut pada citra noise (gaussian, poisson, salt and pepper, speckle), rata-rata waktu proses pendeteksian sebesar 2,19 detik. Detektor Susan menghasilkan 100 titik sudut pada citra noise (gaussian, poisson, salt and pepper dan speckle) dengan rata-rata waktu proses pendeteksian sebesar 23,99 detik. Hasil pengujian akurasi setiap detektor sudut pada citra yang memilki noise menyatakan bahwa; seluruh detektor sudut tidak mampu menemukan titik-titik sudut dengan tepat, seluruh detektor sudut tidak akurat dalam menunjukkan lokasi titik sudut, hanya detektor Moravec dan Susan yang stabil terhadap perulangan, seluruh detektor sudut tidak stabil atau sangant sensitif terhadap semua tipe noise. Hasil pengujian dalam penelitian ini memperlihatkan bahwa seluruh detektor sudut sangat sensitif terhadap noise, dengan pengertian lain bahwa tingkat akurasi hasil pendeteksian setiap detektor sudut akan sangat dipengaruhi oleh noise dan tipe noise.
Kata Kunci: Detektor Sudut, Titik Sudut, Grayscale, Noise, Moravec, Susan, Harris, FAST, Eigen dan Forstner
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DOI: 10.33751/komputasi.v15i1.1268
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