Seleksi Arah Sudut Komputasi Dan Fitur Glcm Pada Kstraksi Citra Kayu Jati, Mahoni, Mindi, Dan Sengon

Stefanus Santosa
Martono Martono
Marchus Budi Utomo
Basuki Setiyo Budi

Wahana Teknik Sipil: Jurnal Pengembangan Teknik Sipil
Vol 23, No 2 (2018): Wahana Teknik Sipil

Research on feature extraction of wood texture with features and angle direction israrely done, especially in teak, mahogany, mindi, and albasia. This research isneeded to select more efficient and effective features and angle directions to identify wood species. The features tested were Angular Second Moment (ASM), Contrast, IDM / Homogenity, Entropy, Correlation and the direction of the computational 0, 45, 90, and 135 degrees of gray level co-occurrence matrix (GLCM). The experimental results show that the selected angles are 0, 45, and 90 degrees and features are IDM and Entropy.Kata kunci : gray level co-occurrence matrix (GLCM), features extraction, woodclassification