Grey Level Co-Occurrence Matrix (GLCM) & Hybrid Klasifikasi untuk Mendeteksi Kerusakan Jalan Aspal

Ika Maylani (Institut Teknologi Insan Cendekia Mandiri)
Virginia Wahyu Ambarwati
Bismar Wasykuru
Alqaroni Alqaroni
Firnanda Tri Buana Kusuma Wati

Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK)
2023: SNESTIK III

The importance of detecting damage to the asphalt road surface is to minimize the occurrence of accidents caused by uneven road surfaces. Image extraction can be used to detect road surface damage. GLCM is a statistical method in which statistical calculations use the distribution of gray degrees (histograms) by measuring the level of contrast, granularity, and roughness of an area from the neighboring pixels in the image. The classification process uses a hybrid classification, which combines the SVM method with kernel changes and KNN with changes in k=3, 4, 5, 7 and 9 tracts.