Implementation of KNN Methods And GLCM Extraction For Classification Of Road Damage Level

Adyanata Lubis; Isdaryanto  Iskandar; MM Lanny  W Panjaitan

doi:10.34306/itsdi.v4i1.564

Authors

Adyanata Lubis STKIP Rokania
Isdaryanto Iskandar Katolik Indonesia Atma Jaya University
MM Lanny W Panjaitan Katolik Indonesia Atma Jaya University

DOI:

https://doi.org/10.34306/itsdi.v4i1.564

Keywords:

Digital Image, KNN Method, GLCM, Road Damage

Abstract

Road damage that occurs on several road surfaces causes huge losses, especially for road users such as travel time, congestion, accidents and others , so it is necessary to assess the level of road damage. At this time, problems in determining the level of road damage such as detecting cracks, potholes, calculating the width of cracks, the percentage of cracks and generating the level of road damage are still carried out by slow manual calculations using the Surface method. Distress Index (SDI). In this study, the KNN and GLCM methods will be used to detect road damage. Based on the results of the tests carried out, the accuracy of the results of disease detection with the KNN method and GLCM extraction depends on the number of datasets contained in the system. The process of measuring the level of road damage to get the results of the level of damage to the road can be done quickly, namely by entering a road damage image into the application.

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