J-Icon : Jurnal Komputer dan Informatika
Vol 11 No 1 (2023): Maret 2023

SISTEM PENDETEKSI KERUSAKAN JALAN ASPAL MENGGUNAKAN CANNY EDGE DETECTION

Farhan Aditya Rafi (Department of Computer sciences, Universitas Nusa Cendana, Indonesia)
Adriana Fanggidae (Department of Computer sciences, Universitas Nusa Cendana, Indonesia)
Yulianto Triwahyuadi Polly (Department of Computer sciences, Universitas Nusa Cendana, Indonesia)



Article Info

Publish Date
31 Mar 2023

Abstract

Road is a means of access for humans to move from one place to another, connecting one place to another, and serving as transportation infrastructure. At all times, asphalt roads are passed by road users, including small, medium, and large vehicles. However, road conditions are not always smooth and often there are damages in certain parts of the road. Factors such as water, weather, temperature changes, unstable soil conditions, air temperature, poor compaction process on the base layer, and the weight or overload of heavy vehicles that exceed capacity, as well as the increasing volume of vehicles, can cause road damage. Road damage can reduce economic revenue and increase accident rates. Some types of asphalt road damage include undulating, potholes, cracking, and asphalt puddles on the road surface. Potholes are the most common type of damage that cause accidents for road users. This study uses the Canny edge detection method to detect asphalt road damage. The minimum object size that can be detected as road damage is 15x15 pixels and the maximum is 290x540 pixels. Testing was conducted on 65 primary data and 35 secondary data, and the average accuracy obtained were 90.5% and 88%, respectively.

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Journal Info

Abbrev

jicon

Publisher

Subject

Computer Science & IT

Description

J-ICON : Jurnal Komputer dan Informatika focuses on the areas of computer sciences, artificial intelligence and expert systems, machine learning, information technology and computation, internet of things, mobile e-business, e-commerce, business intelligence, intelligent decision support systems, ...