A New Computer Vision Based Rail Detection
Method Using Entropy and Support Vector Machines

Dublin Core

Title

A New Computer Vision Based Rail Detection
Method Using Entropy and Support Vector Machines

Subject

Keywords-classification; entropy; support vector machine;
image processing; railways

Description

Abstract—Condition monitoring in railways is an important and
critical process in terms of travel safety. However, this process is
generally done based on observation or with various equipment.
Therefore, it is costly and has a high probability of error. In this
study, a computer vision-based method for rail detection for
condition monitoring in railways is proposed. In addition to the
features obtained from the images, a new feature is calculated
using entropy. Rail detection is provided by classifying these
features with Support Vector Machine (SVM). It has been seen
that the proposed method works successfully and provides
improvement in the monitoring process.

Creator

Kağan Murat, Mehmet Karaköse, Erhan Akın

Source

www.ijcit.com

Date

June 2023

Contributor

peri irawan

Format

pdf

Language

english

Type

text

Files

Citation

Kağan Murat, Mehmet Karaköse, Erhan Akın, “A New Computer Vision Based Rail Detection
Method Using Entropy and Support Vector Machines,” Repository Horizon University Indonesia, accessed May 30, 2025, https://repository.horizon.ac.id/items/show/9123.