Crack detection in train track using CNN

In Indian railways, the most significant reason for concern regarding unexplained rail track cracks is accidents. Most accidents happen when railway rails fracture, resulting in the loss of life and significant financial damages. Image processing technologies are used in this study to classify probl...

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Bibliographic Details
Main Authors: Ganesan, Keerthiga, Loganathan, Mohana Sundari, Vetriselvan, Akash, Sasikumar, Ajay
Format: Conference Proceeding
Language:English
Subjects:
Accident prediction
Artificial neural networks
Damage detection
Damage prevention
Image processing
Rails (railroad)
Railway tracks
Online Access:Get full text
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Summary:In Indian railways, the most significant reason for concern regarding unexplained rail track cracks is accidents. Most accidents happen when railway rails fracture, resulting in the loss of life and significant financial damages. Image processing technologies are used in this study to classify problems on railway rails, preventing train accidents. To provide track fracture detection approach that incorporates Convolutional Neural Networks with the picture pre-processing process. The main purpose of the investigation is to divide these groups into train track cracks and regular photos. This can be divided into two groups. In addition, one of the most promising areas of this research is to extract handcrafted qualities from raw images after various treatments. The aim of this strategy is to extract some features that are responsible for predicting cracks in railroad tracks.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0248062