click here to download project abstract
– ABSTRACT
Train Track Crack Classification a railway crack detection system. This paper
presents the classification system that classify any crack in the railway tracks by
using deep learning with convolutional neural networks (CNNs).In railway
network Accidents are the major concern in terms of railway track unidentified
crack in rail tracks in Indian railway. About Most of the accidents are occurring at
railway track crack in railway tracks resulting in loss of precious life and loss of
economy It is required to monitor the track health condition frequently using an
crack classify system.
This project prevents train derailment by classify cracks in railway track using
image processing technology. To propose a solution for track crack recognition
that uses a combination of Convolutional Neural Network and specific image
pre-processing steps.
It described the innovative solution that provides efficient
image processing and deep learning with convolutional neural networks.
A variety of neuron-wise and layer-wise visualization methods were applied using
a CNN, trained with a publicly available from given image dataset. So, it’s
observed that neural networks can capture the colours and textures of lesions
specific to respective cracks in train tracks, loss of precious life and loss of
economy It is required to monitor the track health condition frequently using an
crack which resembles human decision-making.
