Convolutional Neural Network and OpenCV Based Mobile Application to Detect Wear out in Car Tyres

Authors

  • Harshitha Allipilli Stanley College of Engineering and Technology for Women, Hyderabad, India.
  • Samyuktha Samala Stanley College of Engineering and Technology for Women, Hyderabad, India.

DOI:

https://doi.org/10.24191/jcrinn.v6i1.181

Keywords:

opencv, convnet, convolutional neural networks, mobile applications, deep learning, wear out

Abstract

This work proposes a technique for detecting wear out of car  tyres. Tyre is the only part of the vehicle which is in contact with road. Hence tyre condition should be monitored timely in order to have a safe drive. Tyre wear out occurs because of the parameters such as when the tread limit of tyre is less than 1.6 cm, rubber degradation, when there are around 4 to 5 punctures, bulged tyre. We consider some of the above parameters to assess the wear of tyre using the computer vision techniques such as opencv and convolutional neural networks. Opencv and convolutional neural networks are most used in object detection and image classification. We used these techniques and obtained an accuracy of 90.95%, with which we can predict the wear of tyre to avoid dangerous accidents.

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Published

2021-03-29

How to Cite

Allipilli, H., & Samala, S. (2021). Convolutional Neural Network and OpenCV Based Mobile Application to Detect Wear out in Car Tyres. Journal of Computing Research and Innovation, 6(1), 97-`110. https://doi.org/10.24191/jcrinn.v6i1.181

Issue

Section

General Computing