Convolutional neural network and opencv based mobile application to detect wear out in car tyres / Harshitha Allipilli and Samyuktha Samala

• Main Authors: Allipilli, Harshitha (Author), Samala, Samyuktha (Author)
• Format: Book
• Published: UiTM Cawangan Perlis, 2021-03.
• Subjects: Article; PeerReviewed
• Online Access: Link Metadata
• Notes: https://ir.uitm.edu.my/id/eprint/47090/1/47090.pdf
• Keywords: Online data processing; Neural networks (Computer science)

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.