Indian Journal of Science and Technology
Year: 2021, Volume: 14, Issue: 10, Pages: 881-891
Sharmad Bhat1, Saish Naik1, Mandar Gaonkar1, Pradnya Sawant1, Shailendra Aswale1*, Pratiksha Shetgaonkar1
1Computer Department, SRIEIT, Goa University, Shiroda, 403103, India. Tel.: +91-9822161240
Email: [email protected]
Received Date:13 August 2020, Accepted Date:28 February 2021, Published Date:02 April 2021
Objectives: The proposed research work detects road cracks in a given set of images. In addition, it identifies the longitudinal type of crack in given crack image. Methods: The study mainly focuses on implementing a road crack detection technique using Convolutional Neural Networks. Findings: The proposed model is able to distinguish between crack and non-crack images and also able to classify the longitudinal crack from other given crack images. Novelty: Proposed road crack detection technique provides high accuracy compared to earlier standard techniques.
Keywords: Road crack detection; CNN (Convolutional Neural Networks); support vector machines (SVM); deep learning; classification; image processing
© 2021 Bhat et al.This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)
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