Study on crack detection using image processing techniques and deep learning – a survey

Saleem, Muhammad Asif and Senan, Norhalina and Ahmad, Rehan (2020) Study on crack detection using image processing techniques and deep learning – a survey. International Journal of Scientific and Technology Research, 9 (2). pp. 6263-6266. ISSN 2277-8616

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Due to continuous seasonal changes and low quality of development materials, cracks may create in the walls of the building. One of the underlying indications of the debasement of a solid surface is cracks. The manual examination has numerous disadvantages like the imperceptibility of cracks, tedious and prerequisite of master's information. So it very well may be done consequently by utilizing image processing. Deep learning algorithms have been used for the solution of multiple issues in the area of image classification. The purpose of this writing is to study and understand the existing crack detection techniques using image processing. For this purpose, recent research articles have been selected for review. In this writing review, a portion of the ongoing papers on crack identification have been evaluated and the investigation of the audit is being done on image processing strategies. It is concluded from the literature that deep learning performs much better in crack detection.

Item Type: Article
Uncontrolled Keywords: cracks detection; Fuzzy logic; Convolution Neural Network; Deep Learning; Computer Vision; Supervised Learning; Unsupervised Learning
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA1501-1820 Applied optics. Photonics
Divisions: Faculty of Computer Science and Information Technology > Department of Multimedia
Depositing User: Miss Afiqah Faiqah Mohd Hafiz
Date Deposited: 09 Jan 2022 02:58
Last Modified: 09 Jan 2022 02:58

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