Research Article
Non Destructive Analysis of Crack Using Image Processing, Ultrasonic and IRT: A Critical Review and Analysis
@INPROCEEDINGS{10.1007/978-3-031-28975-0_12, author={P. Ramani and V. Subbiah Bharathi and S. Sugumaran}, title={Non Destructive Analysis of Crack Using Image Processing, Ultrasonic and IRT: A Critical Review and Analysis}, proceedings={Cognitive Computing and Cyber Physical Systems. Third EAI International Conference, IC4S 2022, Virtual Event, November 26-27, 2022, Proceedings}, proceedings_a={IC4S}, year={2023}, month={3}, keywords={Degradation Infrared thermography Morphological operation Ultrasonic testing Support vector machine}, doi={10.1007/978-3-031-28975-0_12} }- P. Ramani
V. Subbiah Bharathi
S. Sugumaran
Year: 2023
Non Destructive Analysis of Crack Using Image Processing, Ultrasonic and IRT: A Critical Review and Analysis
IC4S
Springer
DOI: 10.1007/978-3-031-28975-0_12
Abstract
Crack is one of the most important surfaces damage to monuments, concrete structures, buildings, and roads. Manually examining damage is time- and labor-intensive. Crack irregularity measurements are challenging and need more expertise. Thus, develop automatic crack detection using the image processing method. This article reveals the various strategies to distinguish the crack length, width, and depth utilizing different automatic crack detection methods. In this, 53 papers describe the detection of cracks and other decay measurements. The investigation is given on the survey and dependent on the Infrared Thermography method, Ultrasonic imaging, and Image processing. The main aim of this paper is to summarize and compare the few strategies used in various Non-Destructive Techniques. Detection of the crack using Deep Learning achieves with maximum accuracy of 98%. Finally, we represent different issues that can be valuable for inquiring about to achieve further investigation on this detection.
