Computer Vision and Image Processing Approaches for Corrosion Detection
| Autor: | Ahmad Ali Imran Mohd Ali, Shahrizan Jamaludin, Md Mahadi Hasan Imran, Ahmad Faisal Mohamad Ayob, Sayyid Zainal Abidin Syed Ahmad, Mohd Faizal Ali Akhbar, Mohammed Ismail Russtam Suhrab, Mohamad Riduan Ramli |
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| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | Journal of Marine Science and Engineering, Vol 11, Iss 10, p 1954 (2023) |
| Druh dokumentu: | article |
| ISSN: | 11101954 2077-1312 |
| DOI: | 10.3390/jmse11101954 |
| Popis: | Corrosion is an undesirable phenomenon resulting in material deterioration and degradation through electrochemical or chemical reactions with the surrounding environment. Additionally, corrosion presents considerable threats in both the short and long term because of its ability to create failures, leakages, and damage to materials, equipment, and environment. Despite swift technological developments, it remains difficult to determine the degrees of corrosion due to the different textures and the edgeless boundary of corrosion surfaces. Hence, there is a need to investigate the robust corrosion detection algorithms that are suitable for all degrees of corrosion. Recently, many computer vision and image processing algorithms have been developed for corrosion prediction, assessment, and detection, such as filtering, texture, color, pixelation, image enhancement, wavelet transformation, segmentation, classification, and clustering approaches. As a result, this paper reviews and discusses the state-of-the-art computer vision and image processing methods that have been developed for corrosion detection in various applications, industries, and academic research. The challenges for corrosion detection using computer vision and image processing algorithms are also explored. Finally, recommendations for future research are also detailed. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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