Crack detection in historic structures using mixed Prewitt filter: Case study of the Historic Si-o-se-pol Bridge in Iran
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Abstract
In contrast to new and modern structures, historical structures have cultural significance, and it is essential to make an effort to preserve them. For this purpose, fast and accurate damage detection of historical structures plays a crucial role. Thus, the current study introduces a novel and effective tool for detecting cracks in historic structures. A new and modified version of the Prewitt filter is proposed to detect cracks in the Si-o-se-pol Bridge, a historic bridge in Iran. Results of crack detection using vertical and horizontal Prewitt filters are compared to those obtained from the proposed mixed filter. The findings show that the mixed Prewitt filter has significantly better performance compared to the vertical and horizontal Prewitt filters.
Keywords
crack detection, crack identification, historical structures, Prewitt filter
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
References
- Abdel-Qader, I., Abudayyeh, O., & Kelly, M. E. (2003). Analysis of edge-detection techniques for crack identification in bridges. Journal of Computing in Civil Engineering, 17(4), 255-263. DOI: https://doi.org/10.1061/(ASCE)0887-3801(2003)17:4(255)
- Ahmed, A. S. (2018). Comparative study among Sobel, Prewitt and Canny edge detection operators used in image processing. Journal of Theoretical and Applied Information Technology, 96(19), 6517-6525.
- Avdelidis, N. P., & Moropoulou, A. (2004). Applications of infrared thermography for the investigation of historic structures. Journal of Cultural Heritage, 5(1), 119-127. DOI: https://doi.org/10.1016/j.culher.2003.07.002
- Binda, L., & Saisi, A. (2001). State of the art of research on historic structures in Italy. Milan, Italy: Politecnico of Milan.
- Binda, L., & Saisi, A. (2009). Application of NDTs to the diagnosis of Historic Structures. Paper presented at the Proceedings of the Non-Destructive Testing in Civil Engineering NDTCE, Zurich.
- Dong, W., & Shisheng, Z. (2008). Color image recognition method based on the prewitt operator. Paper presented at the International conference on computer science and software engineering, Duhok. DOI: https://doi.org/10.1109/CSSE.2008.567
- Gentile, C., & Saisi, A. (2013). Operational modal testing of historic structures at different levels of excitation. Construction and Building Materials, 48(1), 1273-1285. DOI: https://doi.org/10.1016/j.conbuildmat.2013.01.013
- Germanese, D., Leone, G. R., Moroni, D., Pascali, M. A., & Tampucci, M. (2018). Long-term monitoring of crack patterns in historic structures using UAVs and planar markers: A preliminary study. Journal of Imaging, 4(8), 99-107. DOI: https://doi.org/10.3390/jimaging4080099
- Mesquita, E., Arêde, A., Pinto, N., Antunes, P., & Varum, H. (2018). Long-term monitoring of a damaged historic structure using a wireless sensor network. Engineering Structures, 161(1), 108-117. DOI: https://doi.org/10.1016/j.engstruct.2018.02.013
- Saadatmorad, M., Talookolaei, R. A. J., Milani, G., Khatir, S., & Le, C. T. (2023). Crack detection in historical masonry structures using efficient image processing: Application on a masonry bridge in Iran. Paper presented at IEEE International Workshop on Metrology for Living Environment (MetroLivEnv), Milan. DOI: https://doi.org/10.1109/MetroLivEnv56897.2023.10164038
- Wang, N., Zhao, Q., Li, S., Zhao, X., & Zhao, P. (2018). Damage classification for masonry historic structures using convolutional neural networks based on still images. Computer‐Aided Civil and Infrastructure Engineering, 33(12), 1073-1089. DOI: https://doi.org/10.1111/mice.12411
- Yang, L., Wu, X., Zhao, D., Li, H., & Zhai, J. (2011). An improved Prewitt algorithm for edge detection based on noised image. Paper presented at 4th International congress on image and signal processing, Shanghai. DOI: https://doi.org/10.1109/CISP.2011.6100495