Abstract
Timely detection of road cracks is vital for efficient maintenance of road pavements. The conventional road condition assessments involve manual surveys that fail to meet the present-day requirements. Hence, there arises a need to assess the pavement conditions using state-of-the-art technology. The presented work addresses this need and utilizes 2D-digital images of roads. The study considers Sobel edge detection operator and analyzes the performance of its components when used individually vis-à-vis when combined for recognizing road cracks. The main feature of this study is to establish a relation between the type of road crack to be recognized, the type of Sobel component to be used, and the direction and orientation of capturing road images. The study concludes by providing guidelines about which element of a Sobel operator is suitable for highlighting which crack type. The results are beneficial when crack highlighting is required at pixel level to provide more precise information about road damage and its severity.
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Acknowledgements
The presented research work is supported by the doctoral fellowship awarded to the first author Ms. Deeksha Arya from the Ministry of Education, India.
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Arya, D., Ghosh, S.K., Toshniwal, D. (2023). Automatic Recognition of Road Cracks Using Sobel Components in Digital Images. In: Devi, L., Das, A., Sahu, P.K., Basu, D. (eds) Proceedings of the Sixth International Conference of Transportation Research Group of India. CTRG 2021. Lecture Notes in Civil Engineering, vol 271. Springer, Singapore. https://doi.org/10.1007/978-981-19-3505-3_11
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DOI: https://doi.org/10.1007/978-981-19-3505-3_11
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