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Identification, 3D-Reconstruction, and Classification of Dangerous Road Cracks.
Sghaier, Souhir; Krichen, Moez; Ben Dhaou, Imed; Elmannai, Hela; Alkanhel, Reem.
Affiliation
  • Sghaier S; Department of Science and Technology, College of Ranyah, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia.
  • Krichen M; Faculty of Computer Science and Information Technology, Al-Baha University, Al-Baha 65528, Saudi Arabia.
  • Ben Dhaou I; ReDCAD Laboratory, National School of Engineers of Sfax, University of Sfax, Sfax 3029, Tunisia.
  • Elmannai H; Department of Computer Science, Hekma School of Engineering, Computing and Informatics, Dar Al-Hekma University, Jeddah P.O. Box 34801, Saudi Arabia.
  • Alkanhel R; Department of Computing, University of Turku, 20500 Turku, Finland.
Sensors (Basel) ; 23(7)2023 Mar 29.
Article in En | MEDLINE | ID: mdl-37050640
Advances in semiconductor technology and wireless sensor networks have permitted the development of automated inspection at diverse scales (machine, human, infrastructure, environment, etc.). However, automated identification of road cracks is still in its early stages. This is largely owing to the difficulty obtaining pavement photographs and the tiny size of flaws (cracks). The existence of pavement cracks and potholes reduces the value of the infrastructure, thus the severity of the fracture must be estimated. Annually, operators in many nations must audit thousands of kilometers of road to locate this degradation. This procedure is costly, sluggish, and produces fairly subjective results. The goal of this work is to create an efficient automated system for crack identification, extraction, and 3D reconstruction. The creation of crack-free roads is critical to preventing traffic deaths and saving lives. The proposed method consists of five major stages: detection of flaws after processing the input picture with the Gaussian filter, contrast adjustment, and ultimately, threshold-based segmentation. We created a database of road cracks to assess the efficacy of our proposed method. The result obtained are commendable and outperform previous state-of-the-art studies.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Diagnostic_studies Language: En Journal: Sensors (Basel) Year: 2023 Document type: Article Affiliation country: Saudi Arabia Country of publication: Switzerland

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Diagnostic_studies Language: En Journal: Sensors (Basel) Year: 2023 Document type: Article Affiliation country: Saudi Arabia Country of publication: Switzerland