Ribeiriño bridge (case study)
Object description
(No object description available.)
Object analysis
The methodology includes survey planning and data acquisition, data filtering, generation of ortho-images and image classification using K-means and Fuzzy C-means algorithms. Both algorithms are evaluated using two classes (biological crusts and concrete) and three classes (biological crusts, water and concrete). The selection of these algorithms is motivated by their simplicity and efficiency.
Object state
The primary goal is to evaluate the possibility of using intensity information from laser scanning data to detect areas with water presence and vegetation in bridge abutments and pillars. Additional goals are to increase the degree of automation of bridge inspection work and contribute providing quantitative and qualitative information for the bridge management systems.
Images
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Documents
This case study was contributed by Gabriel Suárez of Universidad De Vigo. Last edited by technical staff.