Detection of Manhole Covers in High-Resolution Aerial Images of Urban Areas by Combining Two Methods


Mispositioning of buried utilities is an increasingly important problem both in industrialized and developing countries because of urban sprawl and technological advances. However, a number of these networks have surface access traps, which could be visible on high-resolution airborne or satellite pictures and might function presence indicators. We tend to place forward a methodology to detect manhole covers and grates on very high-resolution aerial and satellite images. 2 methods are tested: the primary is predicated on a geometrical circular filter, whereas the second one uses Machine Learning to retrieve some patterns. The results are compared and combined to benefit from the 2 approaches.

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