PROJECT TITLE :

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

ABSTRACT:

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.