@article{fdi:010066922,
  title = {{D}etection of manhole covers in high-resolution aerial images of urban areas by combining two methods},
  author = {{P}asquet, {J}. and {D}esert, {T}. and {B}artoli, {O}. and {C}haumont, {M}. and {D}elenne, {C}. and {S}ubsol, {G}. and {D}erras, {M}. and {C}hahinian, {N}an{\'e}e},
  editor = {},
  language = {{ENG}},
  abstract = {{M}ispositioning of buried utilities is an increasingly important problem both in industrialized and developing countries because of urban sprawl and technological advances. {H}owever, some of these networks have surface access traps, which may be visible on high-resolution airborne or satellite images and could serve as presence indicators. {W}e put forward a methodology to detect manhole covers and grates on very high-resolution aerial and satellite images. {T}wo methods are tested: the first is based on a geometrical circular filter, whereas the second one uses machine learning to retrieve some patterns. {T}he results are compared and combined to benefit from the two approaches.},
  keywords = {{B}uried utility network ; circular object detection ; geometrical filter ; high resolution ; machine learning ; {FRANCE}},
  booktitle = {},
  journal = {{IEEE} {J}ournal of {S}elected {T}opics in {A}pplied {E}arth {O}bservations and {R}emote {S}ensing},
  volume = {9},
  numero = {5},
  pages = {1802--1807},
  ISSN = {1939-1404},
  year = {2016},
  DOI = {10.1109/jstars.2015.2504401},
  URL = {https://www.documentation.ird.fr/hor/fdi:010066922},
}