Using self-organizing maps approach to pipeline localization


== Abstract ==

International audience; The aim of this paper is to detect and follow the pipeline in sonar imagery. This work is performed in two steps. The first is to split an image (first experiment) or an transformed line image of pipeline image (second experiment) into regions of uniform texture using the Gray Level Co-occurrence Matrix Method (GLCM). The second addresses the unsupervised learning method based on the Artificial Neural Networks (Self-Organizing Map or SOM) used for determining the comparative model of pipeline from the image. To increase the performance of SOM, we propose a penalty function based on data histogram visualization for detecting the position of pipeline. After a brief review of both techniques (GLCM and SOM), we will present our methods and some results from several experiments on the real world data set.


== Original document ==

The different versions of the original document can be found in:

* [https://hal-lirmm.ccsd.cnrs.fr/lirmm-00141703/file/Ocean2003_b.PDF https://hal-lirmm.ccsd.cnrs.fr/lirmm-00141703/file/Ocean2003_b.PDF]

* [http://xplorestaging.ieee.org/ielx5/9015/28618/01282919.pdf?arnumber=1282919 http://xplorestaging.ieee.org/ielx5/9015/28618/01282919.pdf?arnumber=1282919],
: [http://dx.doi.org/10.1109/oceans.2003.1282919 http://dx.doi.org/10.1109/oceans.2003.1282919]

* [http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.ieee-000001282919 http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.ieee-000001282919],
: [https://www.researchgate.net/profile/Bruno_Jouvencel/publication/4065819_Using_Self-Organizing_Maps_Approach_to_Pipeline_Localization/links/00b49518898266504d000000.pdf https://www.researchgate.net/profile/Bruno_Jouvencel/publication/4065819_Using_Self-Organizing_Maps_Approach_to_Pipeline_Localization/links/00b49518898266504d000000.pdf],
: [https://hal-lirmm.ccsd.cnrs.fr/docs/00/14/17/03/PDF/Ocean2003_b.PDF https://hal-lirmm.ccsd.cnrs.fr/docs/00/14/17/03/PDF/Ocean2003_b.PDF],
: [https://ieeexplore.ieee.org/document/1282919 https://ieeexplore.ieee.org/document/1282919],
: [https://hal-lirmm.ccsd.cnrs.fr/docs/00/19/19/31/PDF/D117.PDF https://hal-lirmm.ccsd.cnrs.fr/docs/00/19/19/31/PDF/D117.PDF],
: [https://academic.microsoft.com/#/detail/1491751277 https://academic.microsoft.com/#/detail/1491751277]

* [https://hal-lirmm.ccsd.cnrs.fr/lirmm-00141703 https://hal-lirmm.ccsd.cnrs.fr/lirmm-00141703],
: [https://hal-lirmm.ccsd.cnrs.fr/lirmm-00141703/document https://hal-lirmm.ccsd.cnrs.fr/lirmm-00141703/document],
: [https://hal-lirmm.ccsd.cnrs.fr/lirmm-00141703/file/Ocean2003_b.PDF https://hal-lirmm.ccsd.cnrs.fr/lirmm-00141703/file/Ocean2003_b.PDF]

* [https://hal-lirmm.ccsd.cnrs.fr/lirmm-00269450 https://hal-lirmm.ccsd.cnrs.fr/lirmm-00269450],
: [https://hal-lirmm.ccsd.cnrs.fr/lirmm-00269450/document https://hal-lirmm.ccsd.cnrs.fr/lirmm-00269450/document],
: [https://hal-lirmm.ccsd.cnrs.fr/lirmm-00269450/file/D117.PDF https://hal-lirmm.ccsd.cnrs.fr/lirmm-00269450/file/D117.PDF]