[ Approche hybride de classification combinant la méthode orientée objet et un système expert pour l'extraction d'une carte d'occupation de sol sur image très haute résolution spatiale de la ville de Rabat (Maroc) ]
Volume 10, Issue 2, February 2015, Pages 594–603
Rida Azmi1, Abderrahim Saadane2, Ilias Kacimi3, and Mustapha Hakdaoui4
1 Département de Géologie, Université Mohamed V, Rabat, Morocco
2 Département des Sciences de la terre, Ecole Nationale Supérieure des Mines de Rabat, Rabat, Morocco
3 Laboratoire d'Océanologie, Géodynamique et Génie Géologique, Faculté des Sciences Agdal-Rabat, Morocco
4 Laboratoire de Géologie Appliquée, Géomatique et Environnement, Faculté des sciences Ben M'sick, Université Hassan II, Casablanca, Morocco
Original language: French
Copyright © 2015 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
In this work, we present a hybrid classification technique combining an expert system and an object-oriented approach. The expert system allows the integration of a knowledge base built through a series of deductive rules, that will guide the classification whose primitives requires informations on the highest level and will be represented by semantic objects, not pixels. Instead of the original bands only, other derived data combining textural, spectral information and shapes, are included in the classification process. The result is then combined with an expert system whose rules use variables such as vegetation index (NDVI), shading of building objects and other indicators. In conclusion, this approach has allowed us to improve the accuracy of the feature extraction method by extracting objects like, roads, trees, grass, bare soil and shadow on a very high-resolution image of the city of Rabat.
Author Keywords: Feature Extraction, Expert System, Fuzzy Classification, rules based classification, high-resolution.
Volume 10, Issue 2, February 2015, Pages 594–603
Rida Azmi1, Abderrahim Saadane2, Ilias Kacimi3, and Mustapha Hakdaoui4
1 Département de Géologie, Université Mohamed V, Rabat, Morocco
2 Département des Sciences de la terre, Ecole Nationale Supérieure des Mines de Rabat, Rabat, Morocco
3 Laboratoire d'Océanologie, Géodynamique et Génie Géologique, Faculté des Sciences Agdal-Rabat, Morocco
4 Laboratoire de Géologie Appliquée, Géomatique et Environnement, Faculté des sciences Ben M'sick, Université Hassan II, Casablanca, Morocco
Original language: French
Copyright © 2015 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
In this work, we present a hybrid classification technique combining an expert system and an object-oriented approach. The expert system allows the integration of a knowledge base built through a series of deductive rules, that will guide the classification whose primitives requires informations on the highest level and will be represented by semantic objects, not pixels. Instead of the original bands only, other derived data combining textural, spectral information and shapes, are included in the classification process. The result is then combined with an expert system whose rules use variables such as vegetation index (NDVI), shading of building objects and other indicators. In conclusion, this approach has allowed us to improve the accuracy of the feature extraction method by extracting objects like, roads, trees, grass, bare soil and shadow on a very high-resolution image of the city of Rabat.
Author Keywords: Feature Extraction, Expert System, Fuzzy Classification, rules based classification, high-resolution.
Abstract: (french)
Dans ce travail nous présentons une technique de classification hybride combinant un système expert et une approche orientée objet. Le système expert permet l'intégration d'une base des connaissances construites par une série des règles déductives, qui vont guider la classification dont les primitives nécessitent des informations de haut niveau, et qui seront représentées par des objets sémantiques et non par des pixels. Au lieu des bandes originales seules, d'autres données dérivées combinant à la fois les informations texturales, spectrales et de formes, sont intégrées dans le processus de classification. Le résultat est ensuite piloté par un système expert dont les règles utilisent des variables telles que l'indice de végétation (NDVI), l'ombrage des objets représentant le bâti et d'autres indicateurs de formes. En conclusion, cette approche nous a permis d'améliorer la précision de l'extraction du bâti, réseau routier, arbres, pelouse, sol nu et ombre sur une image de très haute résolution spatiale de la ville de Rabat.
Author Keywords: Classification floue, Extraction des primitives, System Expert, règles de décision.
How to Cite this Article
Rida Azmi, Abderrahim Saadane, Ilias Kacimi, and Mustapha Hakdaoui, “Hybrid classification approach combining object oriented method and expert system for extracting land cover map from very high spatial resolution image – case study city of Rabat – Morocco,” International Journal of Innovation and Applied Studies, vol. 10, no. 2, pp. 594–603, February 2015.
