A fuzzy inference system for multispectral image classification

Pedro J.Soto Vega, Victor A.Ayma Quirita, Pedro M. Achanccaray, Ricardo Tanscheit, Marley Vellasco

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

2 Citas (Scopus)


This work presents an approach for multispectral image classification that makes use of a Fuzzy Inference System (FIS). An IKONOS satellite sensor image of a neighborhood in Rio de Janeiro, Brazil has been used. The ground truth used in this work comprises six classes: trees, scrub, buildings, roads, water and shadows. Then, inputs sets, rules and outputs sets were defined. Four input variables, based on four indexes computed from the image spectral bands, have been considered: Normalized Difference Vegetation Index (NDVI), Buildings Index (BI), Water Index (WI) and Road Index (RI). Experimental results show that the proposed method outperforms other methods, achieving higher Overall and Average accuracies, providing a better representation of the classification process.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 2016 IEEE ANDESCON, ANDESCON 2016
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781509025312
EstadoPublicada - 27 ene. 2017
Publicado de forma externa
Evento2016 IEEE ANDESCON, ANDESCON 2016 - Arequipa, Perú
Duración: 19 oct. 201621 oct. 2016

Serie de la publicación

NombreProceedings of the 2016 IEEE ANDESCON, ANDESCON 2016


Conferencia2016 IEEE ANDESCON, ANDESCON 2016


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