A fuzzy inference system for multispectral image classification

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations


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.

Original languageEnglish
Title of host publicationProceedings of the 2016 IEEE ANDESCON, ANDESCON 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509025312
StatePublished - 27 Jan 2017
Externally publishedYes
Event2016 IEEE ANDESCON, ANDESCON 2016 - Arequipa, Peru
Duration: 19 Oct 201621 Oct 2016

Publication series

NameProceedings of the 2016 IEEE ANDESCON, ANDESCON 2016


Conference2016 IEEE ANDESCON, ANDESCON 2016


  • fuzzy inference systems
  • image processing
  • multispectral image classification
  • remote sensing


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