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Spectral fuzzy classification: An application.


Amo, Ana del and Montero de Juan, Francisco Javier and Fernández, Angela and López, Marina and Tordesillas, José Manuel and Biging, Greg (2002) Spectral fuzzy classification: An application. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 32 (1). pp. 42-48. ISSN 1094-6977

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Geographical information (including remotely sensed data) is usually imprecise, meaning that the boundaries between different phenomena are fuzzy. In fact, many classes in nature show internal gradual differences in species, health, age, moisture, as well other factors. If our classification model does not acknowledge that those classes are heterogeneous, and crisp classes are artificially imposed, a final careful analysis should always search for the consequences of such an unrealistic assumption. In this correspondence, we consider the unsupervised algorithm presented in [3], and its application to a real image in Sevilla province (south Spain). Results are compared with those obtained from the ERDAS ISO-DATA classification program on the same image, showing the accuracy of our fuzzy approach. As a conclusion, it is pointed out that whenever real classes are natural fuzzy classes, with gradual transition between classes, then its fuzzy representation will be more easily understood-and therefore accepted-by users.

Item Type:Article
Uncontrolled Keywords:Fuzzy classification; Outranking models; Remote sensing
Subjects:Sciences > Computer science > Artificial intelligence
Sciences > Mathematics > Logic, Symbolic and mathematical
ID Code:16777

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