RT Journal Article
T1 Spectral fuzzy classification: An application
A1 Del Amo, Ana
A1 Montero De Juan, Francisco Javier
A1 Fernández, Angela
A1 López, Marina
A1 Tordesillas, José Manuel
A1 Biging, Greg
AB 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.
PB IEEE-Inst Electrical Electronics Engineers Inc
SN 1094-6977
YR 2002
FD 2002
LK https://hdl.handle.net/20.500.14352/57610
UL https://hdl.handle.net/20.500.14352/57610
LA eng
NO Kachroo, P., Shedied, S.A., Vanlandingham, H.: Pursuit evasion: the herding noncooperative dynamic game - the stochastic model. IEEE Trans. Syst., Man, Cybern. C. 32, 37-42 (2002). https://doi.org/10.1109/TSMCC.2002.1009131
DS Docta Complutense
RD 12 abr 2025