Discovering similarities in Landsat satellite images using the K-means method | Zendy

Paola Ariza-Colpas | Zendy; Ana Isabel Oviedo Carrascal | Zendy; De-la-Hoz-Franco Emiro | Zendy

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Discovering similarities in Landsat satellite images using the K-means method

Author(s) -

Paola Ariza-Colpas,

Ana Isabel Oviedo Carrascal,

De-la-Hoz-Franco Emiro

Publication year - 2020

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2020.03.017

Subject(s) - computer science , segmentation , identification (biology) , satellite , artificial intelligence , computer vision , information retrieval , data mining , pattern recognition (psychology) , natural language processing , botany , engineering , biology , aerospace engineering

This article different ways for the treatment and identification of similarities in satellite images. By means of the systematic review of the literature it is possible to know the different existing forms for the treatment of this type of objects and by means of the implementation that is described, the operation of the K-means algorithm is shown to help the segmentation and analysis of characteristics associated to the color. In this type of objects, a descriptive analysis of the results thrown by the method is finally carried out.

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