Application of Self-Organizing Maps at Change Detection in Amazon Forest

Author

Mendes Mota, Rodrigo Luiz ; Ramos, Alexandre C. B. ; Shiguemori, Elcio H.

Author_Institution

Fed. Univ. of Itajuba, Itajubá, Brazil

fYear

2014

fDate

7-9 April 2014

Firstpage

371

Lastpage

376

Abstract

This paper presents a change detection of aerial images algorithm based on Kohonen self-organizing maps. In this study, a set of images from different period of time from Tapajós National Forest at Amazon forest in Pará, Brazil, has been employed. As input of the self-organizing maps, used as an unsupervised neural network, it was obtained features from the images using three different size of square windows and as output, a map of 16 colors, as 16 groupings. The results are obtained through the comparison between the outputs obtained with these different sizes of windows.

Keywords

feature extraction; forestry; geophysical image processing; self-organising feature maps; unsupervised learning; Amazon forest; Kohonen self-organizing maps; Tapajós National Forest; aerial images algorithm; change detection; feature detection; unsupervised neural network; Feature extraction; Image color analysis; Image edge detection; Neurons; Satellites; Self-organizing feature maps; Amazon forest; Kohonen maps; change detection; computational vision; digital image processing;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Technology: New Generations (ITNG), 2014 11th International Conference on

Conference_Location

Las Vegas, NV

Print_ISBN

978-1-4799-3187-3

Type

conf

DOI

10.1109/ITNG.2014.41

Filename

6822225