GPU-based acceleration of interval type-2 fuzzy c-means clustering for satellite imagery land-cover classification

Author

Long Thanh Ngo ; Dinh Sinh Mai ; Mau Uyen Nguyen

Author_Institution

Dept. of Inf. Syst., Le Quy Don Tech. Univ., Hanoi, Vietnam

fYear

2012

fDate

27-29 Nov. 2012

Firstpage

992

Lastpage

997

Abstract

When processing with large data such as satellite images, the computing speed is the problem need to be resolved. This paper introduces a method to improve the computational efficiency of the interval type-2 fuzzy c-means clustering(IT2-FCM) based on GPU platform and applied to land-cover classification from multi-spectral satellite image. GPU-based calculations are high performance solution and free up the CPU. The experimental results show that the performance of the GPU is many times faster than CPU.

Keywords

computational complexity; fuzzy set theory; geophysical image processing; graphics processing units; image classification; pattern clustering; GPU based acceleration; GPU based calculations; GPU platform; IT2-FCM); computational efficiency; interval type-2 fuzzy c-means clustering; satellite imagery land cover classification; Algorithm design and analysis; Clustering algorithms; Fuzzy logic; Fuzzy sets; Graphics processing units; Partitioning algorithms; Satellites; graphics processing units; high performance computing; interval type-2 fuzzy c-means clustering; type-2 fuzzy sets;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems Design and Applications (ISDA), 2012 12th International Conference on

Conference_Location

Kochi

ISSN

2164-7143

Print_ISBN

978-1-4673-5117-1

Type

conf

DOI

10.1109/ISDA.2012.6416674

Filename

6416674