DocumentCode :
3562634
Title :
Local binary pattern texture feature for satellite imagery classification
Author :
Vigneshl, T. ; Thyagharajan, K.K.
Author_Institution :
Dept. of Comput. Sci. & Eng., S.A. Eng. Coll., Chennai, India
fYear :
2014
Firstpage :
1
Lastpage :
6
Abstract :
The Texture Feature Extraction (TFE) plays an important role in satellite image processing application. This paper proposes a novel method for Satellite Imagery Classification. Our proposed method is a combination of Local Binary Pattern (LBP) and Fuzzy c-means classification algorithm. Local Binary Pattern is calculated by thresholding a 3 × 3 neighborhood of each pixel by the center pixel value. During the Feature Extraction Phase, Local Binary Pattern extracts the important characteristics from the satellite images. Fuzzy c-means algorithm classifying the images into different classes. This is a very challenging task in texture feature extraction being used in satellite images.
Keywords :
image processing; remote sensing; Feature Extraction Phase; Fuzzy c-means classification algorithm; Texture Features Extraction; center pixel value; local binary pattern; satellite image processing application; satellite imagery classification; Accuracy; Classification algorithms; Clustering algorithms; Educational institutions; Feature extraction; Remote sensing; Satellites; Classification; Feature extraction; Fuzzy c-means; Local Binary pattern; Satellite image processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Science Engineering and Management Research (ICSEMR), 2014 International Conference on
Print_ISBN :
978-1-4799-7614-0
Type :
conf
DOI :
10.1109/ICSEMR.2014.7043591
Filename :
7043591
Link To Document :
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