Title :
A simple estimation the number of classes in satellite imagery
Author :
Koonsanit, Kitti ; Jaruskulchai, Chuleerat
Author_Institution :
Dept. of Comput. Sci., Kasetsart Univ., Bangkok, Thailand
Abstract :
Clustering is a popular tool for exploratory data analysis, such as K-means and Fuzzy C-mean. A simple estimation the number of classes for segmented areas (K) in satellite imagery application is often needed in advance as an input parameter to the K-means algorithm. In this paper, a method has been developed to estimate the number of classes for segmented areas in satellite imagery clustering application using an image processing technique based on the co-occurrence matrix technique. The proposed method was tested using data from known the number of classes with satellite imagery. The results from the tests confirm the effectiveness of the proposed method in finding the estimation the number of classes and compared with ground truth data.
Keywords :
image segmentation; matrix algebra; pattern clustering; K-means; co-occurrence matrix; exploratory data analysis; fuzzy C-mean; image processing; satellite imagery application; satellite imagery clustering; segmented areas; simple estimation; Clustering algorithms; Color; Educational institutions; Estimation; Image segmentation; Pattern recognition; Satellites; Segmentation; clustering; satellite image; the number of classes; the number of clusters;
Conference_Titel :
ICT and Knowledge Engineering (ICT & Knowledge Engineering), 2011 9th International Conference on
Conference_Location :
Bangkok
Print_ISBN :
978-1-4577-2161-8
DOI :
10.1109/ICTKE.2012.6152390