Water-body segmentation in satellite imagery applying modified Kernel K-means

Yousefi, Paria and Jalab, Hamid Abdullah and Ibrahim, Rabha Waell and Mohd Noor, Nurul Fazmidar and Ayub, Mohamad Nizam and Gani, Abdullah (2018) Water-body segmentation in satellite imagery applying modified Kernel K-means. Malaysian Journal of Computer Science, 31 (2). pp. 143-154. ISSN 0127-9084, DOI https://doi.org/10.22452/mjcs.vol31no2.4.

Full text not available from this repository.
Official URL: https://doi.org/10.22452/mjcs.vol31no2.4


The main purpose of k-Means clustering is partitioning patterns into various homogeneous clusters by minimizing cluster errors, but the modified solution of k-Means can be recovered with the guidance of Principal Component Analysis (PCA). In this paper, the linear Kernel PCA guides k-Means procedure using filter to modify images in situations where some parts are missing by k-Means classification. The proposed method consists of three steps: 1) transformation of the color space and using PCA to solve the eigenvalue problem pertaining to the covariance matrices of satellite image; 2) feature extraction from selected eigenvectors and are rearranged by applying the training map to extract the useful information as a set of new orthogonal variables called principal components; and 3) classification of the images based on the extracted features using k-Means clustering. The quantitative results obtained using the proposed method were compared with k-Means and k-Means PCA techniques in terms of accuracy in extraction. The contribution of this approach is the modification of PCA selection to achieve more accurate extraction of the water-body segmentation in satellite images.

Item Type: Article
Uncontrolled Keywords: Contextual filter; Image segmentation; K-Means clustering; PCA; Satellite images; Statistical pattern recognition; Water feature extraction
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Computer Science & Information Technology
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 12 Feb 2019 01:12
Last Modified: 12 Feb 2019 01:12
URI: http://eprints.um.edu.my/id/eprint/20257

Actions (login required)

View Item View Item