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Classification of Satellite Images through Gabor Filter using SVM
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 116 - Number 7 |
| Year of Publication: 2015 |
| Authors: Manali Jain, Amit Sinha |
10.5120/20348-2534
|
Manali Jain, Amit Sinha . Classification of Satellite Images through Gabor Filter using SVM. International Journal of Computer Applications. 116, 7 ( April 2015), 18-21. DOI=10.5120/20348-2534
Abstract
The classification of satellite image has various issues including image quality. The aim of classifying satellite image is to provide better understanding of image . The classification of image depends on various features. the present paper focuses on five categories of satellite image such as residential area, agriculture, desert, mountain and forest. The objective of this paper is to study the use of texture, color, shape as an image feature for pattern retrieval. We propose the novel approach to extract features of image through Gabor filter feature vector i. e color, texture, shape and classification of image through support vector machine (SVM) with the use of Gaussian radial basis kernel function. The proposed methodology gives the better accuracy up to 98. 5% over DCT Gabor based classification. The work is useful and may be embedded with different applications like residential purposes and government planning commission and national environment mission etc.
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