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Segmentation of multi-spectral images using the combined classifier approach
- Source :
-
Image & Vision Computing . Jun2003, Vol. 21 Issue 6, p473. 10p. - Publication Year :
- 2003
-
Abstract
- Segmentation methods, combining spectral and spatial information, are essential for analysis of multi-spectral images. In this article, we propose such a method based on statistical pattern recognition algorithms and a combined classifier approach. A set of experiments is presented with multi-spectral images of detergent laundry powders acquired by imaging cross-sections with scanning electron microscopy using energy-dispersive X-ray microanalysis (SEM/EDX). The algorithm stability and the segmentation quality are investigated. The use of a priori information for the segmentation of images with similar spectral properties is studied as well. Finally, a comparison with probabilistic relaxation method for multi-spectral image segmentation is made. [Copyright &y& Elsevier]
- Subjects :
- *IMAGING systems
*REMOTE sensing
Subjects
Details
- Language :
- English
- ISSN :
- 02628856
- Volume :
- 21
- Issue :
- 6
- Database :
- Academic Search Index
- Journal :
- Image & Vision Computing
- Publication Type :
- Academic Journal
- Accession number :
- 9793278
- Full Text :
- https://doi.org/10.1016/S0262-8856(03)00013-1