Abstract
A morphological tool for accurate automatic texture classification is proposed and applied to a large set of plastering mortars. Starting from measurements of morphological data (covariance, speed of erosion and dilation, size distribution, watershed sizing) on grey level images, correspondence analysis is used in a learning procedure to visualize the surfaces in a reduced space, and to select the most pertinent measurements with respect to the classification of textures.
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References
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© 2002 Kluwer Academic/Plenum Publishers
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Aubert, A., Jeulin, D., Hashimoto, R. (2002). Surface Texture Classification from Morphological Transformations. In: Goutsias, J., Vincent, L., Bloomberg, D.S. (eds) Mathematical Morphology and its Applications to Image and Signal Processing. Computational Imaging and Vision, vol 18. Springer, Boston, MA. https://doi.org/10.1007/0-306-47025-X_28
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DOI: https://doi.org/10.1007/0-306-47025-X_28
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-7923-7862-4
Online ISBN: 978-0-306-47025-7
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