Abstract
Granulometry formalizes the intuitive geometric notion of a sieving process. It was initially set oriented to extract size distribution from binary images, and has been extended to function operators to analyze and extract texture features in grey-scale images. In this paper, we study and establish granulometry with respect to grey-scale morphological operators based on fuzzy logic. We discuss applications of the granulometry in image analysis. A numerical experiment shows that granulometry is a powerful tool for image denoising for image analysis and processing.
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© 2007 Springer-Verlag Berlin Heidelberg
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Deng, T., Chen, Y. (2007). A Morphological Approach for Granulometry with Application to Image Denoising. In: Cao, BY. (eds) Fuzzy Information and Engineering. Advances in Soft Computing, vol 40. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71441-5_100
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DOI: https://doi.org/10.1007/978-3-540-71441-5_100
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71440-8
Online ISBN: 978-3-540-71441-5
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