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Fractal Analysis of Laplacian Pyramidal Filters Applied to Segmentation of Soil Images

The laplacian pyramid is a well-known technique for image processing in which local operators of many scales, but identical shape, serve as the basis functions. The required properties to the pyramidal filter produce a family of filters, which is unipara metrical in the case of the classical problem...

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Detalles Bibliográficos
Autores principales: de Castro, J., Ballesteros, F., Méndez, A., Tarquis, A. M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4121259/
https://www.ncbi.nlm.nih.gov/pubmed/25114957
http://dx.doi.org/10.1155/2014/212897
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author de Castro, J.
Ballesteros, F.
Méndez, A.
Tarquis, A. M.
author_facet de Castro, J.
Ballesteros, F.
Méndez, A.
Tarquis, A. M.
author_sort de Castro, J.
collection PubMed
description The laplacian pyramid is a well-known technique for image processing in which local operators of many scales, but identical shape, serve as the basis functions. The required properties to the pyramidal filter produce a family of filters, which is unipara metrical in the case of the classical problem, when the length of the filter is 5. We pay attention to gaussian and fractal behaviour of these basis functions (or filters), and we determine the gaussian and fractal ranges in the case of single parameter a. These fractal filters loose less energy in every step of the laplacian pyramid, and we apply this property to get threshold values for segmenting soil images, and then evaluate their porosity. Also, we evaluate our results by comparing them with the Otsu algorithm threshold values, and conclude that our algorithm produce reliable test results.
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spelling pubmed-41212592014-08-11 Fractal Analysis of Laplacian Pyramidal Filters Applied to Segmentation of Soil Images de Castro, J. Ballesteros, F. Méndez, A. Tarquis, A. M. ScientificWorldJournal Research Article The laplacian pyramid is a well-known technique for image processing in which local operators of many scales, but identical shape, serve as the basis functions. The required properties to the pyramidal filter produce a family of filters, which is unipara metrical in the case of the classical problem, when the length of the filter is 5. We pay attention to gaussian and fractal behaviour of these basis functions (or filters), and we determine the gaussian and fractal ranges in the case of single parameter a. These fractal filters loose less energy in every step of the laplacian pyramid, and we apply this property to get threshold values for segmenting soil images, and then evaluate their porosity. Also, we evaluate our results by comparing them with the Otsu algorithm threshold values, and conclude that our algorithm produce reliable test results. Hindawi Publishing Corporation 2014 2014-07-10 /pmc/articles/PMC4121259/ /pubmed/25114957 http://dx.doi.org/10.1155/2014/212897 Text en Copyright © 2014 J. de Castro et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
de Castro, J.
Ballesteros, F.
Méndez, A.
Tarquis, A. M.
Fractal Analysis of Laplacian Pyramidal Filters Applied to Segmentation of Soil Images
title Fractal Analysis of Laplacian Pyramidal Filters Applied to Segmentation of Soil Images
title_full Fractal Analysis of Laplacian Pyramidal Filters Applied to Segmentation of Soil Images
title_fullStr Fractal Analysis of Laplacian Pyramidal Filters Applied to Segmentation of Soil Images
title_full_unstemmed Fractal Analysis of Laplacian Pyramidal Filters Applied to Segmentation of Soil Images
title_short Fractal Analysis of Laplacian Pyramidal Filters Applied to Segmentation of Soil Images
title_sort fractal analysis of laplacian pyramidal filters applied to segmentation of soil images
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4121259/
https://www.ncbi.nlm.nih.gov/pubmed/25114957
http://dx.doi.org/10.1155/2014/212897
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