16 resultados para Fractal Descriptors
Filtro por publicador
- Aberdeen University (1)
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- Deakin Research Online - Australia (60)
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- Diposit Digital de la UB - Universidade de Barcelona (1)
- Duke University (3)
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- Indian Institute of Science - Bangalore - Índia (60)
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- Universidad Autónoma de Nuevo León, Mexico (5)
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- Universidad del Rosario, Colombia (9)
- Universidad Politécnica de Madrid (25)
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- Universidade Federal do Pará (2)
- Universidade Federal do Rio Grande do Norte (UFRN) (44)
- Universitat de Girona, Spain (29)
- Universitätsbibliothek Kassel, Universität Kassel, Germany (4)
- Université de Lausanne, Switzerland (2)
- Université de Montréal, Canada (16)
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- University of Queensland eSpace - Australia (10)
- University of Southampton, United Kingdom (2)
- University of Washington (2)
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- Worcester Research and Publications - Worcester Research and Publications - UK (2)
Resumo:
Although the hydrophobicity is usually an arduous parameter to be determined in the field, it has been pointed out as a good option to monitor aging of polymeric outdoor insulators. Concerning this purpose, digital image processing of photos taken from wet insulators has been the main technique nowadays. However, important challenges on this technique still remain to be overcome, such as; images from non-controlled illumination conditions can interfere on analyses and no existence of standard surfaces with different levels of hydrophobicity. In this paper, the photo image samples were digitally filtered to reduce the illumination influence, and hydrophobic surface samples were prepared from wetting silicon surfaces with solution of water-alcohol. Furthermore norevious studies triying to quantify and relate these properties in a mathematical function were found, that could be used in the field by the electrical companies. Based on such considerations, high quality images of countless hydrophobic surfaces were obtained and three different image processing methodologies, the fractal dimension and two Haralick textures descriptors, entropy and homogeneity, associated with several digital filters, were compared. The entropy parameter Haralick's descriptors filtered with the White Top-Hat filter presented the best result to classify the hydrophobicity.