NDLI: Sistema de segmentação de imagens para quantificação de microestruturas em metais utilizando redes neurais artificiais

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Sistema de segmentação de imagens para quantificação de microestruturas em metais utilizando redes neurais artificiais

Content Provider	Semantic Scholar
Author	Albuquerque, Victor Hugo C. Cortez, Paulo César Alexandria, Auzuir Ripardo De Aguiar, Willys Machado Silva, Edgard De Macedo
Copyright Year	2007
Abstract	Digital Image Processing is an increasing expansion area in some field of application that uses the interpretation of images as tool. Quantitative Metallography area applied to Materials Sciences uses this technique for characterization of phase volumetric fractions, grain size, inclusion distribution determination and other parameters that influence the properties of the materials. The present paper has, as main objective, to present and validate the software Segmentation by Artificial Neural Network (SVRNA), developed by the authors. This software, based on artificial neural network, makes the percentile constituent counting in time reduced in relation to the conventional model. The study is carried out over ABNT 1020 and 1045 steel and nodular cast iron samples. Statistical analysis showed that this software is efficient for admitted degree of significance. It has concluded, therefore, that the program can be used in applications in the field of Material Sciences for determination of microstructures.
Starting Page	394
Ending Page	407
Page Count	14
File Format	PDF HTM / HTML
DOI	10.1590/S1517-70762007000200018
Volume Number	12
Alternate Webpage(s)	http://www.materia.coppe.ufrj.br/sarra/artigos/artigo10671/10671.pdf
Alternate Webpage(s)	https://doi.org/10.1590/S1517-70762007000200018
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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