@inproceedings{0e005e7ca4bb4ab68418b71a74bd1d8d,
title = "Semi-automatic determination of geometrical properties of short natural fibers in biocomposites by digital image processing",
abstract = "The present article proposes a method for the estimation of geometrical properties of short natural fibers that act as reinforcing phase in polymeric composites. The extraction of the image attributes is performed based on the analysis of microscopic images taken in different sections of the material, requiring a minimal user intervention. The proposed method estimates the orientation tensor of the short fibers from geometrical characteristics such as inclination, length, width and aspect ratio, using an elliptical covering on each fiber. The method validation was performed on a polypropylene composite reinforced with 30% by weight of bamboo short fibers (guadua angustifolia species), the accuracy and precision of the proposed method proved to be adequate. The a 11 element of the orientation tensor was evaluated and the results agree in 98% with respect to the commercial software. This technique is a fast alternative of low cost in characterization of new materials. ",
keywords = "Biomaterials, Composite materials, Digital image processing, Orientation tensor",
author = "Victoria Mera-Moya and Fajardo, {Jorge I.} and {de Paula Junior}, {I{\'a}lis C.} and Leslie Bustamante and Cruz, {Luis J.} and Thiago Barros",
year = "2018",
month = jan,
day = "1",
doi = "10.1007/978-3-319-73450-7_37",
language = "English (US)",
isbn = "9783319734491",
series = "Advances in Intelligent Systems and Computing",
pages = "387--396",
editor = "Alvaro Rocha and Teresa Guarda",
booktitle = "Semi-automatic determination of geometrical properties of short natural fibers in biocomposites by digital image processing",
note = "Advances in Intelligent Systems and Computing ; Conference date: 01-01-2015",
}