A Study on the Gray Value Distribution Contour Curve Extraction Based on the Image of the Fracture Surface of the Material and Its Fractal Dimension

DOI

10.2991/icmmct-17.2017.166How to use a DOI?

Keywords

Material; fracture surface; gray value distribution; contour curve; fractal dimension

Abstract

It was proposed that the gray value distribution contour curve of the fracture surface of material was used to represent the true contour curve of fracture surface, the gray value distribution contour curve was extracted by the image analysis software IPP(Image Pro-Plus), and the fractal dimension of the gray value distribution contour curve of the fracture surface was measured by the structure function method as polypropylene (PP) was the sample, in order to characterize the morphological characteristic of the fracture surface of material. The results indicated that the gray value distribution contour curve could reflect the multilevel of the fracture surface of the material; the fractal dimension of gray value distribution contour curve of PP was 1.6375, the linear degree of fitted by the structure function method was high and the correlation coefficients obtained were more than 0.99. The strong 1inear correlation indicated that impact fracture surface of the PP had significant fractal characteristics. Thus using the fractal dimensions to describe the fracture surface morphology of material may provide a new approach to investigate the morphology of fracture surface of materials.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Ju Tian
AU  - ChuanSheng Liu
AU  - Chengbao Wu
AU  - Zhenghua Chen
AU  - Jizhao Liang
AU  - Luyao Li
PY  - 2017/04
DA  - 2017/04
TI  - A Study on the Gray Value Distribution Contour Curve Extraction Based on the Image of the Fracture Surface of the Material and Its Fractal Dimension
BT  - Proceedings of the 2017 5th International Conference on Machinery, Materials and Computing Technology (ICMMCT 2017)
PB  - Atlantis Press
SP  - 818
EP  - 824
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmct-17.2017.166
DO  - 10.2991/icmmct-17.2017.166
ID  - Tian2017/04
ER  -