Concrete Image Segmentation Based on Multiscale Mathematic Morphology Operators and Otsu Method

Joint Authors

Zhou, Sheng-Bo
Shen, Ai-Qin
Li, Geng-Fei

Source

Advances in Materials Science and Engineering

Issue

Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-11, 11 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2015-10-01

Country of Publication

Egypt

No. of Pages

11

Abstract EN

The aim of the current study lies in the development of a reformative technique of image segmentation for Computed Tomography (CT) concrete images with the strength grades of C30 and C40.

The results, through the comparison of the traditional threshold algorithms, indicate that three threshold algorithms and five edge detectors fail to meet the demand of segmentation for Computed Tomography concrete images.

The paper proposes a new segmentation method, by combining multiscale noise suppression morphology edge detector with Otsu method, which is more appropriate for the segmentation of Computed Tomography concrete images with low contrast.

This method cannot only locate the boundaries between objects and background with high accuracy, but also obtain a complete edge and eliminate noise.

American Psychological Association (APA)

Zhou, Sheng-Bo& Shen, Ai-Qin& Li, Geng-Fei. 2015. Concrete Image Segmentation Based on Multiscale Mathematic Morphology Operators and Otsu Method. Advances in Materials Science and Engineering،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1053122

Modern Language Association (MLA)

Zhou, Sheng-Bo…[et al.]. Concrete Image Segmentation Based on Multiscale Mathematic Morphology Operators and Otsu Method. Advances in Materials Science and Engineering No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1053122

American Medical Association (AMA)

Zhou, Sheng-Bo& Shen, Ai-Qin& Li, Geng-Fei. Concrete Image Segmentation Based on Multiscale Mathematic Morphology Operators and Otsu Method. Advances in Materials Science and Engineering. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1053122

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1053122