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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