Automatic Detection of Concrete Spalling Using Piecewise Linear Stochastic Gradient Descent Logistic Regression and Image Texture Analysis
Joint Authors
Nguyen, Quoc-Lam
Tran, Xuan-Linh
Hoang, Nhat-Duc
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-07-16
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Recognition of spalling on surface of concrete wall is crucial in building condition survey.
Early detection of this form of defect can help to develop cost-effective rehabilitation methods for maintenance agencies.
This study develops a method for automatic detection of spalled areas.
The proposed approach includes image texture computation for image feature extraction and a piecewise linear stochastic gradient descent logistic regression (PL-SGDLR) used for pattern recognition.
Image texture obtained from statistical properties of color channels, gray-level cooccurrence matrix, and gray-level run lengths is used as features to characterize surface condition of concrete wall.
Based on these extracted features, PL-SGDLR is employed to categorize image samples into two classes of “nonspall” (negative class) and “spall” (positive class).
Notably, PL-SGDLR is an extension of the standard logistic regression within which a linear decision surface is replaced by a piecewise linear one.
This improvement can enhance the capability of logistic regression in dealing with spall detection as a complex pattern classification problem.
Experiments with 1240 collected image samples show that PL-SGDLR can help to deliver a good detection accuracy (classification accuracy rate = 90.24%).
To ease the model implementation, the PL-SGDLR program has been developed and compiled in MATLAB and Visual C# .NET.
Thus, the proposed PL-SGDLR can be an effective tool for maintenance agencies during periodic survey of buildings.
American Psychological Association (APA)
Hoang, Nhat-Duc& Nguyen, Quoc-Lam& Tran, Xuan-Linh. 2019. Automatic Detection of Concrete Spalling Using Piecewise Linear Stochastic Gradient Descent Logistic Regression and Image Texture Analysis. Complexity،Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1132263
Modern Language Association (MLA)
Hoang, Nhat-Duc…[et al.]. Automatic Detection of Concrete Spalling Using Piecewise Linear Stochastic Gradient Descent Logistic Regression and Image Texture Analysis. Complexity No. 2019 (2019), pp.1-14.
https://search.emarefa.net/detail/BIM-1132263
American Medical Association (AMA)
Hoang, Nhat-Duc& Nguyen, Quoc-Lam& Tran, Xuan-Linh. Automatic Detection of Concrete Spalling Using Piecewise Linear Stochastic Gradient Descent Logistic Regression and Image Texture Analysis. Complexity. 2019. Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1132263
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1132263