Automatic Recognition of Asphalt Pavement Cracks Based on Image Processing and Machine Learning Approaches: A Comparative Study on Classifier Performance
Joint Authors
Nguyen, Quoc-Lam
Hoang, Nhat-Duc
Source
Mathematical Problems in Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-07-11
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
Periodic surveys of asphalt pavement condition are very crucial in road maintenance.
This work carries out a comparative study on the performance of machine learning approaches used for automatic pavement crack recognition.
Six machine learning approaches, Naïve Bayesian Classifier (NBC), Classification Tree (CT), Backpropagation Artificial Neural Network (BPANN), Radial Basis Function Neural Network (RBFNN), Support Vector Machine (SVM), and Least Squares Support Vector Machine (LSSVM), have been employed.
Additionally, Median Filter (MF), Steerable Filter (SF), and Projective Integral (PI) have been used to extract useful features from pavement images.
In the feature extraction phase, performance comparison shows that the input pattern including the diagonal PIs enhances the classification performance significantly by creating more informative features.
A simple moving average method is also employed to reduce the size of the feature set with positive effects on the model classification performance.
Experimental results point out that LSSVM has achieved the highest classification accuracy rate.
Therefore, this machine learning algorithm used with the feature extraction process proposed in this study can be a very promising tool to assist transportation agencies in the task of pavement condition survey.
American Psychological Association (APA)
Hoang, Nhat-Duc& Nguyen, Quoc-Lam. 2018. Automatic Recognition of Asphalt Pavement Cracks Based on Image Processing and Machine Learning Approaches: A Comparative Study on Classifier Performance. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-16.
https://search.emarefa.net/detail/BIM-1208314
Modern Language Association (MLA)
Hoang, Nhat-Duc& Nguyen, Quoc-Lam. Automatic Recognition of Asphalt Pavement Cracks Based on Image Processing and Machine Learning Approaches: A Comparative Study on Classifier Performance. Mathematical Problems in Engineering No. 2018 (2018), pp.1-16.
https://search.emarefa.net/detail/BIM-1208314
American Medical Association (AMA)
Hoang, Nhat-Duc& Nguyen, Quoc-Lam. Automatic Recognition of Asphalt Pavement Cracks Based on Image Processing and Machine Learning Approaches: A Comparative Study on Classifier Performance. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-16.
https://search.emarefa.net/detail/BIM-1208314
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1208314