Road Surface State Recognition Based on SVM Optimization and Image Segmentation Processing
Joint Authors
Zhao, Jiandong
Wu, Hongqiang
Chen, Liangliang
Source
Journal of Advanced Transportation
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-21, 21 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-07-06
Country of Publication
Egypt
No. of Pages
21
Main Subjects
Abstract EN
Adverse road condition is the main cause of traffic accidents.
Road surface condition recognition based on video image has become a central issue.
However, hybrid road surface and road surface under different lighting environments are two crucial problems.
In this paper, the road surface states are categorized into 5 types including dry, wet, snow, ice, and water.
Then, according to the original image size, images are segmented; 9-dimensional color eigenvectors and 4 texture eigenvectors are extracted to construct road surface state characteristics database.
Next, a recognition method of road surface state based on SVM (Support Vector Machine) is proposed.
In order to improve the recognition accuracy and the universality, a grid searching algorithm and PSO (Particle Swarm Optimization) algorithm are used to optimize the kernel function factor and penalty factor of SVM.
Finally, a large number of actual road surface images in different environments are tested.
The results show that the method based on SVM and image segmentation is feasible.
The accuracy of PSO algorithm is more than 90%, which effectively solves the problem of road surface state recognition under the condition of hybrid or different video scenes.
American Psychological Association (APA)
Zhao, Jiandong& Wu, Hongqiang& Chen, Liangliang. 2017. Road Surface State Recognition Based on SVM Optimization and Image Segmentation Processing. Journal of Advanced Transportation،Vol. 2017, no. 2017, pp.1-21.
https://search.emarefa.net/detail/BIM-1170881
Modern Language Association (MLA)
Zhao, Jiandong…[et al.]. Road Surface State Recognition Based on SVM Optimization and Image Segmentation Processing. Journal of Advanced Transportation No. 2017 (2017), pp.1-21.
https://search.emarefa.net/detail/BIM-1170881
American Medical Association (AMA)
Zhao, Jiandong& Wu, Hongqiang& Chen, Liangliang. Road Surface State Recognition Based on SVM Optimization and Image Segmentation Processing. Journal of Advanced Transportation. 2017. Vol. 2017, no. 2017, pp.1-21.
https://search.emarefa.net/detail/BIM-1170881
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1170881