Crack Detection Based on Gaussian Mixture Model using Image Filtering

被引:0
|
作者
Ogawa, Shujiro [1 ]
Matsushima, Kousuke [2 ]
Takahashi, Osamu [3 ]
机构
[1] Natl Inst Technol, Kurume Coll, Adv Engn Course, Fukuoka, Japan
[2] Natl Inst Technol, Kurume Coll, Dept Control & Informat Syst Engn, Fukuoka, Japan
[3] Nagaoka Univ Technol, Dept Civil & Environm Engn, Niigata, Japan
关键词
Gaussian Mixture Model; Image processing; Pavement crack detection; ALGORITHM;
D O I
10.1109/isee2.2019.8921060
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Pavement cracks are caused by various factors such as aged deterioration, load and weather conditions, and so on. As these reduce the safety of road traffic, regular inspections are necessary. In recent years, various crack detection methods using pavement images have been proposed. However, they often have problems with accuracy and processing time. Therefore, we considered the crack detection from the viewpoint of image segmentation. In this paper, we propose a new crack detection method combining GMM and image processing which is filtering. The experimental results show that our proposed method is superior to the state-of-the-art crack detection methods in both accuracy and processing time.
引用
收藏
页码:79 / 84
页数:6
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