Mathematical Morphology Based Asphalt Pavement Crack Detection

2009 ◽  
Author(s):  
Na Wei ◽  
Xiangmo Zhao ◽  
Tao Wang ◽  
Hongxun Song
Keyword(s):  
Mathematical Morphology ◽  
Crack Detection ◽  
Asphalt Pavement ◽  
Pavement Crack Detection

scholarly journals Three-Dimensional Asphalt Pavement Crack Detection Based on Fruit Fly Optimisation Density Peak Clustering

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Wei Li ◽  
Ranran Deng ◽  
Yingjie Zhang ◽  
Zhaoyun Sun ◽  
Xueli Hao ◽  
...  
Keyword(s):  
Crack Detection ◽  
Clustering Algorithm ◽  
Asphalt Pavement ◽  
Fruit Fly ◽  
Detection Methods ◽  
Detection Accuracy ◽  
Density Peak ◽  
3D Data ◽  
Density Peak Clustering ◽  
Pavement Crack Detection

Complex pavement texture and noise impede the effectiveness of existing 3D pavement crack detection methods. To improve pavement crack detection accuracy, we propose a 3D asphalt pavement crack detection algorithm based on fruit fly optimisation density peak clustering (FO-DPC). Firstly, the 3D data of asphalt pavement are collected, and a 3D image acquisition system is built using Gocator3100 series binocular intelligent sensors. Then, the fruit fly optimisation algorithm is adopted to improve the density peak clustering algorithm. Clustering analysis that can accurately detect cracks is performed on the height characteristics of the 3D data of the asphalt pavement. Finally, the clustering results are projected onto a 2D space and compared with the results of other 2D crack detection methods. Following this comparison, it is established that the proposed algorithm outperforms existing methods in detecting asphalt pavement cracks.

Asphalt pavement crack detection based on multi-scale full convolutional network

2021 ◽  
Vol 40 (1) ◽  
pp. 1495-1508
Author(s):  
Yangxu Wu ◽  
Wanting Yang ◽  
Jinxiao Pan ◽  
Ping Chen
Keyword(s):  
Crack Detection ◽  
Asphalt Pavement ◽  
Semantic Segmentation ◽  
Svm Classifier ◽  
Convolutional Network ◽  
Data Set ◽  
Important Indicator ◽  
Standard Data ◽  
Multi Scale ◽  
Pavement Crack Detection

Pavement crack assessment is an important indicator for evaluating road health. However, due to the dark color of the asphalt pavement and the texture characteristics of the pavement, current asphalt pavement crack detection technology cannot meet the requirements of accuracy and efficiency. In this paper, we propose an end-to-end multi-scale full convolutional neural network to achieve the semantic segmentation of cracks in road images by learning the crack characteristics in the complex fine grain background of asphalt pavement. The method uses DenseNet and deconvolution network framework to achieve pixel-level detection and fuses features learned from different scales of convolutional kernels through a full convolutional network to obtain richer information on multi-scale features, allowing more detailed representation of crack features in high-resolution images. And the back end joins the SVM classifier to achieve crack classification after crack segmentation. Then we create a road test standard data set containing 12 cracks and evaluate it on the data. The experimental results show that the method achieves good segmentation effect for 12 types of cracks, and the crack segmentation for asphalt pavement is better than the most advanced methods.

Asphalt Pavement Crack Detection Based on SegNet Network

CICTP 2020 ◽  
2020 ◽  
Author(s):  
M. Jun Zhao ◽  
Beibei Song ◽  
M. Fan He ◽  
M. Suina Ma ◽  
M. Fangfang Kong
Keyword(s):  
Crack Detection ◽  
Asphalt Pavement ◽  
Pavement Crack Detection

An efficient and reliable coarse-to-fine approach for asphalt pavement crack detection

2017 ◽  
Vol 57 ◽  
pp. 130-146 ◽  
Author(s):  
Dejin Zhang ◽  
Qingquan Li ◽  
Ying Chen ◽  
Min Cao ◽  
Li He ◽  
...  
Keyword(s):  
Crack Detection ◽  
Asphalt Pavement ◽  
Pavement Crack Detection ◽  
Coarse To Fine

Gabor filter fusion network for pavement crack detection

2020 ◽  
Vol 13 (6) ◽  
pp. 1-9
Author(s):  
CHEN Xiao-Dong ◽  
◽  
AI Da-Hang ◽  
ZHANG Jia-Chen ◽  
CAI Huai-Yu ◽  
...  
Keyword(s):  
Crack Detection ◽  
Gabor Filter ◽  
Pavement Crack Detection
Sign in / Sign up

Export Citation Format

Share Document