JOURNAL ARTICLE

Mathematical Morphology Based Asphalt Pavement Crack Detection

Abstract

Conventional visual and manual analysis approaches to pavement crack detection are costly, time-consuming, labor-intensive, and subjective. This paper proposed a scheme of automated detection of asphalt pavement surface images. Image enhancement based on mathematical morphologic operations was first performed, then the image is segmented based on the threshold method. The main idea of the proposed image segmentation method is that the threshold values of gray-level pavement images are strongly related with the values of the mean and standard deviation of the pixel intensities. The experimental results have demonstrated that the proposed approach can determine the threshold values accurately and quickly.

Keywords:
Mathematical morphology Pixel Computer science Segmentation Image segmentation Standard deviation Artificial intelligence Asphalt Computer vision Asphalt pavement Road surface Image (mathematics) Visual inspection Image processing Pattern recognition (psychology) Mathematics Materials science Statistics Composite material

Metrics

7
Cited By
0.80
FWCI (Field Weighted Citation Impact)
4
Refs
0.77
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Measurement and Detection Methods
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Infrastructure Maintenance and Monitoring
Physical Sciences →  Engineering →  Civil and Structural Engineering
Vehicle License Plate Recognition
Physical Sciences →  Engineering →  Media Technology
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