원문정보
초록
영어
In this paper, a new road surface crack detection algorithm is proposed; it is based on the ridge edge detection on fractional calculus and the dual-thresholds on a binary image. First, the multi-scale reduction of image data is used to shrink an original image to eliminate noise, which can not only smooth an image but also enhance cracks. Then, the main cracks are extracted by using the ridge edge detection on fractional calculus in a grey scale image. Subsequently, the resulted binary image is further processed by applying both short and long line thresholds to eliminate short curves and noise for getting rough crack segments. Finally the gaps in cracks are connected with a curve connection function which is an artificial intelligence routine. The experiments show that the algorithm for pavement crack images has the good performance of noise immunity, accurate positioning, and high accuracy. It can accurately locate and detect small and thin cracks that are difficult to identify by other traditional algorithms.
목차
1. Introduction
2. Image Transform from Fine Scale to Course Scale
3. Ridge (Valley) Edge Detection based on Fractional Calculus
3.1 Fractional Calculus
3.2 Ridge (Valley) Edge Detection Algorithm
4. Short-term Noise Elimination and Dual-thresholds for Edge Connection
4.1 Short-term Noise Cancellation
4.2 Dual-threshold Gap Linking
5. Experimental Results and Analysis
6. Conclusions
Acknowledgements
References