Survey: Fundamental Pavement Crack Imaging Algorithms

by Hosin Lee, Univ of Utah, Salt Lake City, United States,



Document Type: Proceeding Paper

Part of: Digital Image Processing: Techniques and Applications in Civil Engineering

Abstract:

Many algorithms for distinguishing pavement cracks from background noise are based on the geometric characteristics of noise, such as shape and size. The objective of this paper is to present various image processing algorithms which can be applied over wide ranges of pavement types under different lighting conditions. The paper briefly discusses fifteen basic algorithms from simple histogram threshold algorithm to neural network procedure. This paper discusses each algorithm rather than each individual automated crack imaging device.

Subject Headings: Algorithms | Cracking | Computer vision and image processing | Pavement condition | Signal processing | Noise pollution | Neural networks

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