Method for quantitatively detecting concrete cracks based on machine vision

Abstract

The present application relates to the technical field of machine vision detection, and particularly relates to a concrete crack quantitative detection method based on machine vision, which comprises the following steps: firstly, acquiring multiple images and local calibration information of a region to be detected, registering the multiple images, and performing scale mapping to construct a local measurement field; secondly, performing multi-scale local phase analysis and bilateral phase symmetry analysis based on the local measurement field to generate a crack structure response field; thirdly, extracting a center line and matching bilateral boundaries, and correcting the center line by using boundary matching residual error; and finally, performing topological stability analysis and geometric consistency analysis to output crack length, width, area and orientation. The present application can reduce scale conversion error, improve fine crack recognition ability and quantitative result consistency.

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