Cement notch groove pavement image noise reduction enhancement and crack feature extraction method

Abstract

The present invention discloses a cement notch groove pavement image noise reduction enhancement and crack feature extraction method aiming at the problems that the pavement contrast is too low causedby external factors and the payment spots and notch groove autointerference caused by pavement materials. The method comprises the following steps of: employing an improved local adaptive contrast enhancement algorithm to enhance image contrast after graying processing of an original cement pavement image; employing translation invariance Shearlet transform denoising algorithm of an improved P-Mmodel to remove speckle noise caused by pavement materials; employing a cement notch groove pavement image smoothing model established based on an unidirectional total variation UTV model to the imageafter denoising to remove a pavement notch groove influencing feature extraction; and combining a connected domain mark method, a projection method and a rectangular frame method to extract a crack type determination method and a crack feature calculation method to achieve digital description of crack features. The cement notch groove pavement image noise reduction enhancement and crack feature extraction method is systematic and comprehensive, small in calculated amount and easy to apply.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a method for image noise reduction enhancement and crack feature extraction of cement groove pavement. Background technique [0002] For a long time, road traffic has been closely related to our life. It not only guarantees our normal work and study, but also provides convenience for all kinds of travel and greatly promotes the development of society. As of July 2017, the mileage of expressways in my country has reached 131,000 kilometers. However, with the increase in the total mileage of highways, road surface protection has become more and more important. The highways built in the early stage will inevitably be damaged due to the continuous influence of factors such as natural environment and vehicle load. Therefore, in order to avoid the expansion of damage, it is particularly important to formulate corresponding road surface protection strategies in time. [0003] The degree...

AI Technical Summary

Problems solved by technology

[0005] At present, crack extraction methods will more or less have the following problems in the entire crack detection work, such as image contrast enhancement: some methods use the traditional local adaptive contrast enhancement algorithm to make the details of the image more prominent. It does not solve the problem of low crack recognition accuracy caused by uneven image brightness; in terms of interference noise removal: some methods use the translation-invariant Shearlet transform denoising method, although it can solve the image edge caused by the pseudo-Gibbs effect to a certain extent Blur problem, but the edge information of cracks in the image still cannot be completely preserved for low signal-to-noise ratio road images; in terms of road groove removal: Hough transform can only remove part of the crack interference, and will remove the horizontal segment in the crack; The fast Fourier transform weakens the edge information of the crack while weakening the edge of the groove, making the resulting image blurred

Images