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Pavement disease recognition method based on image analysis

A technology of disease identification and image analysis, applied in image analysis, image enhancement, image data processing, etc., can solve the problems of inability to distinguish disease types, inability to identify shadow interference pollutants, cumbersome calculations, etc.

Active Publication Date: 2017-01-04
HUNAN LIANZHI BRIDGE & TUNNEL TECH
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Problems solved by technology

[0003] The prior art has the following disadvantages in the identification of images: (1) the type of disease cannot be distinguished (the disease specifically includes: cracks, pits, ruts, looseness, subsidence, and surface damage); (2) the calculation is cumbersome and the calculation speed is very slow. Sometimes manual intervention is required; (3) the shadow interference in the road surface image data, the pollutants filled in the damaged pavement, etc. cannot be identified; (4) the false positive rate of disease identification is high, the reliability is low, and sometimes the detection results will appear unidentified. The quality of maintained roads gets better as they are used

Method used

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  • Pavement disease recognition method based on image analysis
  • Pavement disease recognition method based on image analysis

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Embodiment 1

[0061] see figure 1 , a pavement defect recognition method based on image analysis, comprising the following steps:

[0062] The first step is the collection of road surface images, specifically: install the vehicle-mounted high-speed line array camera on the carrying vehicle, and the high-speed line array camera will shoot the entire lane while the carrying vehicle is driving on the road to be detected at a speed of 10-80km / h road surface image; upload the captured road surface image and the geographic location information corresponding to the road surface image to the controller in a wired or wireless manner. The target image containing the damage is extracted (the conventional extraction method in the prior art is used here) for subsequent processing.

[0063] The second step, the preprocessing of the road surface image, specifically: carry out image format recognition processing, image grayscale processing, image smoothing processing, image sharpening processing and edge ...

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Abstract

The invention provides a pavement disease recognition method based on image analysis. The pavement disease recognition method based on image analysis comprises the following steps: step one, acquiring pavement images; step two, preprocessing the pavement images; step three, carrying out segmentation processing on the diseases in the preprocessed pavement images; step four, carrying out feature extraction and measurement on the diseases in the pavement images, specifically carrying out feature extraction and measurement on the diseases in the pavement images in the step three by using an outline area algorithm and an edge detection algorithm successively; and step five, outputting results, specifically accurately positioning the classified and measured diseases on the basis of the geographical location information in the step one through a controller and then outputting the results. By the technical scheme of the invention, labor can be relieved, interference of artificial subjective factors is eliminated, road conditions can be evaluated quickly and accurately, and the shortcomings that cracks are classified by manual judgment, working efficiency is low, error rate is relatively high and the like are overcome.

Description

technical field [0001] The invention relates to the technical field of data image processing, in particular to a method for identifying road surface defects based on image analysis. Background technique [0002] With the development of new technologies for road surface maintenance and the use of various road condition detection equipment, the road condition analysis method has gradually replaced the traditional manual investigation by automatic analysis based on rapid detection equipment. Instrument method, automatic deflection meter, drop hammer deflection meter, laser flatness meter method to measure flatness, etc.; use software to identify and detect road damage rate and other methods. [0003] The prior art has the following disadvantages in the identification of images: (1) the type of disease cannot be distinguished (the disease specifically includes: cracks, pits, ruts, looseness, subsidence, and surface damage); (2) the calculation is cumbersome and the calculation s...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T5/00
CPCG06T7/0002G06T2207/10024G06T5/73G06T5/70
Inventor 梁晓东
Owner HUNAN LIANZHI BRIDGE & TUNNEL TECH
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