Automatic identification method and system of pavement disease image

An automatic recognition and image technology, applied in the field of image processing, can solve the problem of inability to achieve the recognition effect, and achieve the effect of good robust performance and excellent detection efficiency.

Active Publication Date: 2017-10-03
HUAIYIN INSTITUTE OF TECHNOLOGY
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However, for complex situations that contain more non-crack information and

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  • Automatic identification method and system of pavement disease image
  • Automatic identification method and system of pavement disease image
  • Automatic identification method and system of pavement disease image

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[0030] Below in conjunction with specific embodiment, further illustrate the present invention, should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various equivalent forms of the present invention All modifications fall within the scope defined by the appended claims of the present application.

[0031] Such as figure 1 As shown, a method for automatic recognition of road surface disease images disclosed in the embodiment of the present invention first preprocesses the captured road surface image, then performs edge detection on the preprocessed image, and then performs connected domain contour detection, and based on the connected domain contour The shape of the circumscribed rectangle is used to locate and segment the crack area to obtain the crack feature image, and finally classify the...

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Abstract

The invention provides an automatic identification method and system of a pavement disease image. The method comprises: a shot pavement image is preprocessed, wherein preprocessing includes Gamma gray scale correction, Gaussian filter enhancement and local adaptive binarization; edge detection is carried out on a binarized image; connected domain contour detection is carried out on the image after edge detection to obtain the number of the connected domains and external rectangles of connected domain contours; according to the shapes of the external rectangles of the connected domain contours, a region of a pavement crack is determined; on the basis of position information of the region of the pavement crack, a crack region image is extracted from the image after edge detection and a black template is superposed to form a crack feature image with the size identical with that of the original image; and on the basis of a convolution neural network, the crack feature image is classified. Compared with the prior art, the method and system have the following advantages: the detection efficiency of crack positioning in the pavement disease is high; and for crack images with different features, robustness is high.

Description

technical field [0001] The invention relates to an automatic identification method and system for road surface disease images, belonging to the technical field of image processing. Background technique [0002] Among pavement diseases, pavement cracks are the main form of pavement damage in high-grade highway pavement damage, which is very important for modern and efficient road maintenance. Because the traditional manual detection method is time-consuming, inaccurate, highly dangerous, hinders traffic, and has large subjective differences, high-precision cameras are often used to quickly capture road surface images for automatic computer detection. Various pavement crack detection and localization algorithms have been proposed. [0003] According to the image characteristics of the low gray value of the crack area, Xie Changrong et al. published the research on the image processing algorithm of pavement crack detection by analyzing the superiority of various classic image ...

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Application Information

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IPC IPC(8): G06T7/00G06K9/62G06T7/12G06T7/13G06T7/187
CPCG06T7/0004G06T7/12G06T7/13G06T7/187G06F18/241
Inventor 颉正高尚兵周君姜海林张有东陈晓兵李锐覃方哲
Owner HUAIYIN INSTITUTE OF TECHNOLOGY
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