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Method for detecting cracks in bridge image

A detection method and image technology, applied in image enhancement, image analysis, image data processing, etc., can solve problems such as high risk, poor maneuverability, and low efficiency

Active Publication Date: 2019-10-29
HANGZHOU DIANZI UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, this detection method has poor mobility, high risk, and low efficiency. Moreover, due to the subjectivity of manual marking, the detection accuracy is more dependent on the experience and knowledge of experts, and experience lacks objectivity in quantitative analysis.

Method used

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  • Method for detecting cracks in bridge image
  • Method for detecting cracks in bridge image
  • Method for detecting cracks in bridge image

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Embodiment Construction

[0074] The present invention will be further described below in conjunction with accompanying drawing.

[0075] Such as figure 1 As shown, a crack detection method in a bridge image, the specific steps are as follows:

[0076] Step 1. Crack detection

[0077] 1-1. The initial positioning and grayscale of the crack area are performed through the crack detection preprocessing.

[0078] Grayscale processing is performed on the complete bridge deck image. The complete bridge deck image is divided into multiple local regions by uniform meshing. Since the gray value of the target crack of the bridge is lower than the average gray value of the local background, the cumulative gray value in each local area is counted to obtain the gray distribution of all grid areas and the average gray value of the complete bridge deck image is extracted as the gray value Threshold; filter out the grid area whose gray-scale cumulative value is lower than the gray-scale threshold as the region of ...

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Abstract

The invention discloses a method for detecting cracks in a bridge image. Due to the fact that manual marking has certain subjectivity, detection precision depends on experience knowledge of experts, and experience lacks objectivity in quantitative analysis. The method comprises the following steps: 1, detecting the position of a crack in a bridge floor image, and completely extracting the morphological characteristics of the crack; 2, extracting real parameters of cracks in the image. According to the invention, an image processing technology is used to replace human eyes to complete automaticnondestructive detection of bridge cracks. Aiming at the unique spatial ductility and gray distinguishability of bridge cracks, the improved median filtering algorithm is provided, according to the characteristics of crack edge similar gray linear distribution, on the basis of original median filtering, the thought of the similar gray scale extension direction is introduced, interference of bridge floor image composite noise can be restrained more effectively, the signal-to-noise ratio of the image is increased, the continuity of detail information of the crack edge is kept, and the reliability of fidelity filtering of a target crack is improved.

Description

technical field [0001] The invention belongs to the technical field of image detection, and in particular relates to a method for detecting cracks in bridge images. Background technique [0002] As an important carrier connecting two large span points, the internal stress generated by the long-term sun, rain and load operation will also be transmitted to some weak parts along the bridge structure, which makes the surface of the structure prone to exist. Creation and development of cracks. The damage degree of surface cracks with different orientations to the bridge structure is also different. If the extension direction of the surface cracks is perpendicular to the bearing surface of the structure, the damage will be the greatest. [0003] According to engineering practice and theoretical analysis, most bridges in service work with cracks, and the potential damage caused by bridge cracks cannot be underestimated. Once there are serious cracks in the concrete bridge, the ou...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T7/12G06T7/136G06T7/155G06T7/62
CPCG06T7/0004G06T2207/10004G06T2207/20084G06T2207/30132G06T7/12G06T7/136G06T7/155G06T7/62
Inventor 张巨勇王云周洪强何凯陈志平李蓉
Owner HANGZHOU DIANZI UNIV
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