Algorithm for recognizing prefabricated reinforced concrete rough surface through images
A reinforced concrete and image recognition technology, applied in the field of image processing, can solve the problems of time-consuming and labor-intensive, low efficiency of concrete rough surface, etc.
Active Publication Date: 2021-03-02
祐云信息技术南通有限公司
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[0005] The technical problem to be solved by the present invention is to provide an image recognition algorithm for the rough surface of prefabricated reinforced concrete, which solves the problem of low efficiency, time-consuming and labor-intensive detection of the rough surface of concrete by the sand pile method in the prior art
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[0036] Below in conjunction with accompanying drawing, structure and working process of the present invention will be further described.
[0037] The machine vision equipment is used to shoot the standard size field of view on the precast concrete surface, and the captured image is used for statistical calculation of the gray level co-occurrence matrix to obtain 6 statistics, and then the K value proximity algorithm is used for classification to obtain the precast concrete roughness grade.
[0038] An image recognition algorithm for prefabricated reinforced concrete rough surfaces, comprising the following steps:
[0039] Step 1. Collect concrete images with known roughness grades, perform image recognition, save the statistics of the gray level co-occurrence matrix according to the grades, and build a concrete rough surface training set, and the roughness grades are obtained through detection by the traditional sand pile method;
[0040] Step 2, collecting the concrete rough ...
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The invention discloses an algorithm for recognizing a prefabricated reinforced concrete rough surface through an image, and the algorithm comprises the steps: firstly collecting a concrete image witha known roughness grade, carrying out the image recognition, storing the statistical magnitude of a gray level co-occurrence matrix according to the grade, building a concrete rough surface trainingset, and obtaining the roughness grade through the detection of a conventional sand piling method; secondly, collecting a concrete rough surface image on a unit area, and carrying out image processingto obtain gray level co-occurrence matrix statistics; then, classifying concrete roughness grades by using a k-value adjacent method; and finally, comparing the obtained concrete roughness grade witha result detected by a traditional sand piling method, and if the result is correct, recording the result into a training set. A concrete rough surface image of a unit area is obtained through machine vision equipment, the concrete roughness grade is rapidly recognized through an image recognition algorithm, and on-site construction personnel are helped to define operation requirements. Algorithmsoftware is integrated into handheld equipment, and roughness grade parameters of the concrete rough surface can be obtained after photographing.
Description
technical field [0001] The invention belongs to the field of image processing, and in particular relates to an image recognition algorithm for prefabricated reinforced concrete rough surfaces. Background technique [0002] The connection quality of reinforced concrete prefabricated components and cast-in-place concrete is the key to the overall structural performance, and the roughness of the joint surface of reinforced concrete prefabricated components is a key technical point and an important evaluation index of reinforced concrete prefabricated components. In all kinds of joints of precast concrete components, the roughness of the joint surface has a significant impact on the mechanical properties of the joints. The Eurocode regards the roughness of the joint surface as an important parameter for calculating the shear resistance of the joint surface, and the current code in my country also puts forward corresponding design and construction requirements for the roughness o...
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IPC IPC(8): G06T7/00G06K9/62G01B11/30
CPCG06T7/0004G01B11/30G06T2207/10004G06T2207/20081G06T2207/30132G06F18/24147
Inventor 赵强姚竝
Owner 祐云信息技术南通有限公司