An End-to-End Pavement Crack Detection and Recognition Method Based on PCA

A technology for pavement cracks and identification methods, applied in the field of computer vision, can solve the problems of error failure, inability to determine the type of cracks, low efficiency, etc., to achieve good robustness, reduce the workload of artificial marking, and simplify the effect of preprocessing.

Active Publication Date: 2022-03-25
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

However, due to the differences in road conditions and inconsistencies in various scenarios, this detection method is inefficient and has large errors or even fails, and it is impossible to determine the type of cracks.

Method used

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  • An End-to-End Pavement Crack Detection and Recognition Method Based on PCA
  • An End-to-End Pavement Crack Detection and Recognition Method Based on PCA
  • An End-to-End Pavement Crack Detection and Recognition Method Based on PCA

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Embodiment Construction

[0047] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention.

[0048] An end-to-end pavement crack detection and identification method based on PCA, comprising the following steps:

[0049] S1: Get image I about road surface x data set, and preprocess the data set;

[0050] Specific steps are as follows:

[0051] S101: Acquire information about the road surface image I x data set;

[0052] S102: Convert the dataset road image I x Crop to a sub-image of size M×M and convert to grayscale.

[0053] S2: Classify the preprocessed data set, and calculate the background image I without cracks b , and obtain the road image I x with background image I ...

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Abstract

The invention discloses a PCA-based end-to-end pavement crack detection and recognition method, which relates to the field of computer vision and includes the following steps: S1: Acquiring information about the road surface image I x The data set, and preprocess the data set; S2: classify the preprocessed data set, and calculate the background image I without cracks b , and get the road surface image I x with the background image I b difference image I, and build a training set and a test set in proportion; S3: use the training set image I to train the deep neural network model; S4: input the test set image I to the trained deep neural network model to obtain the image category probability, S5: Select the category label corresponding to the maximum probability as the result of image detection and recognition. This solution integrates the traditional detection and recognition process, which improves the efficiency and robustness of pavement crack detection.

Description

technical field [0001] The invention relates to the field of computer vision, in particular to a PCA-based end-to-end pavement crack detection and identification method. Background technique [0002] Whether it is asphalt or cement pavement, after a period of opening to traffic, cracks appear on the pavement due to the external environment, which brings great hidden dangers to the normal use of the pavement. Therefore, an effective detection and evaluation method is needed to detect and identify possible hidden dangers, so as to avoid potential hazards. Pavement crack detection refers to the process of first detecting whether there are cracks or defective parts in the pavement in the image, and then identifying the type of cracks. It involves two processes of detection and identification. This is a key problem in computer vision and is based on images. The basic technology of content recognition. Pavement crack detection can be used in road restoration, road condition moni...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00G06V10/77G06V10/764G06V10/774G06V10/82G06K9/62
CPCG06T7/0004G06T2207/20084G06T2207/20081G06T2207/30132G06F18/2135G06F18/214G06F18/24
Inventor 董乐叶俊贤张宁毛梦蝶黄灿陈相蕾
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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