PCA-based end-to-end pavement crack detection-recognition method

A technology for pavement cracks and identification methods, applied in the field of computer vision, can solve the problems of inability to determine the type of cracks, low efficiency, error failure, etc., to save labor and practice costs, reduce workload, and improve robustness.

Active Publication Date: 2018-10-26
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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  • PCA-based end-to-end pavement crack detection-recognition method
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  • PCA-based end-to-end pavement crack detection-recognition method

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Embodiment Construction

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

[0048] A PCA-based end-to-end pavement crack detection and recognition method, comprising the following steps:

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

[0050] Specific steps are as follows:

[0051] S101: Obtaining about road surface image I x data set;

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

[0053] 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...

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Abstract

The invention discloses a PCA-based end-to-end pavement crack detection-recognition method and relates to the field of computer vision. The method comprises the steps that S1, a dataset about a pavement image I<x> is acquired, and the dataset is preprocessed; S2, the preprocessed dataset is subjected to category marking, a background image I not containing a crack is calculated, a difference image I between the pavement image I<x> and the background image I is acquired, and a training set and a test set are constructed according to proportion; S3, training set images I are utilized to train a deep neural network model; S4, test set images I are input into the trained deep neural network model to acquire image category probabilities; and S5, a category tag corresponding to the maximumprobability is selected to serve as an image detection-recognition result. Through the scheme, traditional detection and recognition processes are fused, and therefore the efficiency and robustness of pavement crack detection are improved.

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 recognition method. Background technique [0002] Whether it is asphalt or cement pavement, after a period of time of traffic opening, 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 harm. Pavement crack detection refers to the process of first detecting whether there are cracks or defective parts in the road surface in the image, and then identifying the crack type. It involves two processes of detection and recognition. This is a key issue in computer vision. It is based on image The basic technology of content recognition. Pavement crack detection can be used in road restoration, road condition monitoring a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06K9/62
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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