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Underground parking garage parking space detection method based on image processing

An underground garage and image processing technology, applied in the field of intelligent traffic management, can solve the problems of high cost, complicated installation, heavy maintenance workload, etc., and achieve the effect of low cost and simple maintenance

Active Publication Date: 2019-09-13
ZHEJIANG UNIV OF TECH
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In addition to computer vision, other methods are complicated to install, require a lot of maintenance, and are expensive

Method used

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  • Underground parking garage parking space detection method based on image processing
  • Underground parking garage parking space detection method based on image processing
  • Underground parking garage parking space detection method based on image processing

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Embodiment Construction

[0042] The specific implementation of the image processing-based underground garage parking space detection method of the present invention will be described in detail below in conjunction with the embodiments.

[0043]A method for detecting parking spaces in underground garages based on image processing, specifically including the following steps:

[0044] Step 1: Detect the corner area of ​​the parking space through the YOLOv3 deep learning model, and record the detected set of m corner rectangular areas as A={R t |t=1,2,…,m}, where, R t Represents the t-th corner rectangular area; if the corner rectangular area is unevenly illuminated, perform illumination compensation on it, and correct the image through histogram equalization;

[0045] Step 2: Apply the adaptive mean method to each region R t The sub-image of is binarized;

[0046] Step 3: For each region R t Corner detection is performed on sub-images, as follows:

[0047] Step 3.1: smoothing the image to be process...

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Abstract

The invention discloses an underground parking garage parking space detection method based on image processing. The method comprises the following steps that: S1: through a YOLOv3 deep learning model,detecting parking space angular point regions, and marking m pieces of detected angular point rectangular region sets as A={Rt|t=1,2,...,m}, wherein Rt shows the tth angular point rectangular region;S2: adopting an adaptive mean value method to carry out binaryzation on the subimage of each region Rt; S3: carrying out angular point detection on the subimage of each region Rt; and S4: according to S3, obtaining the angular point coordinates of all angular point regions in A, and sorting the angular point coordinates according to an abscissa. The detection method has the advantages that the interference of vehicles, rays and obstacles can be effectively eliminated, image processing is used for accurately detecting stop lines and parking space angular points so as to finish parking space detection, and the method is simple in maintenance and low in cost.

Description

technical field [0001] The invention relates to the technical field of intelligent traffic management, in particular to an image processing-based detection method for underground garage parking spaces. Background technique [0002] With the rapid development of my country's transportation industry, the number of cars in cities has increased year by year, and the problems of urban road traffic jams and parking difficulties have become more and more prominent. The construction of underground garages can greatly alleviate the problem of difficult parking, and reliable irregular parking detection is the guarantee in the field of intelligent traffic management. [0003] At present, the parking process of traditional parking lots does not pay attention to the status of parking spaces, and the utilization rate of parking spaces is not high. Especially in large and medium-sized parking lots, vehicles come in and out frequently, the status of parking spaces is difficult to count, and...

Claims

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Application Information

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IPC IPC(8): G08G1/14G06K9/32G06K9/46G06T7/73
CPCG08G1/14G06T7/73G06T2207/10036G06T2207/20061G06T2207/20164G06T2207/30232G06V10/25G06V10/44G06V2201/08
Inventor 汪鹏飞许镇远项健翔岑黎彬王雯卿高飞
Owner ZHEJIANG UNIV OF TECH
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