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License plate location method based on color clustering

A license plate positioning and color clustering technology, applied in the field of image processing, can solve the problems of low recognition rate and inability to meet the requirements of license plate positioning accuracy

Inactive Publication Date: 2016-01-06
ZHEJIANG GONGSHANG UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in the background of bad weather, affected by interference factors such as weather changes, dust stains, and environmental backgrounds, the recognition rate of existing recognition algorithms is still low, and cannot meet the requirements for the accuracy of license plate location under complex environmental conditions.

Method used

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  • License plate location method based on color clustering
  • License plate location method based on color clustering
  • License plate location method based on color clustering

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0044] The license plate location method based on color clustering includes the following specific steps:

[0045] 1) Convert the color source image containing the license plate image into an eight-bit grayscale image, the conversion formula is Gray=(R*38+G*75+B*15)>>7, where >> is the shift operator , respectively calculating the vertical edge response Response of each pixel on the grayscale image;

[0046] 2) Evenly divide the area where the license plate image is located into a grid set {R (r,c) ,r=1,2,...,[height / 10],c=1,2,...,[width / 10]}, where height and width are the height and width of the license plate image; currently The resolution of common traffic checkpoint monitoring images is between 1024×768 and 1360×1096 pixels, the height of the license plate is about 30 pixels to 60 pixels, and the division method of 10×10 pixels can divide the license plate area into about 50 to 100 square.

[0047] 3) Calculate R( r,c) The sum of the vertical edge responses of all int...

experiment example 1

[0100] The experimenters collected about 10,000 images containing license plates at road intersections under different conditions, including daytime, night, sunny, rainy, foggy, slightly defaced license plate, tilted license plate placement, etc. Application Example 1 The method is used to detect and recognize these images, and the detection results are shown in the following table:

[0101]

[0102] Among them, ○ indicates that the condition is satisfied, and × indicates that the condition is not established.

[0103] It can be seen from the above table that, applying the method of the present invention, the positioning accuracy rate can reach 92.6% under severe conditions such as strong car lights at night, rain and fog, and 98.2% under comprehensive conditions. From the above experimental data, it can be seen that , Compared with the prior art, the technical solution of the present invention can greatly overcome technical problems such as blurred images caused by bad wea...

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Abstract

The invention relates to the field of image processing, and particularly discloses a license plate positioning method based on color clustering. The license plate positioning method based on the color clustering comprises the following steps of: (1) transforming a color source image which contains a license plate image into a grayscale image; (2) uniformly dividing an area at which the license plate image is positioned into grids; (3) respectively calculating the response sum of the vertical edges of all pixel points inside the grids, and selecting the grids with the response sum of the vertical edges exceeding a threshold value as grids to be selected; (4) transforming the color source image into an HSV (Hue, Saturation, Value) color space, and respectively calculating the color mode lists of the candidate concentrated grids; (5) clustering the candidate concentrated grids to obtain a license plate candidate area list; (6) selecting an area as a license plate area; and (7) carrying out edge detection on the license plate area by applying a Canny algorithm, and acquiring the accurate position of the edges by applying Hough transformation. According to Tthe license plate positioning method based on color clustering, which is disclosed by the invention, the image recognition capacity is high and the license plate area positioned on the image can be fast and accurately positioned under the situation of complex road illumination condition.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a method for locating license plates based on color clustering. Background technique [0002] Intelligent traffic management is the most advanced research topic in the field of traffic management in the world. In recent years, its achievements have gradually penetrated into various fields of social life, playing an active role in improving work efficiency, facilitating life and maintaining safety. Intelligent traffic management generally uses machine vision and artificial intelligence technology to perform target acquisition, object recognition and behavior understanding on images and videos in the traffic field. Among them, the recognition of vehicle license plates is a key link in the practical application of machine vision. Its technology is relatively mature and has been widely used in specific applications such as traffic flow monitoring, violation monitoring, parking lot ch...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/32G06K9/54
Inventor 彭浩宇王勋
Owner ZHEJIANG GONGSHANG UNIVERSITY
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