CN106355179A - License plate location method and system - Google Patents
License plate location method and system Download PDFInfo
- Publication number
- CN106355179A CN106355179A CN201610760935.9A CN201610760935A CN106355179A CN 106355179 A CN106355179 A CN 106355179A CN 201610760935 A CN201610760935 A CN 201610760935A CN 106355179 A CN106355179 A CN 106355179A
- Authority
- CN
- China
- Prior art keywords
- license plate
- image
- car plate
- average gray
- obtains
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/60—Type of objects
- G06V20/62—Text, e.g. of license plates, overlay texts or captions on TV images
- G06V20/63—Scene text, e.g. street names
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/60—Type of objects
- G06V20/62—Text, e.g. of license plates, overlay texts or captions on TV images
- G06V20/625—License plates
Abstract
The invention provides a license plate location method and system. The method comprises steps as follows: S1, a license plate range is determined according to a vehicle image obtained through snapshot, and a license plate area image is obtained; S2, the license plate area image is subjected to edge extraction with a Sobel algorithm, and a license plate frame image is obtained; S3, the average grey image of the license plate frame image is calculated in a convolution manner, and a two-dimensional point consisting of the average grey degree and the Sobel gradient of the license plate frame image is projected to a two-dimensional coordinate system; S4, the average grey value of the license plate frame image and the average grey value of the Sobel gradient are substituted into two grey parabolic equations obtained through fitting, and a license plate image is calculated. Edge extraction and optimization of the image are performed through the grey image, the Sobel algorithm and the least square method, grey parabolic equations are obtained through fitting, the license plate image is calculated, and the method and the system have the characteristics of low algorithm complexity, high speed and high adaptability, can well recognize a license plate and have wide application value.
Description
Technical field
The present invention relates to field of computer technology is and in particular to a kind of license plate locating method and system.
Background technology
Car license recognition (license plate recognition, lpr) technology is intelligent transportation system (intelligent
Transport system, its) important means that manages, its task is by collection, analysis, processes image and be automatically positioned
With identification vehicle license plate.Lpr system can be widely used for public security bayonet, parking lot management, road violation management, highway inspection, prison
Survey the important events such as black board vehicle.Some electronic police systems are to first pass through vehicle triggering ground induction coil at present, capture many
The image in track, is then analyzed to the independent each image captured on backstage, respectively the car plate in each track is positioned.Cause
This this system needs capturing pre-buried ground induction coil at mouth, and there is the regular hour from video capture to background process and prolong
Late, and need backstage set corresponding processing routine, complex operation, using inconvenience.How to be known using image procossing, pattern
Not etc. technology is not automatically positioned and identifies car plate, and then to improve the efficiency of vehicle identification be current problem demanding prompt solution.
Content of the invention
The technical problem to be solved is for the deficiencies in the prior art, provides a kind of license plate locating method and is
System.
The technical scheme is that a kind of license plate locating method, comprise the steps:
Step s1, determines car plate scope according to capturing the vehicle image obtaining, obtains license plate area image；
Step s2, license plate area image is carried out edge extracting according to sobel algorithm, obtains car plate framing image；
Step s3, calculates the average gray figure of car plate framing image in convolution mode, and described car plate framing image is flat
The two-dimensional points of all gray scale and sobel gradient composition project in two-dimensional coordinate system；
Step s4, the average gray value of the average gray value of car plate framing image and sobel gradient is substituted into two respectively
The gray scale parabolic equation that matching obtains, is calculated license plate image.
The invention has the beneficial effects as follows: the present invention carries out image by gray level image, sobel algorithm and method of least square
Edge extracting and optimization, the gray scale parabolic equation that matching obtains, be calculated license plate image, it is low to have an algorithm complex,
The speed of service is fast, adaptable feature, preferably can identify car plate, be with a wide range of applications.
On the basis of technique scheme, the present invention can also do following improvement.
Further, described step s4 implement including:
With average gray as independent variable, sobel gradient is dependent variable, carries out Second Order Linear Differential Equation plan with method of least square
Close, obtain two parabolas.
Beneficial effect using above-mentioned further scheme is: algorithm complex is low, and the speed of service is fast it is adaptable to quick identify
Car plate.
Further, described two parabolas be using in matlab workbox a=polyfit (xdata, ydata,
N) Function Fitting obtains.
Beneficial effect using above-mentioned further scheme is: is fitted computing using the existing function in matlab, fortune
Scanning frequency degree is fast, and algorithm is easy.
Further, described vehicle image comprises license plate area and background area.
Beneficial effect using above-mentioned further scheme is: localization method is strong to the recognition capability of input, Neng Goutong
Cross algorithm and identify car plate in complex background, adaptable.
Another kind of technical scheme that the present invention solves above-mentioned technical problem is as follows: a kind of Position System of automobile license plate location, comprising:
License plate area image zooming-out module, for determining car plate scope according to the vehicle image that candid photograph obtains, obtains car plate
Area image；
Car plate framing image extraction module, for license plate area image is carried out edge extracting according to sobel algorithm, obtains
Car plate framing image；
Projection module, for calculating the average gray figure of car plate framing image in convolution mode, by described car plate frame figure
The two-dimensional points of the average gray of picture and sobel gradient composition project in two-dimensional coordinate system；
Fitting module, for by the average gray value of the average gray value of car plate framing image and sobel gradient generation respectively
Enter two gray scale parabolic equations, be calculated license plate image.
The invention has the beneficial effects as follows: the present invention carries out image by gray level image, sobel algorithm and method of least square
Edge extracting and optimization, the gray scale parabolic equation that matching obtains, be calculated license plate image, it is low to have an algorithm complex,
The speed of service is fast, adaptable feature, preferably can identify car plate, be with a wide range of applications.
Further, described fitting module implement including:
With average gray as independent variable, sobel gradient is dependent variable, carries out Second Order Linear Differential Equation plan with method of least square
Close, obtain two parabolas.
Beneficial effect using above-mentioned further scheme is: algorithm complex is low, and the speed of service is fast it is adaptable to quick identify
Car plate.
Further, described two parabolas be using in matlab workbox a=polyfit (xdata, ydata,
N) Function Fitting obtains.
Beneficial effect using above-mentioned further scheme is: is fitted computing using the existing function in matlab, fortune
Scanning frequency degree is fast, and algorithm is easy.
Further, described vehicle image comprises license plate area and background area.
Beneficial effect using above-mentioned further scheme is: localization method is strong to the recognition capability of input, Neng Goutong
Cross algorithm and identify car plate in complex background, adaptable.
Brief description
Fig. 1 is a kind of license plate locating method flow chart of the present invention；
Fig. 2 is a kind of Position System of automobile license plate location schematic diagram of the present invention.
Specific embodiment
Below in conjunction with accompanying drawing, the principle of the present invention and feature are described, example is served only for explaining the present invention, and
Non- for limiting the scope of the present invention.
Fig. 1 is a kind of license plate locating method flow chart of the present invention；
As shown in figure 1, a kind of license plate locating method, comprise the steps:
Step s1, determines car plate scope according to capturing the vehicle image obtaining, obtains license plate area image；
Step s2, license plate area image is carried out edge extracting according to sobel algorithm, obtains car plate framing image；
Step s3, calculates the average gray figure of car plate framing image in convolution mode, and described car plate framing image is flat
The two-dimensional points of all gray scale and sobel gradient composition project in two-dimensional coordinate system；
Step s4, the average gray value of the average gray value of car plate framing image and sobel gradient is substituted into two respectively
The gray scale parabolic equation that matching obtains, is calculated license plate image.
In a particular embodiment of the present invention, described step s4 implement including:
With average gray as independent variable, sobel gradient is dependent variable, carries out Second Order Linear Differential Equation plan with method of least square
Close, obtain two parabolas.
In a particular embodiment of the present invention, described two parabolas are using the a=polyfit in matlab workbox
(xdata, ydata, n) Function Fitting obtain.
In a particular embodiment of the present invention, described vehicle image comprises license plate area and background area.
Fig. 2 is a kind of Position System of automobile license plate location schematic diagram of the present invention.
As shown in Fig. 2 a kind of Position System of automobile license plate location, comprising:
License plate area image zooming-out module, for determining car plate scope according to the vehicle image that candid photograph obtains, obtains car plate
Area image；
Car plate framing image extraction module, for license plate area image is carried out edge extracting according to sobel algorithm, obtains
Car plate framing image；
Projection module, for calculating the average gray figure of car plate framing image in convolution mode, by described car plate frame figure
The two-dimensional points of the average gray of picture and sobel gradient composition project in two-dimensional coordinate system；
Fitting module, for by the average gray value of the average gray value of car plate framing image and sobel gradient generation respectively
Enter two gray scale parabolic equations, be calculated license plate image.
In a particular embodiment of the present invention, described fitting module implement including:
With average gray as independent variable, sobel gradient is dependent variable, carries out Second Order Linear Differential Equation plan with method of least square
Close, obtain two parabolas.
In a particular embodiment of the present invention, described two parabolas are using the a=polyfit in matlab workbox
(xdata, ydata, n) Function Fitting obtain.
In a particular embodiment of the present invention, described vehicle image comprises license plate area and background area.
In the description of this specification, reference term " embodiment one ", " embodiment two ", " example ", " specific example " or
The description of " some examples " etc. means that the concrete grammar, device or the feature that describe with reference to this embodiment or example are contained in this
In at least one bright embodiment or example.In this manual, the schematic representation of above-mentioned term is necessarily directed to
Identical embodiment or example.And, the specific features of description, method, device or feature can be real at any one or more
Apply in example or example and combine in an appropriate manner.Additionally, in the case of not conflicting, those skilled in the art can be by
The feature of the different embodiments described in this specification or example and different embodiment or example is combined and combines.
The foregoing is only presently preferred embodiments of the present invention, not in order to limit the present invention, all spirit in the present invention and
Within principle, any modification, equivalent substitution and improvement made etc., should be included within the scope of the present invention.
Claims (8)
1. a kind of license plate locating method is it is characterised in that comprise the steps:
Step s1, determines car plate scope according to capturing the vehicle image obtaining, obtains license plate area image；
Step s2, license plate area image is carried out edge extracting according to sobe l algorithm, obtains car plate framing image；
Step s3, calculates the average gray figure of car plate framing image in convolution mode, by the average ash of described car plate framing image
The two-dimensional points of degree and sobel gradient composition project in two-dimensional coordinate system；
Step s4, the average gray value of the average gray value of car plate framing image and sobel gradient is substituted into two matchings respectively
The gray scale parabolic equation obtaining, is calculated license plate image.
2. a kind of license plate locating method according to claim 1 it is characterised in that described step s4 implement bag
Include:
With average gray as independent variable, sobel gradient is dependent variable, carries out Second Order Linear Differential Equation matching with method of least square, obtains
To two parabolas.
3. a kind of license plate locating method according to claim 2 is it is characterised in that described two parabolas are to utilize
A=polyfit in matlab workbox (xdata, ydata, n) Function Fitting obtain.
4. a kind of license plate locating method according to claim 1 is it is characterised in that described vehicle image comprises license plate area
And background area.
5. a kind of Position System of automobile license plate location is it is characterised in that include:
License plate area image zooming-out module, for determining car plate scope according to the vehicle image that candid photograph obtains, obtains license plate area
Image；
Car plate framing image extraction module, for license plate area image is carried out edge extracting according to sobel algorithm, obtains car plate
Framing image；
Projection module, for calculating the average gray figure of car plate framing image in convolution mode, by described car plate framing image
The two-dimensional points of average gray and sobel gradient composition project in two-dimensional coordinate system；
Fitting module, for substituting into two respectively by the average gray value of the average gray value of car plate framing image and sobel gradient
Individual gray scale parabolic equation, is calculated license plate image.
6. a kind of Position System of automobile license plate location according to claim 5 it is characterised in that described fitting module implement bag
Include:
With average gray as independent variable, sobel gradient is dependent variable, carries out Second Order Linear Differential Equation matching with method of least square, obtains
To two parabolas.
7. a kind of Position System of automobile license plate location according to claim 6 is it is characterised in that described two parabolas are to utilize
A=polyfit in matlab workbox (xdata, ydata, n) Function Fitting obtain.
8. a kind of Position System of automobile license plate location according to claim 5 is it is characterised in that described vehicle image comprises license plate area
And background area.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610760935.9A CN106355179A (en) | 2016-08-30 | 2016-08-30 | License plate location method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610760935.9A CN106355179A (en) | 2016-08-30 | 2016-08-30 | License plate location method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106355179A true CN106355179A (en) | 2017-01-25 |
Family
ID=57857731
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610760935.9A Pending CN106355179A (en) | 2016-08-30 | 2016-08-30 | License plate location method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106355179A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111079744A (en) * | 2019-12-06 | 2020-04-28 | 鲁东大学 | Intelligent vehicle license plate identification method and device suitable for complex illumination environment |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102306282A (en) * | 2011-07-19 | 2012-01-04 | 北京博康智能信息技术有限公司 | License plate positioning method and license plate positioning device |
| CN102902957A (en) * | 2012-09-05 | 2013-01-30 | 佳都新太科技股份有限公司 | Video-stream-based automatic license plate recognition method |
| CN103093229A (en) * | 2013-01-21 | 2013-05-08 | 信帧电子技术（北京）有限公司 | Positioning method and device of vehicle logo |
| CN103324930A (en) * | 2013-06-28 | 2013-09-25 | 浙江大学苏州工业技术研究院 | License plate character segmentation method based on grey level histogram binaryzation |
-
2016
- 2016-08-30 CN CN201610760935.9A patent/CN106355179A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102306282A (en) * | 2011-07-19 | 2012-01-04 | 北京博康智能信息技术有限公司 | License plate positioning method and license plate positioning device |
| CN102902957A (en) * | 2012-09-05 | 2013-01-30 | 佳都新太科技股份有限公司 | Video-stream-based automatic license plate recognition method |
| CN103093229A (en) * | 2013-01-21 | 2013-05-08 | 信帧电子技术（北京）有限公司 | Positioning method and device of vehicle logo |
| CN103324930A (en) * | 2013-06-28 | 2013-09-25 | 浙江大学苏州工业技术研究院 | License plate character segmentation method based on grey level histogram binaryzation |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111079744A (en) * | 2019-12-06 | 2020-04-28 | 鲁东大学 | Intelligent vehicle license plate identification method and device suitable for complex illumination environment |
| CN111079744B (en) * | 2019-12-06 | 2020-09-01 | 鲁东大学 | Intelligent vehicle license plate identification method and device suitable for complex illumination environment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103279756B (en) | Vehicle detection based on integrated classifier analyzes system and determination method thereof | |
| CN106971185B (en) | License plate positioning method and device based on full convolution network | |
| Saha et al. | License Plate localization from vehicle images: An edge based multi-stage approach | |
| CN102354457B (en) | General Hough transformation-based method for detecting position of traffic signal lamp | |
| CN108269407B (en) | Security robot capable of automatically managing people stream and logistics | |
| Saini et al. | Multiwavelet transform based license plate detection | |
| CN103824066A (en) | Video stream-based license plate recognition method | |
| CN108198417B (en) | A kind of road cruising inspection system based on unmanned plane | |
| CN103646544B (en) | Based on the vehicle behavioural analysis recognition methods of The Cloud Terrace and camera apparatus | |
| CN103164697B (en) | The licence plate recognition method of a kind for the treatment of time and accuracy of identification self-adaptation | |
| CN106803262A (en) | The method that car speed is independently resolved using binocular vision | |
| CN103324958A (en) | License plate locating method based on projection method and SVM under complex background | |
| Wen et al. | A rear-vehicle detection system for static images based on monocular vision | |
| KR100942409B1 (en) | Method for detecting a moving vehicle at a high speed | |
| CN106355179A (en) | License plate location method and system | |
| US8971579B2 (en) | Windshield localization for occupancy detection | |
| Xu et al. | A novel method for people and vehicle classification based on Hough line feature | |
| CN105005780A (en) | License plate identification method | |
| KR20140000402A (en) | Vehicle detector and method using stereo camera | |
| Alhussein et al. | Vehicle license plate detection and perspective rectification | |
| Hermawati et al. | A real-time license plate detection system for parking access | |
| CN112101107B (en) | Intelligent recognition method for intelligent network connection model vehicle on-loop simulation traffic signal lamp | |
| CN109886120B (en) | Zebra crossing detection method and system | |
| CN106920398A (en) | A kind of intelligent vehicle license plate recognition system | |
| CN106971186B (en) | A kind of intelligent traffic monitoring system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20170125 |