CN112488100A - License plate recognition rate improving method and device based on multi-algorithm fusion - Google Patents
License plate recognition rate improving method and device based on multi-algorithm fusion Download PDFInfo
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- CN112488100A CN112488100A CN202011352444.3A CN202011352444A CN112488100A CN 112488100 A CN112488100 A CN 112488100A CN 202011352444 A CN202011352444 A CN 202011352444A CN 112488100 A CN112488100 A CN 112488100A
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- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V30/00—Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
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- G06V30/14—Image acquisition
- G06V30/146—Aligning or centring of the image pick-up or image-field
- G06V30/1475—Inclination or skew detection or correction of characters or of image to be recognised
- G06V30/1478—Inclination or skew detection or correction of characters or of image to be recognised of characters or characters lines
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/26—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion
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- G06V20/00—Scenes; Scene-specific elements
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Abstract
The invention discloses a license plate recognition rate improving method and device based on multi-algorithm fusion, and belongs to the technical field of calculation, calculation or counting related to license plate recognition.
Description
Technical Field
The invention relates to an intelligent traffic technology, in particular to a license plate recognition rate improving method and device based on multi-algorithm fusion, and belongs to the technical field of calculation, calculation or counting related to image recognition.
Background
The license plate number of the automobile is the only 'identity' mark of the automobile, the automatic license plate recognition technology can realize the automatic registration and verification of the 'identity' of the automobile without changing the automobile, and the technology is applied to various occasions such as road charging, parking management, weighing systems, traffic guidance, traffic law enforcement, road inspection, vehicle scheduling, vehicle detection and the like. The license plate recognition technology requires that the license plate of the moving automobile can be extracted and recognized from a complex background, and the information such as the license plate number and the color of the automobile can be recognized through the technologies such as license plate extraction, image preprocessing, feature extraction, license plate character recognition and the like.
A license plate recognition method in the prior art is as follows: firstly, preprocessing a vehicle image to obtain a license plate image to be recognized and a license plate type of the license plate image to be recognized, determining the positions of upper and lower layer dividing lines on the license plate image to be recognized of the double-line license plate type based on the size specification of the double-line license plate under the condition that the license plate type of the license plate image to be recognized indicates a multi-line license plate, dividing the license plate image to be recognized of the double-line license plate type along the determined dividing lines to obtain an upper license plate image and a lower license plate image, and performing size transformation on the upper license plate image to obtain an upper license plate image after size transformation; and splicing the upper layer license plate image and the lower layer license plate image after size conversion in the horizontal direction to obtain a converted single-line license plate type license plate image, and identifying the single-line license plate type license plate image to obtain a license plate number. The method simply and efficiently realizes the recognition of the multi-line license plate by converting the multi-line license plate into the single-line license plate.
However, the above method has the following disadvantages in the process of actually recognizing the license plate: for some special license plates, there are often more than two layers of text on the license plate, for example: have four layers of characters on the tablet of entrying temporarily, from top to bottom in proper order note have: the time limit information, the temporary entry information, the license plate number information and the route information, and the division in the double-row license plate mode can cause the reduction of the recognition rate. For another example: the agricultural machinery license plate is issued by an agricultural machinery supervision department, the color of the license plate is a white frame with a green bottom and a white character, and the size of the license plate is 300mm x 165 mm. The license plate of the low-speed truck consists of two license plates with the same size, the license plates are respectively hung on the front and the tail of the truck, the size is also 300mm x 165mm, the two license plates are double-layer characters, but the positions of the segmentation lines are slightly different due to different license plate types, and the identification rate is reduced due to the fact that the positions of the segmentation lines of the upper layer and the lower layer are determined on the license plate image to be identified of the double-row license plate type only based on the size specification of the double-row license plate.
Therefore, it is necessary to provide a license plate recognition rate improving method and device based on multi-algorithm fusion to improve the license plate recognition rate.
Disclosure of Invention
The invention aims to provide a license plate recognition rate improving method and device based on multi-algorithm fusion, which realizes the remarkable improvement of the multi-line character license plate recognition rate through the fusion of multiple algorithms such as binarization processing, inclination correction, layout analysis and the like and solves the problem of low recognition rate when the existing double-line license plate recognition mode is adopted to recognize a double-layer character license plate.
The invention adopts the following technical scheme for realizing the aim of the invention:
in a first aspect, the invention provides a license plate recognition rate improving method based on multi-algorithm fusion, which comprises the following steps:
acquiring a vehicle image;
extracting a license plate image in the vehicle image;
carrying out binarization processing on the license plate image to obtain a binarization image, wherein the binarization image comprises license plate foreground character information and license plate background information;
performing inclination correction on the license plate foreground character information;
performing layout analysis on the license plate foreground character information after inclination correction, and converting the character information in different lines into the same line;
and performing character recognition on the character information converted to the same line to obtain a license plate character recognition result.
Optionally, the method further comprises:
determining the type of the license plate according to the size of the license plate;
and performing layout recovery processing on the license plate character recognition result according to the type of the license plate, and adjusting the layout arrangement mode of the license plate character recognition result to be a license plate character layout arrangement mode matched with the type of the license plate.
Optionally, the method further comprises:
and sending the license plate character recognition result after the layout recovery processing to a manual inspection terminal for manual examination.
In a second aspect, the present invention further provides a license plate recognition rate improving device based on multi-algorithm fusion, including:
an acquisition unit configured to acquire a vehicle image;
the extraction unit is used for extracting a license plate image in the vehicle image;
the processing unit is used for carrying out binarization processing on the license plate image to obtain a binarization image, wherein the binarization image comprises license plate foreground character information and license plate background information;
the correction unit is used for carrying out inclination correction on the license plate foreground character information;
the analysis unit is used for performing layout analysis on the license plate foreground character information after inclination correction and converting the character information in different lines into the same line;
and the recognition unit is used for carrying out character recognition on the character information converted to the same line to obtain a license plate character recognition result.
Optionally, the apparatus further comprises:
the determining unit is used for determining the type of the license plate according to the size of the license plate;
and the recovery unit is used for performing layout recovery processing on the license plate character recognition result according to the type of the license plate and adjusting the layout arrangement mode of the license plate character recognition result to be a license plate character layout arrangement mode matched with the type of the license plate.
Optionally, the apparatus further comprises:
and the sending unit is used for sending the license plate character recognition result after the layout recovery processing to a manual inspection terminal for manual examination.
The invention has the following beneficial effects: the invention provides a license plate recognition rate improving method and device based on multi-algorithm fusion.
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In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious to those skilled in the art that other drawings can be obtained according to the drawings without any inventive exercise.
Fig. 1 is a flowchart of a license plate recognition rate improving method based on multi-algorithm fusion according to an embodiment of the present invention.
Fig. 2 is a flowchart of a license plate recognition rate improving method based on multi-algorithm fusion according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of a license plate recognition rate improving device based on multi-algorithm fusion according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the specific embodiments of the present invention and the accompanying drawings. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention. The technical solutions provided by the embodiments of the present invention are described in detail below with reference to the accompanying drawings.
Referring to fig. 1, fig. 1 is a flowchart illustrating a license plate recognition rate improving method based on multi-algorithm fusion according to an embodiment of the present invention, where an execution main body of the method may be a processor, and the method specifically includes steps S101 to S106.
Step S101, a vehicle image is acquired.
Specifically, images of the head and the tail of the passing vehicle can be collected through the high-definition camera, and the images of the head and the tail of the passing vehicle are sent to the processor.
And S102, extracting a license plate image in the vehicle image.
And step S103, performing binarization processing on the license plate image to obtain a binarization image, wherein the binarization image comprises license plate foreground character information and license plate background information.
In digital image processing, a binary image plays a very important role, and binarization of an image greatly reduces the amount of data in the image, thereby making it possible to highlight the contour of a target. The invention uses the binarization processing of the image, sets the gray value of the point on the license plate image as 0 or 255, and displays the obvious black and white effect of the whole license plate image, namely, the gray image with 256 brightness levels is selected by a proper threshold value to obtain the binarization image which can still reflect the whole and local characteristics of the image, thereby being beneficial to that when the license plate image is further processed, the collective property of the image is only related to the position of the point with the pixel value of 0 or 255, and the multilevel value of the pixel is not related any more, so that the processing becomes simple, and the processing and compression quantity of the data are small. In order to obtain an ideal binary image, a non-overlapping region is generally defined by closed and connected boundaries. All pixels with the gray levels larger than or equal to the threshold are judged to belong to the specific object, the gray level of the pixels is 255 for representation, otherwise the pixels are excluded from the object area, the gray level is 0, and the pixels represent the background or the exceptional object area.
If a particular object has a uniform gray level inside it and is in a uniform background with gray levels of other levels, a comparable segmentation effect can be obtained using thresholding. If the difference between the object and the background is not represented in gray scale values (e.g., different textures), the difference feature can be converted into a gray scale difference, and then the image can be segmented using a threshold selection technique. The threshold value is dynamically adjusted to realize the binarization of the image, and the specific result of the image segmentation can be dynamically observed.
And step S104, performing inclination correction on the license plate foreground character information.
Specifically, firstly, the hough transform may be used to perform the tilt angle detection, and then the image rotation may be used to perform the tilt correction.
And step S105, performing layout analysis on the license plate foreground character information after inclination correction, and converting the character information in different lines into the same line.
Specifically, because characters on a license plate of one type may be arranged in multiple lines, the number of lines of the characters is identified by performing layout analysis on the license plate foreground character information after inclination correction, and then the character information in different lines is converted to the same line from left to right according to a top-down mode.
And step S106, performing character recognition on the character information converted to the same line to obtain a license plate character recognition result.
Specifically, character recognition of the character information converted to the same line can be realized according to the prior art, and recognition efficiency and recognition accuracy are greatly improved.
As shown in fig. 2, in an alternative embodiment, the license plate recognition method disclosed in the present application may further include step S201 and step S202.
Step S201, determining the type of the license plate according to the size of the license plate.
Specifically, license plates of different vehicle types have specific sizes, for example, the size of a front license plate of a two-wheel or three-wheel motorcycle is as follows: 220mm 95mm, the license plate background information is a black frame line with yellow background and black characters, and the license plate types are determined to be two-wheeled motorcycles and three-wheeled motorcycles. The size of the rear license plate of the light motorcycle is as follows: and 220mm by 140mm, wherein the license plate background information is a white frame line with a blue background and a white character, and the license plate type is determined to be the moped. The size of the front license plate of the large automobile is as follows: 440mm 140mm, the license plate background information is yellow background black character black frame line, the foreground character information is: the total mass is 4.5t (including), the number of passengers is 20 (including) and the vehicle length, and the type of the license plate is determined to be a large-sized vehicle. The size of the license plate of the small automobile is as follows: and 440mm by 140mm, wherein the license plate background information is a white frame line with blue background and white characters, and the type of the license plate is determined to be a small automobile. The size of the license plate of the coach automobile is 440 mm-140 mm, the background information of the license plate is a black frame line with yellow background and black characters, and the type of the license plate is determined to be the type of the license plate as the coach automobile.
And S202, performing layout recovery processing on the license plate character recognition result according to the license plate type, and adjusting the layout arrangement mode of the license plate character recognition result to be a license plate character layout arrangement mode matched with the license plate type.
Further, in an optional implementation manner, the license plate recognition method disclosed in the present application further includes the following steps: and sending the license plate character recognition result after the layout recovery processing to a manual inspection terminal for manual examination.
Referring to fig. 3, the present invention provides a license plate recognition rate improving apparatus based on multi-algorithm fusion, including:
an acquisition unit configured to acquire a vehicle image;
the extraction unit is used for extracting a license plate image in the vehicle image;
the processing unit is used for carrying out binarization processing on the license plate image to obtain a binarization image, wherein the binarization image comprises license plate foreground character information and license plate background information;
the correction unit is used for carrying out inclination correction on the license plate foreground character information;
the analysis unit is used for performing layout analysis on the license plate foreground character information after inclination correction and converting the character information in different lines into the same line;
and the recognition unit is used for carrying out character recognition on the character information converted to the same line to obtain a license plate character recognition result.
Further, the apparatus may further include:
the determining unit is used for determining the type of the license plate according to the size of the license plate;
and the recovery unit is used for performing layout recovery processing on the license plate character recognition result according to the license plate type and adjusting the layout arrangement mode of the license plate character recognition result into a license plate character layout arrangement mode matched with the license plate type.
Further, the apparatus may further include:
and the sending unit is used for sending the license plate character recognition result after the layout recovery processing to a manual inspection terminal for manual examination.
The embodiment of the invention also provides a storage medium, wherein a computer program is stored in the storage medium, and when being executed by a processor, the computer program realizes part or all of the steps in the license plate recognition rate improving method based on multi-algorithm fusion. The storage medium may be a magnetic disk, an optical disk, a Read Only Memory (ROM), a Random Access Memory (RAM), or the like.
Those skilled in the art will readily appreciate that the techniques of the embodiments of the present invention may be implemented as software plus a required general purpose hardware platform. Based on such understanding, the technical solutions in the embodiments of the present invention may be essentially or partially implemented in the form of software products, which may be stored in a storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and include instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the embodiments or some parts of the embodiments.
The same or similar parts between the various embodiments in this specification may be referred to each other. Particularly, for the embodiment of the license plate recognition rate improving device based on multi-algorithm fusion, since the embodiment is basically similar to the method embodiment, the description is simple, and the relevant points can be referred to the description in the method embodiment.
The above-described embodiments of the present invention should not be construed as limiting the scope of the present invention.
Claims (10)
1. A license plate recognition rate improving method based on multi-algorithm fusion is characterized in that,
acquiring a vehicle image and extracting a license plate image in the vehicle image;
carrying out binarization processing on the license plate image to obtain a binarization image containing license plate foreground character information;
performing inclination correction on the license plate foreground character information;
performing layout analysis on the license plate foreground character information after inclination correction, and converting the character information in different lines into the same line;
and performing character recognition on the character information converted to the same line to obtain a license plate character recognition result.
2. The method for improving the license plate recognition rate based on multi-algorithm fusion of claim 1, wherein after the license plate character recognition result is obtained, the layout recovery processing is performed on the license plate character recognition result according to the license plate type, and the layout arrangement mode of the license plate character recognition result is adjusted to be the license plate character layout arrangement mode matched with the license plate type.
3. The method for improving the recognition rate of the license plate based on the multi-algorithm fusion as claimed in claim 1, wherein a license plate image is segmented by dynamically adjusting a threshold value to obtain a binary image.
4. The method for improving the recognition rate of the license plate based on the multi-algorithm fusion as claimed in claim 1, wherein the method for performing the tilt correction on the foreground character information of the license plate comprises the following steps: and detecting the inclination angle of the license plate foreground character information by adopting Hough transform, and rotating the license plate foreground character information according to the detected inclination angle.
5. The method for improving the recognition rate of the license plate based on the multi-algorithm fusion as claimed in claim 2, wherein the license plate character recognition result after the layout recovery is sent to a manual inspection terminal for manual review.
6. The utility model provides a license plate recognition rate hoisting device based on multi-algorithm fuses which characterized in that includes:
an acquisition unit that acquires a vehicle image;
the extraction unit is used for extracting the license plate image in the vehicle image;
the processing unit is used for carrying out binarization processing on the license plate image to obtain a binarization image containing license plate foreground character information;
the correction unit is used for carrying out inclination correction on the license plate foreground character information;
the analysis unit is used for performing layout analysis on the license plate foreground character information after inclination correction and converting the character information in different lines into the same line; and a process for the preparation of a coating,
and the recognition unit is used for carrying out character recognition on the character information converted to the same line to obtain a license plate character recognition result.
7. The device according to claim 6, further comprising:
the determining unit is used for determining the type of the license plate according to the size of the license plate; and a process for the preparation of a coating,
and the recovery unit is used for performing layout recovery processing on the license plate character recognition result according to the license plate type and adjusting the layout arrangement mode of the license plate character recognition result into a license plate character layout arrangement mode matched with the license plate type.
8. The device according to claim 6, further comprising:
and the sending unit is used for sending the license plate character recognition result after the layout is recovered to a manual inspection terminal for manual examination.
9. A computer storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the license plate recognition rate enhancing method of claim 1.
10. A license plate recognition terminal device, characterized by comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the license plate recognition rate enhancing method of claim 1 when executing the program.
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| CN105335743A (en) * | 2015-10-28 | 2016-02-17 | 重庆邮电大学 | Vehicle license plate recognition method |
| CN109145915A (en) * | 2018-07-27 | 2019-01-04 | 武汉科技大学 | License plate rapid distortion antidote under a kind of complex scene |
| US20190114516A1 (en) * | 2017-10-13 | 2019-04-18 | Getac Technology Corporation | Method for recognizing license plate in vehicle camera device and vehicle camera device |
| CN110163199A (en) * | 2018-09-30 | 2019-08-23 | 腾讯科技（深圳）有限公司 | Licence plate recognition method, license plate recognition device, car license recognition equipment and medium |
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2020
- 2020-11-26 CN CN202011352444.3A patent/CN112488100A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105335743A (en) * | 2015-10-28 | 2016-02-17 | 重庆邮电大学 | Vehicle license plate recognition method |
| US20190114516A1 (en) * | 2017-10-13 | 2019-04-18 | Getac Technology Corporation | Method for recognizing license plate in vehicle camera device and vehicle camera device |
| CN109145915A (en) * | 2018-07-27 | 2019-01-04 | 武汉科技大学 | License plate rapid distortion antidote under a kind of complex scene |
| CN110163199A (en) * | 2018-09-30 | 2019-08-23 | 腾讯科技（深圳）有限公司 | Licence plate recognition method, license plate recognition device, car license recognition equipment and medium |
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