CN111652222A - License plate positioning method and device, computer equipment and storage medium - Google Patents
License plate positioning method and device, computer equipment and storage medium Download PDFInfo
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- CN111652222A CN111652222A CN202010677544.7A CN202010677544A CN111652222A CN 111652222 A CN111652222 A CN 111652222A CN 202010677544 A CN202010677544 A CN 202010677544A CN 111652222 A CN111652222 A CN 111652222A
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- 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
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- 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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/74—Image or video pattern matching; Proximity measures in feature spaces
- G06V10/75—Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video features; Coarse-fine approaches, e.g. multi-scale approaches; using context analysis; Selection of dictionaries
- G06V10/751—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
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- 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 discloses a license plate positioning method and device, computer equipment and a storage medium, wherein the method comprises the following steps: positioning the license plate of the acquired image by using a template matching method to obtain a matching result, calculating the best matching score, calculating the comparison score of the template images, and judging whether the comparison score of the template images of the image is larger than a preset value or not; when the comparison score of the template images of the existing images is larger than a preset value, checking the images by using a COMPARE _ SSIM algorithm, and if the checking result is larger than the set value, finishing license plate positioning; and when the comparison score of the template images without the images is larger than a preset value, processing the images by using a rectangle detection algorithm, verifying the images by using a COMPARE _ SSIM algorithm, and if the verification result is larger than the set value, finishing license plate positioning. And determining to position the license plate by using a COMPARE _ SSIM algorithm or a processing mode of combining rectangle detection and the COMPARE _ SSIM algorithm according to the comparison score of the calculated template graph, so that the license plate region in the license plate image can be positioned at a higher speed and accuracy.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to a license plate positioning method and device, computer equipment and a storage medium.
Background
The intelligent traffic is the main direction of current traffic management development, is the leading research subject of the current world traffic transportation field, the license plate recognition technology is the core of the intelligent traffic system, is the application of the computer image processing technology and the mode recognition technology in the intelligent traffic field, and is widely applied to the specific problems of vehicle charging and management, traffic flow detection, parking lot charging management, illegal vehicle monitoring, fake license plate vehicle recognition and the like. With the improvement of computer performance and the development of image processing technology, the license plate recognition technology has become mature.
The license plate recognition process is basically divided into three steps: license plate positioning, character cutting and character recognition. The license plate positioning technology is a crucial step in the license plate recognition technology, and as a first step in the whole license plate recognition process, whether the license plate is successfully positioned or not directly affects subsequent steps, so that the speed and the recognition rate of license plate recognition are determined. Many positioning methods have been studied in order to accurately and quickly locate the card-out area. The more common license plate positioning method comprises the following steps: 1. the method comprises the following steps of (1) license plate positioning based on character jumping characteristics, 2 license plate positioning based on combination of colors and edge characteristics, and 3 license plate positioning based on deep learning.
Although the existing license plate positioning method can achieve some achievements aiming at the positions of a vehicle head, a vehicle tail and the like under the ideal conditions of illumination and weather, because the application of a license plate recognition system is more and more extensive, the scenes of the acquired license plate images are more and more complex, the change degree of the weather conditions causes the acquisition of license plate images with different qualities, and when the color information of the license plate is not obvious and the edge information is interfered, the performance of the existing method is not ideal.
In practical situations, when the quality of the acquired license plate image is not good, the license plate positioning method in the prior art may have the following disadvantages: 1) the expansion-operated license plate image has the advantages that the regions except the license plate region are adhered, and other regions are also adhered, so that a plurality of license plate candidate regions are formed, and the complexity of subsequent processing is increased; 2) the license plate part in the license plate image subjected to expansion operation is often adhered to other parts of the vehicle, so that the area originally containing the license plate is mistakenly regarded as a license plate candidate area; 3) when the position of the vehicle in the license plate image is far or near, the size of the license plate position in the license plate image is different, so that the parameters of the license plate image during expansion calculation are not easy to control, for example, the parameters are only suitable for the remote license plate, and then the near license plate is broken. Once the processed picture has the defects, great difficulty is brought to subsequent license plate recognition, and the phenomena of slow license plate positioning and inaccurate license plate positioning are caused.
The information disclosed in this background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.
Based on the above reasons, the invention provides a license plate positioning method and device, computer equipment and a storage medium.
Disclosure of Invention
In order to meet the above requirements, a first object of the present invention is to provide a license plate positioning method.
The second purpose of the invention is to provide a license plate positioning device.
A third object of the present invention is to provide a license plate location computer device.
It is a fourth object of the invention to provide a non-transitory computer readable storage medium having a computer program stored thereon.
In order to achieve the purpose, the invention adopts the following technical scheme:
in a first aspect, a license plate positioning method is provided, which includes the following steps:
positioning the license plate of the acquired image by using a template matching method to obtain a matching result, calculating the best matching score, calculating the comparison score of the template images, and judging whether the comparison score of the template images of the image is larger than a preset value or not;
when the comparison score of the template images of the existing images is larger than a preset value, checking the images by using a COMPARE _ SSIM algorithm, and if the checking result is larger than the set value, finishing license plate positioning;
and when the comparison score of the template images without the images is larger than a preset value, processing the images by using a rectangle detection algorithm, verifying the images by using a COMPARE _ SSIM algorithm, and if the verification result is larger than the set value, finishing license plate positioning.
In a possible embodiment, the step of locating the license plate of the acquired image by using a template matching method and obtaining the matching result further comprises collecting and generalizing a plurality of template maps in advance.
In a possible implementation manner, the step of locating the license plate of the acquired image by using a template matching method and obtaining a matching result matches the image by using a normalized correlation coefficient.
In one possible embodiment, the processing the image using the rectangle detection algorithm includes:
carrying out binarization on the image;
searching all contours in the binarized image, placing the contours in a list, carrying out impurity processing on the contours, and calculating the contours in the list to form a minimum region boundary rectangle;
a new image is extracted from the minimum region boundary rectangle for inspection.
In one possible embodiment, the step of calculating the minimum region boundary rectangle formed by the outlines in the list comprises:
obtaining a region boundary rectangle in which the length-width ratio in the image is 1.8-3.6, the product of the length and the width is 2000px-10000px, the included angle formed by the bottom of the rectangle and the x axis is not more than 30 degrees, and the positions of the center points of the rectangle are all within 0.8 times of the peripheral size of the image.
In a possible embodiment, said step of extracting a new image from said minimum region bounding rectangle for examination further comprises clipping the image by an image clipping function for non-angled rectangles.
In a possible embodiment, the step of extracting a new image from the minimum region boundary rectangle for inspection further comprises rotating the angle of the angle rectangle to be horizontal, obtaining the coordinates of the rectangle through matrix calculation, and intercepting the image according to the coordinates of the rectangle.
In another aspect, the present invention provides a license plate positioning device, including the following units:
the template matching unit is used for positioning the license plate of the acquired image by using a template matching method, obtaining a matching result, calculating the best matching score, calculating the comparison score of the template image, and judging whether the comparison score of the template image of the image is larger than a preset value or not;
the COMPARE _ SSIM checking unit is used for checking the image by using a COMPARE _ SSIM algorithm when the comparison score of the template image of the image is greater than a preset value, and finishing license plate positioning if the checking result is greater than the set value;
and the rectangle detection unit is used for processing the image by using a rectangle detection algorithm when the comparison score of the template image without the image is larger than a preset value, verifying the image by using a COMPARE _ SSIM algorithm, and finishing license plate positioning if the verification result is larger than the set value.
In a third aspect, the present invention provides a license plate positioning computer device, including a memory, a processor, and a license plate positioning program stored on the memory and executable on the processor, where the license plate positioning program, when executed by the processor, implements the license plate positioning method as described in any one of the above.
In a fourth aspect, the present invention proposes a non-transitory computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements a license plate location method as recited in any of the above.
Compared with the prior art, the invention has the beneficial effects that: according to the license plate positioning method, after the images are sampled, the images are matched by using a template matching method based on a normalized correlation coefficient matching principle, then the license plate is positioned by using a COMPARE _ SSIM algorithm or a processing mode of combining rectangle detection and the COMPARE _ SSIM algorithm according to the calculated comparison score of the template images, and the license plate region in the license plate images can be positioned at a higher speed and a higher accuracy.
The invention is further described below with reference to the accompanying drawings and specific embodiments.
Drawings
FIG. 1 is a schematic flow chart of a license plate location method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a frame of an embodiment of a license plate location device according to the present invention;
FIG. 3 is a block diagram of a license plate location computer apparatus according to an embodiment of the present invention;
FIG. 4 is a block diagram of a particular embodiment of a non-transitory computer readable storage medium of the present invention;
FIG. 5 is a schematic diagram of a state in a vehicle image operation flow of a license plate location method according to the present invention;
FIG. 6 is a schematic diagram of a state in which a vehicle image includes a plurality of rectangular regions according to a license plate location method of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present 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.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
As shown in the flowchart of fig. 1, a license plate positioning method according to a first embodiment of the present invention includes the following steps:
step S1, the license plate of the acquired image is positioned by a template matching method to obtain a matching result, the best matching score is calculated, the template comparison score is calculated, and whether the template comparison score of the image is larger than a preset value or not is judged;
step S2, when the template graph comparison score of the existing image is larger than a preset value, the image is verified by using a COMPARE _ SSIM algorithm, and if the verification result is larger than the set value, license plate positioning is completed;
and step S3, when the comparison score of the template map without the image is larger than a preset value, processing the image by using a rectangular detection algorithm, then verifying the image by using a COMPARE _ SSIM algorithm, and if the verification result is larger than the set value, finishing the license plate positioning.
The steps S2 and S3 are parallel steps, and when the determination condition of one of the steps is not successful, another step is executed, after the execution is finished, another step is automatically skipped to finish the positioning process, and the next round of process is started.
Wherein, as the basis for the implementation of the steps:
template matching method: typically used in object detection, similarity analysis, comparing a template to an overlapping image area. The overlap area of size w × h is compared with the template by image sliding using a specified method, and the comparison result is stored in the return. After the functions are compared, the corresponding functions are used for finding out the best matching item;
rectangle detection: and carrying out topological structure analysis on the digital binary image through boundary tracking, and retrieving the contour from the binary image. Contours are used for shape analysis and object detection and recognition;
COMPARE _ SSIM: the structural similarity measurement is a full-reference image quality evaluation index, and measures the image similarity from three aspects of brightness, contrast and structure. The SSIM value range [0,1] indicates that the image distortion is smaller when the value is larger. In the application of the scheme, the image can be blocked by using a sliding window, the total number of blocks is N, the influence of the window shape on the blocks is considered, the mean value, the variance and the covariance of each window are calculated by adopting Gaussian weighting, then the structural similarity SSIM of the corresponding block is calculated, and finally the mean value is used as the structural similarity measurement of the two images, namely the average structural similarity SSIM.
As a preferred embodiment, the step of locating the license plate of the acquired image by using the template matching method and obtaining the matching result further includes collecting and summarizing a plurality of template drawings in advance.
As an optional embodiment, step S1 is preceded by an image binarization process for facilitating subsequent operations.
As a preferred embodiment, the step of locating the license plate of the acquired image by using a template matching method and obtaining a matching result matches the image by using a normalized correlation coefficient matching formula.
Wherein the matching formula is:
wherein T 'is a detection target, namely a matching template, and I' is an image for target detection.
As a preferred embodiment, the processing the image by using the rectangle detection algorithm includes:
carrying out binarization on the image;
searching all contours in the binarized image, placing the contours in a list, carrying out impurity processing on the contours, and calculating the contours in the list to form a minimum region boundary rectangle;
a new image is extracted from the minimum region boundary rectangle for inspection.
The results obtained in the above steps are shown in fig. 5, i.e., the original picture, the binarized picture, and the extracted contour.
Specifically, the impurity processing is to compress horizontal, vertical and diagonal line segments of the image, and the end points thereof are retained, so as to obtain an image with a large effective area ratio.
The binarization processing is a process of setting the gray value of a pixel point on an image to be 0 or 255, namely, the whole image presents an obvious black and white effect. In the scheme, the binarization of the image greatly reduces the data volume in the image, so that the outline of the target can be highlighted.
In one possible embodiment, the step of calculating the minimum region boundary rectangle formed by the outlines in the list comprises:
obtaining a region boundary rectangle in which the length-width ratio in the image is 1.8-3.6, the product of the length and the width is 2000px-10000px, the included angle formed by the bottom of the rectangle and the x axis is not more than 30 degrees, and the positions of the center points of the rectangle are all within 0.8 times of the peripheral size of the image.
In a possible embodiment, said step of extracting a new image from said minimum region bounding rectangle for examination further comprises clipping the image by an image clipping function for non-angled rectangles.
In a possible embodiment, the step of extracting a new image from the minimum region boundary rectangle for inspection further comprises rotating the angle of the angle rectangle to be horizontal, obtaining the coordinates of the rectangle through matrix calculation, and intercepting the image according to the coordinates of the rectangle.
Specifically, the required rectangle is only the rectangle including the license plate, and in order to avoid excessive calculation and to eliminate some, the calculation steps are installed, and the size of the acquired rectangle is as follows:
aspect ratio: the length/width is 1.8-3.6 times;
size: length and width of 2000px-10000 px;
angle: the included angle formed by the rectangular bottom and the x axis is not more than 30 degrees;
position: the positions of the central points of the rectangles are all within 0.8 times of the size of the periphery of the picture;
when the rectangle is obtained, at this time, a rectangular region is extracted to form a new image for validation, as shown in fig. 6 (the region pointed by the arrow), the rectangle without angle is intercepted by an image intercepting function, while the rectangle with angle needs to be rotated by a corresponding angle to be horizontal, the coordinate of the rectangle after rotation is also changed, the coordinate of the rectangle is obtained again through matrix calculation, and then the rectangle is intercepted according to the coordinate.
Finally, through the verification of the COMPARE _ SSIM algorithm, due to the diversity of the images, a plurality of template images are verified, and when one similarity value is larger than a set value, the license plate positioning is completed.
As a second embodiment of the present invention, as shown in fig. 2, the present invention further provides a license plate positioning device, including the following units;
the template matching unit 100 is used for positioning the license plate of the acquired image by using a template matching method, obtaining a matching result, calculating the best matching score, calculating the comparison score of the template image, and judging whether the comparison score of the template image of the image is larger than a preset value or not;
the COMPARE _ SSIM checking unit 200 is used for checking the image by using a COMPARE _ SSIM algorithm when the comparison score of the template image of the image is greater than a preset value, and finishing license plate positioning if the checking result is greater than the set value;
and the rectangle detection unit 300 is configured to, when the template map comparison score of an image is greater than a preset value, process the image by using a rectangle detection algorithm, verify the image by using a COMPARE _ SSIM algorithm, and complete license plate positioning if a verification result is greater than a set value.
The template matching unit 100, the COMPARE _ SSIM checking unit 200, and the rectangle detecting unit 300 correspond to the above steps S1, S2, and S3, respectively, and the present apparatus is intended to implement steps S1 to S3 by using three units.
The template matching unit 100, the COMPARE _ SSIM checking unit 200, and the rectangle detecting unit 300 may include, but are not limited to, embodiments of an operation interface, a prompt interface, and operation software.
As a third embodiment of the present invention, as shown in fig. 3, the present invention provides a license plate location computer device, including a memory 400, a processor 500, and a license plate location program stored on the memory 400 and executable on the processor 500, where the license plate location program, when executed by the processor 500, implements the license plate location method as described in any one of the above.
The Memory 400 may be a Read-Only Memory (ROM) or other types of static storage devices that can store static information and instructions, a Random Access Memory (RAM) or other types of dynamic storage devices that can store information and instructions, an Electrically Erasable Programmable Read-Only Memory (EEPROM), a compact disc Read-Only Memory (CD-ROM) or other optical disc storage, optical disc storage (including compact disc, laser disc, optical disc, digital versatile disks, blu-ray disks, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to such. The memory may be self-contained and coupled to the processor via a communication bus. The memory may also be integral to the processor.
As a fourth embodiment of the present invention, as shown in fig. 4, the present invention provides a non-transitory computer readable storage medium, on which a computer program 600 is stored, and when the computer program is executed by a processor, the method for locating a license plate according to any one of the above-mentioned embodiments is implemented.
The storage medium may be an internal storage unit of the aforementioned server, such as a hard disk or a memory of the server. The storage medium may also be an external storage device of the device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like provided on the device. Further, the storage medium may also include both an internal storage unit and an external storage device of the apparatus.
It should be noted that, as will be clear to those skilled in the art, specific implementation processes of the above apparatus, the computer device and the units may refer to corresponding descriptions in the foregoing method embodiments, and for convenience and brevity of description, no further description is provided herein.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be embodied in electronic hardware, computer software, or combinations of both, and that the components and steps of the examples have been described in a functional general in the foregoing description for the purpose of illustrating clearly the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention. It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative. For example, the division of each unit is only one logic function division, and there may be another division manner in actual implementation. For example, more than one unit or component may be combined or may be integrated into another system, or some features may be omitted, or not implemented.
The steps in the method of the embodiment of the invention can be sequentially adjusted, combined and deleted according to actual needs. The units in the device of the embodiment of the invention can be merged, divided and deleted according to actual needs.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention essentially or partially contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a terminal, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention.
While the invention has been described with reference to specific embodiments, the invention is not limited thereto, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A license plate positioning method is characterized by comprising the following steps:
positioning the license plate of the acquired image by using a template matching method to obtain a matching result, calculating the best matching score, calculating the comparison score of the template images, and judging whether the comparison score of the template images of the image is larger than a preset value or not;
when the comparison score of the template images of the existing images is larger than a preset value, checking the images by using a COMPARE _ SSIM algorithm, and if the checking result is larger than the set value, finishing license plate positioning;
and when the comparison score of the template images without the images is larger than a preset value, processing the images by using a rectangle detection algorithm, verifying the images by using a COMPARE _ SSIM algorithm, and if the verification result is larger than the set value, finishing license plate positioning.
2. The license plate location method of claim 1, wherein the step of locating the license plate of the acquired image by using the template matching method and obtaining the matching result further comprises pre-collecting and summarizing a plurality of template images.
3. The license plate location method of claim 1, wherein the step of locating the license plate of the acquired image by using a template matching method and obtaining the matching result matches the image by using a normalized correlation coefficient.
4. The license plate location method of claim 1, wherein the processing the image using the rectangle detection algorithm comprises:
carrying out binarization on the image;
searching all contours in the binarized image, placing the contours in a list, carrying out impurity processing on the contours, and calculating the contours in the list to form a minimum region boundary rectangle;
a new image is extracted from the minimum region boundary rectangle for inspection.
5. The license plate location method of claim 4, wherein the step of computing the minimum region bounding rectangle formed by the outlines in the list comprises:
obtaining a region boundary rectangle in which the length-width ratio in the image is 1.8-3.6, the product of the length and the width is 2000px-10000px, the included angle formed by the bottom of the rectangle and the x axis is not more than 30 degrees, and the positions of the center points of the rectangle are all within 0.8 times of the peripheral size of the image.
6. The method of claim 4, wherein the step of extracting a new image from the minimum region boundary rectangle for inspection further comprises clipping the image with an image clipping function for non-angle rectangles.
7. The license plate location method of claim 4, wherein the step of extracting a new image from the minimum region boundary rectangle for inspection further comprises rotating the angle of the angle rectangle to horizontal, retrieving the coordinates of the rectangle by matrix calculation, and intercepting the image according to the coordinates of the rectangle.
8. A license plate positioner, its characterized in that includes the following unit:
the template matching unit is used for positioning the license plate of the acquired image by using a template matching method, obtaining a matching result, calculating the best matching score, calculating the comparison score of the template image, and judging whether the comparison score of the template image of the image is larger than a preset value or not;
the COMPARE _ SSIM checking unit is used for checking the image by using a COMPARE _ SSIM algorithm when the comparison score of the template image of the image is greater than a preset value, and finishing license plate positioning if the checking result is greater than the set value;
and the rectangle detection unit is used for processing the image by using a rectangle detection algorithm when the comparison score of the template image without the image is larger than a preset value, verifying the image by using a COMPARE _ SSIM algorithm, and finishing license plate positioning if the verification result is larger than the set value.
9. A license plate location computer device comprising a memory, a processor, and a license plate location program stored on the memory and executable on the processor, the license plate location program when executed by the processor implementing the license plate location method of any one of claims 1-7.
10. A non-transitory computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the license plate location method of any of claims 1-7.
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