CN109765397B - Speed measurement method, device and system - Google Patents
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- CN109765397B CN109765397B CN201910087770.7A CN201910087770A CN109765397B CN 109765397 B CN109765397 B CN 109765397B CN 201910087770 A CN201910087770 A CN 201910087770A CN 109765397 B CN109765397 B CN 109765397B
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Abstract
The invention relates to the technical field of speed measurement, and provides a speed measurement method, a speed measurement device and a speed measurement system, wherein the speed measurement method comprises the following steps: the method comprises the steps of obtaining a first image and a second image which comprise an object to be detected and identification lines according to a preset time interval, detecting target angular points which exist in the first image and the second image, obtaining angular point displacement of the object to be detected within the preset interval according to coordinates of the target angular points, and further calculating the speed of the object to be detected. Compared with the prior art, the speed measuring method, the speed measuring device and the speed measuring system provided by the invention can detect the speed of a train when the train runs at a lower speed in the loading process, and avoid the problem that the running speed of the train cannot be detected by radar speed measurement or can be reflected for a longer time.
Description
Technical Field
The invention relates to the technical field of speed measurement, in particular to a speed measurement method, a speed measurement device and a speed measurement system.
Background
The existing train speed measurement mainly uses a speed measurement radar, and the basic principle of radar speed measurement is that a device which continuously emits electric waves is utilized to emit the electric waves towards an object, when the radio waves are in the process of traveling, the radio waves are reflected when touching the object, and the wavelength of the electric waves which are reflected back can be changed along with the moving state of the touched object. After calculation, the relative moving speed between the object and the radar can be obtained.
However, in the process of loading the train, the running speed is slow, and is 0.2-0.3 m/s on average, so that the field angle of radar speed measurement is too small, the running speed of the train cannot be detected, or the running speed of the train can be reflected for a long time. When the train is automatically loaded, if the current speed cannot be obtained in more than 0.1 second, serious accidents such as material scattering, unbalanced loading and the like can be caused.
Disclosure of Invention
The invention aims to provide a speed measuring method, a speed measuring device and a speed measuring system, which aim to solve the problem that in the prior art, the running speed of a train is slower, so that the running speed of the train cannot be detected by radar speed measurement or can be reflected for a longer time in the loading process of the train.
In order to achieve the above purpose, the embodiment of the present invention adopts the following technical solutions:
in a first aspect, an embodiment of the present invention provides a speed measurement method, which is applied to a camera device of a speed measurement system, and is used for detecting a speed of an object to be detected, the speed measurement system further includes a laser emitting device, the laser emitting device is used for emitting laser to project onto the object to be detected to form a marking line, and the marking line and a reinforcing structure of the object to be detected form an angular point; the method comprises the following steps: acquiring a first image and a second image containing the object to be detected according to a preset time interval, wherein the first image and the second image both contain identification lines; detecting all target corner points in the first image and the second image, wherein the first image and the second image both comprise the target corner points; and obtaining the angular point displacement of the object to be detected within the preset time interval according to the coordinates of each target angular point, and further calculating the speed of the object to be detected.
In a second aspect, an embodiment of the present invention provides a speed measurement device, which is applied to a camera device of a speed measurement system, and is used for detecting a speed of an object to be detected, the speed measurement system further includes a laser emission device, the laser emission device is used for emitting laser to project onto the object to be detected to form a mark line, and the mark line and a reinforcing structure of the object to be detected form an angular point; the device comprises: the device comprises an acquisition module, a detection module and a processing module, wherein the acquisition module is used for acquiring a first image and a second image which comprise the object to be detected according to a preset time interval, and the first image and the second image both comprise identification lines; a processing module, configured to detect all target corner points in the first image and the second image, where the first image and the second image both include the target corner point; and obtaining the angular point displacement of the object to be detected within the preset time interval according to the coordinates of each target angular point, and further calculating the speed of the object to be detected.
In a third aspect, an embodiment of the present invention provides a speed measurement system, where the speed measurement system includes a camera device and a laser emitter, the camera device is configured to detect a speed of an object to be detected, the laser emitter is configured to emit laser light to project onto the object to be detected to form a mark line, and the mark line and a reinforcing structure of the object to be detected form an angular point; the image pickup apparatus includes: one or more processors; a memory for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the method of speed measurement described above.
Compared with the prior art, the embodiment of the invention has the following beneficial effects:
according to the speed measuring method, the speed measuring device and the speed measuring system provided by the embodiment of the invention, the first image and the second image which comprise the object to be detected and the identification line are obtained according to the preset time interval, the target angular point existing in the first image and the target angular point existing in the second image are detected, the angular point displacement of the object to be detected in the preset interval is obtained according to the coordinate of the target angular point, and the speed of the object to be detected is further calculated. The speed of the train can be detected when the train runs at a slow speed in the loading process, and the problem that the running speed of the train cannot be detected by radar speed measurement or can be reflected for a long time is solved.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention, and therefore should not be considered as limiting the scope, and for a user of ordinary skill in the art, other related drawings can be obtained according to these drawings without creative efforts.
Fig. 1 shows a schematic view of an application scenario of a speed measurement system provided in an embodiment of the present invention.
Fig. 2 illustrates an example of a first image provided by an embodiment of the present invention.
Fig. 3 is a schematic diagram illustrating a partial structure of an image pickup apparatus according to an embodiment of the present invention.
Fig. 4 shows a flowchart of a speed measurement method according to an embodiment of the present invention.
Fig. 5 shows a flowchart of another speed measurement method provided in the embodiment of the present invention.
Fig. 6 shows a block schematic diagram of a speed measuring device provided in an embodiment of the present invention.
Icon: 10-a speed measuring system; 100-a camera device; 101-a processor; 102-a memory; 103-a bus; 104-a communication interface; 105-a camera; 200-a laser emitting device; 300-a speed measuring device; 301-an obtaining module; 302-processing module.
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 only a part of the embodiments of the present invention, and not all of the embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be obtained by a user skilled in the art without inventive work based on the embodiments of the present invention, are within the scope of protection of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present invention, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
The existing train speed measurement mainly uses a speed measurement radar, and the basic principle of radar speed measurement is that a device which continuously emits electric waves is utilized to emit the electric waves towards an object, when the radio waves are in the process of traveling, the radio waves are reflected when touching the object, and the wavelength of the electric waves which are reflected back can be changed along with the moving state of the touched object. After calculation, the relative moving speed between the object and the radar can be obtained.
However, in the process of loading the train, the running speed is low, the average speed is 0.2-0.3 m/s, so that the field angle of radar speed measurement is too small, and when the train enters a radar detection area at the joint of the carriage, the running speed of the train cannot be measured for 2-5 seconds, or the running speed of the train can be reflected for a long time. When the train is automatically loaded, if the current speed cannot be obtained in more than 0.1 second, serious accidents such as material scattering, unbalanced loading and the like can be caused.
The method comprises the steps of establishing a relation between pixels and three-dimensional space coordinates according to a space mapping relation between structured light and images shot by a camera, utilizing the characteristic that a freight train carriage can have an outward protruding reinforcing structure every 1-2 meters, achieving the purpose of measuring the train speed by identifying and tracking characteristic corner point pixels of the structured light on the surface of the freight train carriage, and filling the blank of an ultra-low speed accurate speed measurement scheme of 0-4 km/h of a freight train, wherein the speed measurement precision is +/-0.01 m/s.
The invention aims to solve the technical problem that a speed measuring method is provided, and the core improvement point is that a first image and a second image which comprise an object to be measured and a marking line are obtained according to a preset time interval, target angular points existing in the first image and the second image are detected, angular point displacement of the object to be measured in the preset interval is obtained according to coordinates of the target angular points, and then the speed of the object to be measured is calculated, so that the speed of a train at a lower running speed in the loading process can be detected, and the problem that the running speed of the train cannot be detected by radar speed measurement or can be reflected by longer time is avoided.
The speed measuring method provided by the embodiment of the invention is applied to the camera device 100 of the speed measuring system 10 and used for detecting the speed of an object to be detected, namely the speed of a train. Referring to fig. 1 and fig. 2, the speed measuring system 10 further includes a laser emitting device 200, the laser emitting device 200 is configured to emit laser to project onto the object to be detected to form a marking line, and the marking line and the reinforcing structure of the object to be detected form an angular point. The relative positions of the image pickup device 100 and the laser emitting device 200 are fixed.
The image capturing apparatus 100 may be, but is not limited to, a smart camera, please refer to fig. 3, fig. 3 shows a schematic diagram of a partial structure of the image capturing apparatus according to an embodiment of the present invention, and the image capturing apparatus 100 includes a processor 101, a memory 102, a bus 103, a communication interface 104, and a camera 105. The processor 101, the memory 102, the communication interface 104, and the camera 105 are connected via the bus 103, and the processor 101 is configured to execute an executable module, such as a computer program, stored in the memory 102.
The processor 101 may be an integrated circuit chip having signal processing capabilities. In the implementation process, the steps of the velocity measurement method may be implemented by an integrated logic circuit of hardware in the processor 101 or instructions in the form of software. The Processor 101 may be a general-purpose Processor 101, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the device can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components.
The Memory 102 may comprise a high-speed Random Access Memory (RAM) and may also include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. The Memory 102 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like.
The bus 103 may be an ISA (Industry Standard architecture) bus, a PCI (peripheral Component interconnect) bus, an EISA (extended Industry Standard architecture) bus, or the like. Only one bi-directional arrow is shown in fig. 3, but this does not indicate only one bus 103 or one type of bus 103.
The image pickup apparatus 100 realizes a communication connection between the image pickup apparatus 100 and an external device through at least one communication interface 104 (which may be wired or wireless). The memory 102 is used for storing programs, such as the speed measuring device 300. The speed measuring device 300 includes at least one software function module which can be stored in the memory 102 in the form of software or firmware (firmware) or solidified in an Operating System (OS) of the image capturing device 100. After receiving the execution instruction, the processor 101 executes the program to implement the speed measurement method.
The camera 105 is used for shooting an image containing the identification line and an object to be detected, and sending the image to the processor 101 for processing through the bus 103 or sending the image to the memory 102 for storage.
It should be understood that the configuration shown in fig. 3 is only a partial schematic configuration of the image capture apparatus 100, and the image capture apparatus 100 may also include more or fewer components than shown in fig. 3, or have a different configuration than shown in fig. 3. The components shown in fig. 3 may be implemented in hardware, software, or a combination thereof.
Based on the above-mentioned image capturing apparatus 100, a possible implementation manner of the speed measuring method is given below, an execution main body of the method may be the above-mentioned image capturing apparatus 100, please refer to fig. 4, and fig. 4 shows a flowchart of the speed measuring method provided in an embodiment of the present invention. The speed measuring method comprises the following steps:
s1, acquiring a first image and a second image containing the object to be detected at a preset time interval.
Wherein the first image and the second image both contain identification lines.
In the embodiment of the present invention, the first image may be an image including an object to be detected and a marking line, the second image may be an image including an object to be detected and a marking line, and a common corner point exists in the first image and the second image. The preset time interval may be a user-defined time interval, for example, 0.1 s. The step of acquiring a first image and a second image including an object to be detected according to a preset time interval may be understood as that the camera 105 photographs the object to be detected and the identification line to obtain the first image, and photographs the object to be detected and the identification line again after the preset time interval to obtain the second image.
And S2, detecting all target corner points in the first image and the second image.
Wherein, the first image and the second image both comprise target corner points.
In an embodiment of the present invention, the target corner point may be a corner point existing in both the first image and the second image. The step of detecting all target corner points in the first image and the second image may be understood as performing corner point detection on the first image to obtain a first corner point set, performing corner point detection on the second image to obtain a second corner point set, and finally determining all target corner points from the first corner point set and the second corner point set.
Referring to fig. 4, step S2 may include the following sub-steps:
and S21, carrying out corner detection on the first image to obtain a first corner set.
In an embodiment of the present invention, the first set of corners may be a set including first corners in at least one first image, the first corners being corners in the first image. The step of performing corner detection on the first image to obtain a first corner set can be understood as that, first, threshold binarization is performed on the first image to obtain a first binary image containing identification lines, then, hough transform is adopted to extract the identification lines in the first binary image to obtain a first identification image, and finally, corner detection is performed on the first identification image to obtain the first corner set.
And S22, performing corner point detection on the second image to obtain a second corner point set.
In an embodiment of the invention, the set of second corner points may be a set comprising second corner points in at least one second image, the second corner points being corner points in the second image. The step of performing corner detection on the second image to obtain a second corner set may be understood as performing threshold binarization on the second image to obtain a second binary image containing identification lines, then extracting the identification lines in the second binary image by hough transform to obtain a second identification image, and finally performing corner detection on the second identification image to obtain the second corner set.
In other embodiments of the present invention, the execution sequence of the sub-step S21 and the sub-step S22 may be exchanged, or the sub-step S21 and the sub-step S22 may be executed simultaneously, which is not limited herein.
S23, all the target corner points are determined from the first and second sets of corner points.
In an embodiment of the present invention, the target corner point may be a corner point included in both the first image and the second image. Determining all target corner points from the first corner point set and the second corner point set, wherein the first corner point set comprises at least one first corner point, the second corner point set comprises at least one second corner point, and firstly, acquiring first corner point coordinates of each first corner point in a first image and acquiring second corner point coordinates of each second corner point in a second image; secondly, obtaining a prediction corner coordinate corresponding to the first corner coordinate according to the first corner coordinate, a preset time interval and a preset corner motion model, and calculating deviation information corresponding to the second corner according to the second corner coordinate and the prediction corner coordinate; and finally, comparing the deviation information with a deviation threshold value, and taking a second corner point corresponding to the deviation information as a target corner point when the deviation information is smaller than the deviation threshold value.
Specifically, the sub-step S23 may include the following sub-steps:
s231, acquiring first corner coordinates of each first corner in the first image.
S232, second corner coordinates of each second corner in the second image are obtained.
In other embodiments of the present invention, the execution sequence of the sub-step S231 and the sub-step S231 may be exchanged, or the sub-step S231 and the sub-step S231 may be executed simultaneously, which is not limited herein.
And S233, obtaining a predicted corner coordinate corresponding to the first corner coordinate according to the first corner coordinate, the preset time interval and the preset corner motion prediction model.
In the embodiment of the present invention, the corner point motion model may be, but is not limited to, a kalman corner point motion model, and is used for predicting the motion speed and direction of the corner point. The predicted corner coordinates may be coordinates of a predicted corner in the second image, which are predicted according to the first corner coordinates, a preset time interval, and a preset corner motion prediction model.
Specifically, at least one image of the motion of the object to be detected and the first image are acquired before the first image, so that the motion speed and direction of a corner point between the image and the first image are obtained, and a predicted corner point coordinate corresponding to the corner point after a preset interval time of the first image is predicted according to the motion speed and direction. In one embodiment, the predicted corner coordinates are the first corner coordinates + a predetermined time interval corner motion model.
And S234, calculating deviation information corresponding to the second corner point according to the second corner point coordinate and the predicted corner point coordinate.
In the embodiment of the present invention, the deviation information may be a difference between the predicted corner coordinate and the second corner coordinate, and the deviation information is | the predicted corner coordinate — the second corner coordinate |. For example, the second corner coordinate is (50, 26), the prediction corner coordinate is (49, 26), and the deviation information | (49, 26) - (50, 26) | 1.
And S235, comparing the deviation information with a deviation threshold value, and taking a second corner point corresponding to the deviation information as a target corner point when the deviation information is smaller than the deviation threshold value.
In the embodiment of the present invention, the deviation threshold may be a minimum threshold that is customized by a user to determine that the second corner point is the target corner point. And comparing the deviation information obtained in the step S245 with a deviation threshold, and when the deviation information is smaller than the deviation threshold, taking a second corner point corresponding to the deviation information as a target corner point.
And S3, obtaining the angular point displacement of the object to be detected within a preset time interval according to the coordinates of each target angular point, and further calculating the speed of the object to be detected.
In the embodiment of the present invention, the angular point displacement may be a displacement of a target angular point moving under a world coordinate system between a first image and a second image, and the angular point displacement of the object to be detected within a preset time interval is obtained according to coordinates of each target angular point, and then the velocity of the object to be detected is calculated, and it is understood that, first, coordinates of the first image of each target angular point in the first image and coordinates of the second image of each target angular point in the second image are obtained, then, first position coordinates of the target angular point in the world coordinate system are obtained according to the first image coordinates and a preset conversion model, second position coordinates of the target angular point in the world coordinate system are obtained according to the second image coordinates and the preset conversion model, and finally, the angular point displacement is obtained according to the first position coordinates and the second position coordinates of each target angular point, and calculating the speed of the object to be detected according to the angular point displacement and the preset time interval.
Specifically, step S3 may include the following sub-steps:
s31, respectively acquiring first image coordinates of each target corner point in the first image and second image coordinates in the second image.
In the embodiment of the present invention, the first image coordinates may be coordinates of the target corner points in the first image, and the second image coordinates may be coordinates of the target corner points in the second image, and the step of respectively obtaining first image coordinates of each target corner point in the first image and second image coordinates of each target corner point in the second image may be understood as obtaining first image coordinates of each target corner point in the first image and obtaining second image coordinates of each target corner point in the second image.
And S32, obtaining a first position coordinate of the target corner point in the world coordinate system according to the first image coordinate and the preset conversion model.
In the embodiment of the present invention, the preset conversion model may be a conversion relation between an image coordinate system and a world coordinate system, and the first position coordinate may be an actual position coordinate of the target corner point in the world coordinate system when the first image is captured. The step of obtaining the first position coordinate of the target corner point in the world coordinate system according to the first image coordinate and the preset conversion model may be understood as obtaining the first position coordinate of the target corner point in the world coordinate system according to the first image coordinate in the image coordinate system and a conversion relation from the preset image coordinate system to the world coordinate system.
And S33, obtaining a second position coordinate of the target corner point in the world coordinate system according to the second image coordinate and the preset conversion model.
In the embodiment of the present invention, the preset conversion model may be a conversion relation between an image coordinate system and a world coordinate system, and the second position coordinate may be an actual position coordinate of the target corner point in the world coordinate system when the second image is captured. And a step of obtaining a second position coordinate of the target corner point in the world coordinate system according to the second image coordinate and the preset conversion model, wherein the second position coordinate of the target corner point in the world coordinate system is obtained according to the second image coordinate in the image coordinate system and a conversion relation from the preset image coordinate system to the world coordinate system.
In other embodiments of the present invention, the execution sequence of the sub-step S32 and the sub-step S33 may be exchanged, or the sub-step S32 and the sub-step S33 may be executed simultaneously, which is not limited herein.
And S34, obtaining corner point displacement according to the first position coordinates and the second position coordinates of each target corner point, and calculating the speed of the object to be detected according to the corner point displacement and a preset time interval.
In the embodiment of the present invention, the angular point displacement may be a displacement of a target angular point moving under a world coordinate system, where the angular point displacement of the target angular point is a displacement of a second position coordinate — a first position coordinate, the angular point displacement is obtained according to the first position coordinate and the second position coordinate of each target angular point, and the velocity of the object to be detected is calculated according to the angular point displacement and a preset time interval. Specifically, the average angular point displacement is divided by a preset time interval to obtain the speed of the object to be detected.
In other embodiments of the present invention, the step of obtaining the corner displacement according to the first position coordinate and the second position coordinate of each target corner, and calculating the speed of the object to be detected according to the corner displacement and the preset time interval may further be understood as calculating a difference value between the first position coordinate and the second position coordinate of each target corner to obtain the corner displacement of each target corner, and calculating the corner speed corresponding to the target corner according to the corner displacement corresponding to the target corner and the preset time interval, specifically, the corner speed is the corner displacement/the preset time interval. Then, according to the above manner, the angular point speeds corresponding to all the target angular points are obtained, and then the angular point speeds corresponding to all the target angular points are averaged to obtain the speed of the object to be detected.
The method comprises the steps of obtaining a first image and a second image which comprise an object to be detected and identification lines according to a preset time interval, detecting target angular points which exist in the first image and the second image, obtaining angular point displacement of the object to be detected within the preset interval according to coordinates of the target angular points, and further calculating the speed of the object to be detected. The speed of the train can be detected when the train runs at a slow speed in the loading process, and the problem that the running speed of the train cannot be detected by radar speed measurement or can be reflected for a long time is solved.
With reference to the method flows of fig. 4 to fig. 5, a possible implementation manner of the speed measuring device 300 is given below, where the speed measuring device 300 may be implemented by using a device structure of the image capturing device 100 in the foregoing embodiment, or implemented by using the processor 101 in the image capturing device 100, please refer to fig. 6, and fig. 6 shows a block schematic diagram of the speed measuring device provided in the embodiment of the present invention. The speed measuring device 300 comprises an obtaining module 301 and a processing module 302.
An obtaining module 301, configured to obtain a first image and a second image that include an object to be detected according to a preset time interval, where the first image and the second image both include an identification line;
a processing module 302, configured to detect all target corner points in a first image and a second image, where the first image and the second image both include the target corner point; and obtaining the angular point displacement of the object to be detected within a preset time interval according to the coordinates of each target angular point, and further calculating the speed of the object to be detected.
In this embodiment of the present invention, the processing module 302 executes a step of detecting all target corner points in the first image and the second image, specifically to: carrying out corner detection on the first image to obtain a first corner set; carrying out corner point detection on the second image to obtain a second corner point set; all target corner points are determined from the first set of corner points and the second set of corner points.
The processing module 302 performs the step of determining all target corner points from the first set of corner points and the second set of corner points, specifically to: acquiring a first corner coordinate of each first corner in the first image; acquiring second corner coordinates of each second corner in the second image; obtaining a prediction angular point coordinate corresponding to the first angular point coordinate according to the first angular point coordinate, a preset time interval and a preset angular point motion model; calculating deviation information corresponding to the second corner point according to the second corner point coordinate and the predicted corner point coordinate; and comparing the deviation information with a deviation threshold value, and taking a second corner point corresponding to the deviation information as a target corner point when the deviation information is smaller than the deviation threshold value.
The processing module 302 executes the steps of obtaining angular point displacement of the object to be detected within a preset time interval according to the coordinates of each target angular point, and further calculating the speed of the object to be detected, and is specifically configured to: respectively acquiring a first image coordinate of each target corner point in a first image and a second image coordinate in a second image; obtaining a first position coordinate of the target corner point in a world coordinate system according to the first image coordinate and a preset conversion model; obtaining a second position coordinate of the target corner point in a world coordinate system according to the second image coordinate and a preset conversion model; and obtaining angular point displacement according to the first position coordinates and the second position coordinates of each target angular point, and calculating the speed of the object to be detected according to the angular point displacement and a preset time interval.
The processing module 302 performs the step of calculating the speed of the object to be detected according to the angular point displacement and the preset time interval, and is specifically configured to: calculating average angular point displacement according to angular point displacement corresponding to all target angular points; and calculating the speed of the object to be detected according to the average angular point displacement and the preset time interval.
In other embodiments of the present invention, the processing module 302 performs the step of calculating the speed of the object to be detected according to the angular point displacement and the preset time interval, and may be further specifically configured to: calculating the angular point speed corresponding to the target angular point according to the angular point displacement corresponding to the target angular point and a preset time interval; and averaging the angular point speeds corresponding to all the target angular points to obtain the speed of the object to be detected.
In summary, embodiments of the present invention provide a speed measurement method, apparatus, and system, where the method includes: the method comprises the steps of obtaining a first image and a second image which comprise an object to be detected and identification lines according to a preset time interval, detecting target angular points which exist in the first image and the second image, obtaining angular point displacement of the object to be detected within the preset interval according to coordinates of the target angular points, and further calculating the speed of the object to be detected. The speed of the train can be detected when the train runs at a slow speed in the loading process, and the problem that the running speed of the train cannot be detected by radar speed measurement or can be reflected for a long time is solved.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, the functional modules in the embodiments of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules 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 may 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 server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes. It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
Claims (10)
1. The speed measuring method is characterized in that the speed measuring method is applied to a camera device of a speed measuring system and used for detecting the speed of an object to be detected, the speed measuring system further comprises a laser emitting device, the laser emitting device is used for emitting laser to be projected onto the object to be detected to form a marking line, and the marking line and a reinforcing structure of the object to be detected form an angular point; the method comprises the following steps:
acquiring a first image and a second image containing the object to be detected according to a preset time interval, wherein the first image and the second image both contain identification lines;
detecting all target corner points in the first image and the second image, wherein the first image and the second image both comprise the target corner points;
obtaining angular point displacement of the object to be detected within the preset time interval according to the coordinates of each target angular point, and further calculating the speed of the object to be detected;
the step of detecting all target corner points in the first image and the second image includes:
and performing threshold binarization on the first image and the second image to obtain a first binary image and a second binary image which contain the identification lines, then extracting the identification lines in the first binary image and the second binary image by adopting Hough transform to obtain a first identification image and a second identification image, and finally performing corner detection on the first identification image and the second identification image to determine a target corner.
2. The method of claim 1, wherein the step of detecting all target corner points in the first image and the second image comprises:
carrying out corner detection on the first image to obtain a first corner set;
carrying out corner point detection on the second image to obtain a second corner point set;
and determining all target corner points from the first corner point set and the second corner point set.
3. The method of claim 2, wherein the first set of corners includes at least one first corner, wherein the second set of corners includes at least one second corner, and wherein the step of determining all target corners from the first set of corners and the second set of corners comprises:
acquiring a first corner coordinate of each first corner in a first image;
acquiring second corner coordinates of each second corner in a second image;
obtaining a prediction angular point coordinate corresponding to the first angular point coordinate according to the first angular point coordinate, a preset time interval and a preset angular point motion model;
calculating deviation information corresponding to the second corner point according to the second corner point coordinate and the prediction corner point coordinate;
and comparing the deviation information with a deviation threshold value, and taking a second corner point corresponding to the deviation information as a target corner point when the deviation information is smaller than the deviation threshold value.
4. The method according to claim 1, wherein the step of obtaining the angular point displacement of the object to be detected within the preset time interval according to the coordinates of each target angular point, and further calculating the speed of the object to be detected comprises:
respectively acquiring a first image coordinate of each target corner point in the first image and a second image coordinate in the second image;
obtaining a first position coordinate of the target corner point in a world coordinate system according to the first image coordinate and a preset conversion model;
obtaining a second position coordinate of the target corner point in a world coordinate system according to the second image coordinate and a preset conversion model;
and obtaining angular point displacement according to the first position coordinate and the second position coordinate of each target angular point, and calculating the speed of the object to be detected according to the angular point displacement and the preset time interval.
5. The method according to claim 4, wherein the step of calculating the velocity of the object to be detected based on the angular point displacement and the preset time interval comprises:
calculating average angular point displacement according to the angular point displacement corresponding to all the target angular points;
and calculating the speed of the object to be detected according to the average angular point displacement and the preset time interval.
6. The method according to claim 4, wherein the step of calculating the velocity of the object to be detected based on the angular point displacement and the preset time interval comprises:
calculating the angular point speed corresponding to the target angular point according to the angular point displacement corresponding to the target angular point and the preset time interval;
and averaging the angular point speeds corresponding to all the target angular points to obtain the speed of the object to be detected.
7. The speed measuring device is characterized by being applied to a camera device of a speed measuring system and used for detecting the speed of an object to be detected, and the speed measuring system also comprises a laser emitting device, wherein the laser emitting device is used for emitting laser to be projected onto the object to be detected to form a marking line, and the marking line and a reinforcing structure of the object to be detected form an angular point; the device comprises:
the device comprises an acquisition module, a detection module and a processing module, wherein the acquisition module is used for acquiring a first image and a second image which comprise the object to be detected according to a preset time interval, and the first image and the second image both comprise identification lines;
a processing module, configured to detect all target corner points in the first image and the second image, where the first image and the second image both include the target corner point; obtaining angular point displacement of the object to be detected within the preset time interval according to the coordinates of each target angular point, and further calculating the speed of the object to be detected;
the processing module is used for:
and performing threshold binarization on the first image and the second image to obtain a first binary image and a second binary image which contain the identification lines, then extracting the identification lines in the first binary image and the second binary image by adopting Hough transform to obtain a first identification image and a second identification image, and finally performing corner detection on the first identification image and the second identification image to determine a target corner.
8. The apparatus of claim 7, wherein the processing module is specifically configured to:
carrying out corner detection on the first image to obtain a first corner set;
carrying out corner point detection on the second image to obtain a second corner point set;
and determining all target corner points from the first corner point set and the second corner point set.
9. The apparatus of claim 7, wherein the processing module is specifically configured to:
respectively acquiring a first image coordinate of each target corner point in the first image and a second image coordinate in the second image;
obtaining a first position coordinate of the target corner point in a world coordinate system according to the first image coordinate and a preset conversion model;
obtaining a second position coordinate of the target corner point in a world coordinate system according to the second image coordinate and a preset conversion model;
and calculating the speed of the object to be detected according to the first position coordinate and the second position coordinate of each target corner point and the preset time interval.
10. A speed measuring system is characterized by comprising a camera device and a laser emitting device, wherein the camera device is used for detecting the speed of an object to be detected, the laser emitting device is used for emitting laser to be projected onto the object to be detected to form a marking line, and the marking line and a reinforcing structure of the object to be detected form an angular point; the image pickup apparatus includes:
one or more processors;
memory storing one or more programs that, when executed by the one or more processors, cause the one or more processors to implement the method of any of claims 1-6.
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| CN103854293A (en) * | 2014-02-26 | 2014-06-11 | 奇瑞汽车股份有限公司 | Vehicle tracking method and device based on feature point matching |
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