CN111667408A - Vehicle image processing method and device, storage medium and processor - Google Patents
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Abstract
The invention discloses a vehicle image processing method and device, a storage medium and a processor. Wherein, the method comprises the following steps: identifying a simulation picture of the vehicle to obtain a global graph and a local graph of the vehicle; acquiring the size of the local graph and the local graph after zeroing processing; and combining the local graph after the zeroing processing and the global graph based on the size of the local graph to generate a result graph of the vehicle. The invention solves the technical problems that the global graph and the local graph in the prior art need to be respectively identified, grabbed and synthesized manually and have low processing efficiency.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to a method and a device for processing a vehicle image, a storage medium and a processor.
Background
In the process of rail vehicle body strength simulation automation, the vehicle body strength calculation working conditions are various, and when a simulation analysis report is made, each working condition can display simulation result pictures of a plurality of structural components such as a whole vehicle, a side wall, a end wall, a roof, an underframe and the like; in addition, in general, the global graph and the local graph need to be manually identified, grabbed and synthesized respectively, and the operation process is complex. Although the existing commercial finite element software can directly derive the global map of the car body and the local part to be focused on, the two maps are not in one map, and a structural strength simulator is required to combine hundreds of global maps and local maps, which takes a lot of labor.
Aiming at the problems that the global graph and the local graph in the prior art need to be manually identified, grabbed and synthesized respectively, and the processing efficiency is low, an effective solution is not provided at present.
Disclosure of Invention
The embodiment of the invention provides a vehicle image processing method and device, a storage medium and a processor, which are used for at least solving the technical problems that in the prior art, a global image and a local image need to be manually and respectively identified, captured and synthesized, and the processing efficiency is low.
According to an aspect of an embodiment of the present invention, there is provided a method for processing a vehicle image, including: identifying a simulation picture of a vehicle to obtain a global graph and a local graph of the vehicle; acquiring the size of the local graph and the local graph after zeroing processing; and combining the local graph after the zeroing processing and the global graph based on the size of the local graph to generate a result graph of the vehicle.
Optionally, before acquiring the size of the partial map and the zero-returned partial map, the vehicle image processing method further includes: scanning the pixel colors of the local graph, counting the types of the colors and the positions of pixel points of each color, and determining the color position of each color in the local graph; and performing zeroing processing on the color position of each color in the local graph.
Optionally, performing zeroing processing on the color position of each color in the local map, including: performing coordinate conversion on the color position of each color to obtain the minimum coordinate of the color position of each color based on a zero point; and zeroing the color position after the coordinate conversion.
Optionally, before the zeroed local map and the global map are merged based on the size of the local map to generate a result map of the vehicle, the vehicle image processing method further includes: searching in the global map based on the size of the local map, and determining whether a region with the size larger than or equal to that of the local map exists in the global map; and if the region with the size larger than or equal to the size of the local graph does not exist in the global graph, gradually scaling the local graph after the zeroing processing according to a proportion until the region with the size larger than or equal to the scaled local graph exists in the global graph.
Optionally, merging the local graph after the zeroing process and the global graph, including: acquiring the position of the area of the zoomed local image with the size larger than or equal to the global difference; and drawing the local graph at the position.
According to another aspect of the embodiments of the present invention, there is also provided a vehicle image processing apparatus including: the identification module is used for identifying the simulation picture of the vehicle to obtain a global graph and a local graph of the vehicle; the acquisition module is used for acquiring the size of the local graph and the local graph after the zeroing processing; and the merging module is used for merging the local graph after the zeroing processing and the global graph based on the size of the local graph to generate a result graph of the vehicle.
Optionally, the vehicle image processing apparatus further includes: the scanning module is used for scanning pixel colors of the local image; the statistical module is used for counting the types of colors and the positions of pixel points of each color and determining the color position of each color in the local graph; and the zeroing processing module is used for performing zeroing processing on the color position of each color in the local image.
Optionally, the zeroing processing module includes: the conversion module is used for carrying out coordinate conversion on the color position of each color to obtain the minimum coordinate of the color position of each color based on a zero point; and the zeroing module is used for zeroing the color position after the coordinate conversion.
Optionally, the vehicle image processing apparatus further includes: the searching module is used for searching in the global map based on the size of the local map and determining whether an area with the size larger than or equal to the size of the local map exists in the global map; and the scaling module is used for scaling the local graph after the zeroing processing step by step according to a proportion until the region of the local graph with the size larger than or equal to the scaled size exists in the global graph.
Optionally, the merging module includes: a sub-obtaining module, configured to obtain a position of a region of the zoomed local image with a size greater than or equal to the global difference; and the drawing module is used for drawing the local graph at the position.
According to another aspect of the embodiments of the present invention, there is also provided a storage medium including a stored program, wherein the program executes the method for processing the vehicle image according to any one of the above.
According to another aspect of the embodiment of the present invention, there is also provided a processor for executing a program, wherein the program executes the method for processing the vehicle image according to any one of the above methods.
In the embodiment of the invention, a simulation picture for identifying the vehicle is adopted to obtain a global graph and a local graph of the vehicle; acquiring the size of the local graph and the local graph after zeroing processing; the method for processing the vehicle image provided by the embodiment of the invention realizes the purpose of automatically identifying and merging the global image and the local image after the rail vehicle body strength simulation post-processing, achieves the technical effect of shortening the whole period of the rail vehicle body strength simulation analysis, and further solves the technical problems that the global image and the local image in the prior art need to be manually identified, captured and synthesized respectively, and the processing efficiency is low.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
FIG. 1 is a flow chart of a method of processing a vehicle image according to an embodiment of the invention;
FIG. 2(a) is a global diagram of a vehicle according to an embodiment of the present invention;
FIG. 2(b) is a partial view of a vehicle according to an embodiment of the invention;
FIG. 3 is a diagram of a simulation result of a vehicle body merged by a global map and a local map according to an embodiment of the present invention;
FIG. 4 is a flow chart of an alternative method of processing vehicle images in accordance with an embodiment of the present invention;
fig. 5 is a schematic diagram of a processing device of a vehicle image according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, 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. 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 should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
In accordance with an embodiment of the present invention, there is provided a method embodiment of a method for processing a vehicle image, wherein the steps illustrated in the flowchart of the figure may be performed in a computer system, such as a set of computer executable instructions, and wherein although a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than that illustrated herein.
Fig. 1 is a flowchart of a processing method of a vehicle image according to an embodiment of the present invention, as shown in fig. 1, the processing method of the vehicle image including the steps of:
and S102, identifying the simulation picture of the vehicle to obtain a global image and a local image of the vehicle.
Optionally, the simulation picture may be a picture of the vehicle obtained by processing an image of the vehicle by using image simulation software, and after the simulation picture of the vehicle is obtained, a global map and a local map of the vehicle are obtained by identifying in an image identification manner.
Where fig. 2(a) is a global view of a vehicle according to an embodiment of the present invention, fig. 2(b) is a local view of the vehicle according to the embodiment of the present invention, and the global view and the local view shown in fig. 2(a) and fig. 2(b) are inputs of a vehicle body image processing system.
In addition, in the embodiment of the present invention, the vehicle may be a rail train.
And step S104, acquiring the size of the local graph and the local graph after the zeroing processing.
And S106, merging the local graph after the zeroing processing and the global graph based on the size of the local graph to generate a result graph of the vehicle.
Therefore, in the embodiment of the invention, the simulation picture of the vehicle can be identified to obtain the global graph and the local graph of the vehicle; acquiring the size of the local graph and the local graph after zeroing processing; and combining the local graph subjected to the zeroing processing and the global graph based on the size of the local graph to generate a result graph of the vehicle, so that the aims of automatically identifying and combining the global graph and the local graph subjected to the rail vehicle body strength simulation post-processing are fulfilled, and the technical effect of shortening the whole period of rail vehicle body strength simulation analysis is achieved.
It is worth noting that in the embodiment of the invention, after the global graph and the local graph of the vehicle are identified and obtained, the local graph after the zeroing processing and the global graph are merged based on the size of the local graph to generate the result graph of the vehicle, so that on the premise of meeting the simulation accuracy, the processing efficiency of the global graph and the local graph after the rail vehicle body strength simulation is improved, and the error of the global graph and the local graph after the vehicle body strength simulation is artificially identified and processed is reduced.
Therefore, the vehicle image processing method provided by the embodiment of the invention solves the technical problems that in the prior art, the global image and the local image need to be manually and respectively identified, captured and synthesized, and the processing efficiency is low.
In an optional embodiment, before acquiring the size of the partial map and zeroing the processed partial map, the vehicle image processing method may further include: scanning pixel colors of the local image, counting the types of the colors and the positions of pixel points of each color, and determining the color position of each color in the local image; and performing zeroing processing on the color position of each color in the local image.
In this embodiment, the local graph shown in fig. 2(b) may be scanned for pixel colors by using an image processing technique, and then the types of the scanned colors and the pixel point positions of each color are counted to determine the color position of each color in the local graph, so as to perform the zeroing process on the color position of each color in the local graph.
In the above embodiment, the zeroing process performed on the color position of each color in the local map includes: performing coordinate conversion on the color position of each color to obtain the minimum coordinate of the color position of each color based on a zero point; and zeroing the color position after the coordinate conversion.
In an optional embodiment, before the combining the zeroed local graph with the global graph to generate the result graph of the vehicle based on the size of the local graph, the processing method of the vehicle image may further include: searching in the global graph based on the size of the local graph, and determining whether a region with the size larger than or equal to that of the local graph exists in the global graph; and if the region with the size larger than or equal to that of the local image does not exist in the global image, gradually scaling the local image subjected to the zeroing processing according to the proportion until the region with the size larger than or equal to that of the scaled local image exists in the global image.
In this embodiment, the size of the local graph after zeroing may be automatically measured and identified, a position where the local graph can be put down is automatically searched in the global graph, and if the local graph after zeroing cannot be put down in the global graph, the local graph after zeroing is gradually reduced according to a certain proportion until an area of the local graph after reduction in size is greater than or equal to exists in the global graph, thereby ensuring that the local graph after zeroing and the global graph can be merged.
In an alternative embodiment, merging the zeroed local graph and the global graph includes: acquiring the position of a region of the zoomed local image with the size larger than or equal to the global difference; the partial map is drawn at the location.
In the embodiment of the present invention, when generating the result graph of the vehicle, the result graph may be output to a picture file, and fig. 3 is a vehicle body simulation result graph obtained by merging the global graph and the local graph according to the embodiment of the present invention.
FIG. 4 is a flow chart of an alternative method for processing a vehicle image according to an embodiment of the present invention, as shown in FIG. 4, first scanning all pixel colors of a local image and counting colors and their coordinates; performing coordinate conversion on the counted colors to enable the minimum coordinate of the colors to be based on a 0 point, and performing zeroing processing; in the global graph, automatically searching the position of the local graph after the zero setting can be put down; judging whether the searching is successful, if so, completing the graph combination; conversely, the local graph is reduced by a certain proportion; in the global map, the automatic search can put down the position of the reduced local map.
As can be seen from the above, in the embodiment of the present invention, after the global map and the local map of the vehicle are identified, the image processing technology may be used to scan the pixel colors of the local map, count the color positions, calculate and analyze the positions of all colors, and perform zeroing processing on the counted color positions of the local map; then automatically measuring and identifying the size of the local graph after zeroing, and automatically searching the position where the local graph can be put down in the global graph; if the local graph after the zero resetting can not be put down in the global graph, the local graph after the zero resetting is gradually reduced according to a certain proportion until the local graph can be put down in the global graph; finding a searched position in the global graph, and drawing a local graph at the position; and combining the global graph and the local graph into a result graph of vehicle body simulation post-processing.
The vehicle image processing method provided by the embodiment of the invention is based on picture files such as a global graph and a local graph of a simulation result output by common commercial finite element simulation analysis software, automatically identifies and captures a processed graph after vehicle body strength simulation, and can automatically carry out secondary processing, processing and the like on the result graph, so that a combined picture which simultaneously displays the global graph and the local graph of the vehicle body strength simulation result is rapidly output.
The vehicle image processing method provided by the embodiment of the invention has the following beneficial effects: (1) the automatic identification and combination of the global graph and the local graph of the rail vehicle body strength simulation post-processing can be realized, so that the automation of the post-processing of the vehicle body strength simulation analysis is realized, the labor cost is saved, and the whole research and development period of the rail vehicle body strength simulation analysis is shortened; (2) the technical support foundation can be laid for the realization of the simulation automation of the rail vehicle, the global graph and the local graph are automatically identified after the simulation of the vehicle body strength, and the errors of the global graph and the local graph after the simulation of the vehicle body strength is manually identified can be reduced; the rail vehicle body strength simulation post-processing global graph and the local graph are automatically merged, the optimal position where the local graph needs to be placed can be automatically found, and the global graph and the local graph are automatically merged into a simulation result graph in a standard format, so that the purposes of automatically identifying and merging the global graph and the local graph of the rail vehicle body strength simulation post-processing and automating the vehicle body strength simulation analysis post-processing can be achieved, the labor cost is saved, and the technical effect of shortening the whole research and development period of the rail vehicle body strength simulation analysis is achieved.
Example 2
According to another aspect of the embodiment of the present invention, there is also provided a processing apparatus for a vehicle image, fig. 5 is a schematic diagram of the processing apparatus for a vehicle image according to the embodiment of the present invention, and as shown in fig. 5, the processing apparatus for a vehicle image may include: an identification module 51, an acquisition module 53 and a merging module 55. The following describes the vehicle image processing device in detail.
And the identification module 51 is used for identifying the simulation picture of the vehicle to obtain a global map and a local map of the vehicle.
And an obtaining module 53, configured to obtain the size of the partial map and the partial map after the zeroing process.
And the merging module 55 is configured to merge the local graph after the zeroing process and the global graph based on the size of the local graph to generate a result graph of the vehicle.
It should be noted here that the above-mentioned identifying module 51, the obtaining module 53 and the merging module 55 correspond to steps S102 to S106 in the embodiment, and the above-mentioned units are the same as the examples and application scenarios realized by the corresponding steps, but are not limited to the disclosure of the above-mentioned embodiment. It should be noted that the above-described elements as part of an apparatus may be implemented in a computer system, such as a set of computer-executable instructions.
Therefore, in the above embodiment of the present application, the simulation picture of the vehicle may be identified by the identification module to obtain the global map and the local map of the vehicle; then, acquiring the size of the local graph and the local graph after zeroing processing by using an acquisition module; the invention further provides a vehicle image processing device, and the vehicle image processing device is used for realizing the purpose of automatic identification and combination of the global image and the local image after the rail vehicle body strength simulation, achieving the technical effect of shortening the whole period of rail vehicle body strength simulation analysis, and further solving the technical problems that the global image and the local image need to be manually identified, grabbed and synthesized respectively in the prior art, and the processing efficiency is low.
In an optional embodiment, the vehicle image processing apparatus further includes: the scanning module is used for scanning pixel colors of the local image; the statistical module is used for counting the types of the colors and the positions of pixel points of each color and determining the color position of each color in the local graph; and the zeroing processing module is used for performing zeroing processing on the color position of each color in the local image.
In an alternative embodiment, the zeroing processing module comprises: the conversion module is used for carrying out coordinate conversion on the color position of each color to obtain the minimum coordinate of the color position of each color based on a zero point; and the zeroing module is used for zeroing the color position after the coordinate conversion.
In an optional embodiment, the vehicle image processing apparatus further includes: the search module is used for searching in the global graph based on the size of the local graph and determining whether an area with the size larger than or equal to that of the local graph exists in the global graph; and the scaling module is used for gradually scaling the local image after the zeroing processing according to a proportion until the region of the local image with the size larger than or equal to the scaled size exists in the global image if the region with the size larger than or equal to the local image does not exist in the global image.
In an alternative embodiment, the merging module includes: the sub-acquisition module is used for acquiring the positions of the areas of the local images with the sizes larger than or equal to the zoomed size in the global difference; and the drawing module is used for drawing the local graph at the position.
Example 3
According to another aspect of the embodiments of the present invention, there is also provided a storage medium including a stored program, wherein the program executes the method of processing the vehicle image of any one of the above.
Example 4
According to another aspect of the embodiment of the present invention, there is also provided a processor for executing a program, wherein the program executes a processing method of the vehicle image according to any one of the above.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
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 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 Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (12)
1. A method for processing an image of a vehicle, comprising:
identifying a simulation picture of a vehicle to obtain a global graph and a local graph of the vehicle;
acquiring the size of the local graph and the local graph after zeroing processing;
and combining the local graph after the zeroing processing and the global graph based on the size of the local graph to generate a result graph of the vehicle.
2. The method of claim 1, wherein prior to obtaining the size of the partial map and zeroing the processed partial map, the method further comprises:
scanning the pixel colors of the local graph, counting the types of the colors and the positions of pixel points of each color, and determining the color position of each color in the local graph;
and performing zeroing processing on the color position of each color in the local graph.
3. The method of claim 2, wherein performing a zeroing process on the color position of each color in the local map comprises:
performing coordinate conversion on the color position of each color to obtain the minimum coordinate of the color position of each color based on a zero point;
and zeroing the color position after the coordinate conversion.
4. The method of claim 1, wherein prior to merging the zeroed local graph with the global graph to generate a result graph for the vehicle based on the size of the local graph, the method further comprises:
searching in the global map based on the size of the local map, and determining whether a region with the size larger than or equal to that of the local map exists in the global map;
and if the region with the size larger than or equal to the size of the local graph does not exist in the global graph, gradually scaling the local graph after the zeroing processing according to a proportion until the region with the size larger than or equal to the scaled local graph exists in the global graph.
5. The method of claim 4, wherein merging the zeroed local graph with the global graph comprises:
acquiring the position of the area of the zoomed local image with the size larger than or equal to the global difference;
and drawing the local graph at the position.
6. A vehicle image processing apparatus, comprising:
the identification module is used for identifying the simulation picture of the vehicle to obtain a global graph and a local graph of the vehicle;
the acquisition module is used for acquiring the size of the local graph and the local graph after the zeroing processing;
and the merging module is used for merging the local graph after the zeroing processing and the global graph based on the size of the local graph to generate a result graph of the vehicle.
7. The apparatus of claim 6, further comprising:
the scanning module is used for scanning pixel colors of the local image;
the statistical module is used for counting the types of colors and the positions of pixel points of each color and determining the color position of each color in the local graph;
and the zeroing processing module is used for performing zeroing processing on the color position of each color in the local image.
8. The apparatus of claim 7, wherein the zeroing processing module comprises:
the conversion module is used for carrying out coordinate conversion on the color position of each color to obtain the minimum coordinate of the color position of each color based on a zero point;
and the zeroing module is used for zeroing the color position after the coordinate conversion.
9. The apparatus of claim 6, further comprising:
the searching module is used for searching in the global map based on the size of the local map and determining whether an area with the size larger than or equal to the size of the local map exists in the global map;
and the scaling module is used for scaling the local graph after the zeroing processing step by step according to a proportion until the region of the local graph with the size larger than or equal to the scaled size exists in the global graph.
10. The apparatus of claim 9, wherein the merging module comprises:
a sub-obtaining module, configured to obtain a position of a region of the zoomed local image with a size greater than or equal to the global difference;
and the drawing module is used for drawing the local graph at the position.
11. A storage medium characterized by comprising a stored program, wherein the program executes the method of processing a vehicle image according to any one of claims 1 to 5.
12. A processor, characterized in that the processor is configured to run a program, wherein the program is configured to execute the method of processing the vehicle image according to any one of claims 1 to 5 when running.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010491677.5A CN111667408B (en) | 2020-06-02 | 2020-06-02 | Vehicle image processing method and device, storage medium and processor |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010491677.5A CN111667408B (en) | 2020-06-02 | 2020-06-02 | Vehicle image processing method and device, storage medium and processor |
Publications (2)
| Publication Number | Publication Date |
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| CN111667408A true CN111667408A (en) | 2020-09-15 |
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