CN112765378B - Method and system for constructing electronic map data structure based on image matching - Google Patents
Method and system for constructing electronic map data structure based on image matching Download PDFInfo
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- G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
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Abstract
The invention discloses a method and a system for constructing an electronic map data structure based on image matching, wherein the method comprises the following steps: selecting a train running section, and storing section information of the section; determining the attribute of the feature point, and determining whether to add an additional attribute according to the attribute of the feature point; storing the link relation between the characteristic points and the distance error range between the characteristic points; storing the focal length, weather, light and filter factors in a corresponding digital form; coding the stored information in a data form to form an electronic map data structure; the system comprises a road section information storage unit, a characteristic point unit, an external factor storage unit and a data structure coding unit; according to the invention, through constructing an electronic map data structure, the corresponding shooting conditions of the high-speed camera during shooting are determined, so that shooting interference is better filtered, and advance preparation can be made through the link among the characteristic points, so that more optimized three-dimensional electronic map characteristic points are obtained.
Description
Technical Field
The invention belongs to the field of train positioning, and particularly relates to a method and a system for constructing an electronic map data structure based on image matching.
Background
The railway train control system is provided with a speed and distance measuring service currently, and the combined multi-dimensional speed and distance measuring system comprises a speed sensor, a speed measuring radar, an acceleration sensor, a transponder, a track circuit, an axle counter and the like. The combination of the above steps provides a high-safety speed and distance measuring function for the train control vehicle-mounted system, the safety of the train is guaranteed, but the speed and distance measuring cost of the railway train control system is high, and in the face of numerous sensing devices, the development cost is increased, the technical integration difficulty is increased, and the installation difficulty of the train is increased.
In order to solve the problem of high cost caused by speed and distance measurement, researchers of the existing train control system try to replace the traditional train positioning technology with the satellite positioning technology and obtain certain results.
However, the application of the satellite positioning technology to high-speed rails still has certain limitations, for example, in tibet railway, since more than half of the lines are tunnels, the satellite positioning technology is not used necessarily. Satellite positioning technology also has limitations in traversing urban underground high-speed rail lines.
Therefore, finding a universal positioning technical means which is independent of terrain and can reduce the cost of positioning basic equipment is a necessary choice for the future development of train control technology.
The rapid development of the image matching technology, the image technology is utilized to carry out various technologies such as identity recognition, intelligent analysis and the like, and the alpha dog wins the world champions and the like through artificial intelligence, which indicates that the image technology can be well applied to the aspects of life. The identity recognition is applied to the financial field such as banks and the like, which shows that the security of the identity recognition is also verified maturely. The image technology is also applied to high-speed rails, a camera and a millimeter wave radar are installed in a high-speed rail system for achieving an anti-collision function of a train for acquiring the road condition in front of the train, and an image recognition function is also adopted in a remote control system.
Although image recognition is not applied in the safety field, the image recognition plays a certain role in train driving, and the technical experience and accumulation are undoubtedly provided for the application of the image matching technology in high-speed rail train control positioning. However, the precondition of the application of the graph matching technology is to acquire a high-quality image, most of the existing image acquisition modes are directly acquired by adopting a high-speed camera, but due to the fact that the operation process of a train is different in length, the terrain and the features of the train are different, and the influence of various weather factors, the acquired image is affected, the high-quality image cannot be acquired, the extraction of feature point data is affected, and therefore the positioning is inaccurate.
Disclosure of Invention
Aiming at the problems, the invention provides a method and a system for constructing an electronic map data structure based on image matching, which overcome the problems in the image acquisition process by constructing the electronic map data structure.
The invention discloses a method for constructing an electronic map data structure based on image matching,
the construction method comprises the following steps:
selecting a train running section, and storing section information of the section in a data form;
determining the attribute of the feature point, and formulating a corresponding additional attribute according to the attribute of the feature point;
storing the link relation between the characteristic points and storing the distance error range between the characteristic points;
storing the specific forms of the focal length factor, the weather factor, the light factor and the filter factor in a corresponding digital form;
and coding the stored information in a data form to form a three-dimensional electronic map data structure.
Further, the link relation includes establishing a link relation of an actual distance and an error distance between the feature point and the next feature point, and storing the distance data.
Further, the attributes of the feature points include general points and special points, the general points are feature points in normal terrain, and the special points represent feature points in special terrain, including tunnels, stations, bridges and grasslands.
Further, the additional attribute comprises that a reminding setting is additionally added when the special point data is stored.
Further, the weather factors include rainy days, foggy days, snowy days, cloudy days and sunny days, and the light factors include daytime light, highlight light, night light and evening light.
Further, the filter information comprises a grassland background, a tunnel background and a forest background, and the focal length factor comprises a focal length specific multiple.
The invention also discloses a system for constructing the electronic map data structure based on image matching,
the system comprises a road section information storage unit, a characteristic point unit, an external factor storage unit and a data structure coding unit;
wherein the content of the first and second substances,
the road section information storage unit is used for storing the road section information in a data form;
the characteristic point unit is used for storing the characteristic point attribute information and the additional attribute information in a data form;
the characteristic point unit is also used for storing the link relation between the characteristic points and the distance error between the characteristic points;
the external factor unit is used for storing external factor information of various influences on the acquired image such as focal length, weather, light and a filter;
and the data structure coding unit is used for integrally coding the data information stored in the road section information storage unit, the characteristic point unit and the external factor storage unit to form a complete data structure.
Further, before the feature point data of the feature point unit is stored in a transformed form, the feature point image is subjected to data extraction, and the extracted image data is stored.
Further, various factors stored in the external factor unit are stored in a numerical value form, and specific numerical values correspond to corresponding external factor conditions.
The invention has the beneficial effects that:
according to the invention, the weather factors, the light factors and the background conditions are stored, and the corresponding shooting conditions of the high-speed camera during shooting are determined, so that shooting interference is better filtered, and more optimized three-dimensional electronic map feature points are obtained;
according to the invention, an electronic map data structure is constructed by the link relation between the background condition and the characteristic points of the acquired image, so that the high-speed camera can correspondingly adjust the shooting condition when acquiring the image, and can make advance preparation through the link between the characteristic points, thereby obtaining better shooting quality.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
FIG. 1 is a flow chart of a train control positioning method for a high-speed rail of a train according to an embodiment of the invention;
FIG. 2 is a diagram illustrating a relationship between feature point acquisition models in an embodiment of the present invention;
fig. 3 shows a schematic diagram of an electronic map data structure in the embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, 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, but 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.
The invention discloses a high-speed rail train control positioning method and a high-speed rail train control positioning system based on image matching.
Referring to fig. 1, the train control positioning method for high-speed rail of the present invention includes the following steps:
the first step is as follows: building an initial three-dimensional electronic map database
Before the line starts to operate, key characteristic points of the line are collected along the way through slow running of an engineering train, after a complete initial three-dimensional electronic map database is obtained, the gradual increasing speed of the train in the initial three-dimensional electronic map database is established to form a corresponding speed grade, and when a new train is added, the new train is synchronized to the new train.
Meanwhile, when the initial three-dimensional electronic map database is generated, the distance between each feature point and the initial feature point is measured, and the link relation between adjacent feature points or between two adjacent feature points is established, so that the absolute position of the train and the distance from the starting point are known after the train acquires the feature points.
The second step is that: initial positioning
After the initial three-dimensional electronic map database is established, the absolute position of the current track of the train can be determined according to the in-station characteristic points by acquiring the in-station characteristic points, so that the initial train position is obtained.
Because the initial characteristic point is generally in the station, it is easy to obtain, and easy to observe and convenient to change.
The third step: continuous positioning (Interval positioning and feature Point acquisition)
Because each feature point in the initial three-dimensional electronic map database links the specific position of the next feature point, when the train is about to arrive at the next feature point, the high-speed camera is prepared in advance, once the train arrives, the image is obtained immediately, if the obtained image fails when the train arrives at the position, the feature point is considered to be unsuccessfully obtained, and then the next feature point is continuously found.
The fourth step: feature point matching
And setting a threshold value of the matching degree of the feature points, if the matching degree is greater than or equal to the threshold value, determining that the feature points are qualified in matching, and executing the fifth step.
The fifth step: and acquiring geographic coordinates to form the position of the train.
And obtaining the current geographic coordinates according to the positions of the characteristic points to form the current position of the train.
And if the matching of the feature points is unqualified, updating the feature point data which is unqualified in matching, and forming the updated feature point data into an electronic map database.
The feature points are points with certain obvious features, and the feature points can be obviously distinguished from the environment, so that the selected feature points can be better identified in the subsequent capturing process, and quick capturing is realized. In order to reduce the construction debugging workload caused by speed measurement and distance measurement, a method of simultaneous generation and simultaneous identification is adopted to obtain the characteristic points.
The method for establishing the initial three-dimensional electronic map database comprises the following steps:
s1: establishing a characteristic point acquisition model, wherein lambda = F (x)/L, and L = C/t;
s2: acquiring a topographic image of the running process of the train by using a high-speed camera;
s3: screening the characteristic points according to the characteristic point model, wherein the screening of the characteristic points is realized by firstly setting lambdamin(ii) a Then for the characteristic point lambda value is less than or equal to lambdaminThe characteristic point of (2) is deleted, and the lambda value of the characteristic point is larger than lambdaminThe characteristic points of the values are stored in the initial threeIn a wiki map database;
s4: establishing links among the screened feature points;
s5: and setting a feature point matching threshold, if the feature point matching threshold is larger than the threshold, determining that the matching is successful, if the feature point matching threshold is smaller than the threshold, further updating the feature point, and storing the new feature point.
Referring to fig. 2, x represents the distance that the train travels at each moment of each corresponding specific point, f (x) represents the average reflection height of the image at the distance x, L represents the train travel distance, and the length of L is inversely proportional to time: l = C/t, where C is a constant and t is the time for the train to travel past the characteristic point.
The method for establishing the three-dimensional electronic map database comprises the following steps:
a1: setting a characteristic point matching degree threshold value P, wherein the matching degree threshold value P is determined according to the actual application effect;
a2: acquiring an image through a high-speed camera in the process of train advancing, and matching feature point data in the image with feature point data in an initial three-dimensional electronic map database;
a3: if the matching degree of the matching is more than or equal to P, the original feature point is saved, and if the matching degree of the matching is less than P, the feature point is updated;
a4: and continuously matching the updated feature point data, if the matching is successful, replacing the initial three-dimensional electronic map with the new feature point data and storing the new feature point data in the three-dimensional electronic map database, and if not, continuously matching.
When the matching degree of the characteristic points is smaller than a threshold value, judging whether the characteristic points are caused by the change of the ground environment or not, sending the characteristic point data to a three-dimensional electronic database for storage, waiting for the subsequent train identification, comprehensively analyzing the same characteristic points of a plurality of trains, and if most of the trains consider that the points are changed in environment, updating the old characteristic points by a three-dimensional electronic map database according to a voting mechanism; and after the old characteristic points are updated, continuously matching the new characteristic points, and if the matching is successful, establishing the new characteristic points.
The invention also discloses a high-speed rail train control positioning system based on image matching,
the positioning system comprises an initial three-dimensional electronic map database module, an image acquisition module, an image processing module, a feature point matching module and a three-dimensional electronic map database module;
the system comprises an initial three-dimensional electronic map database module, a data processing module and a data processing module, wherein the initial three-dimensional electronic map database module is used for storing initial three-dimensional electronic map data, and the initial three-dimensional electronic map data comprises feature point data acquired by the slow running of a project train before the train is formally run and geographic coordinates corresponding to the feature points;
the image acquisition module is used for acquiring topographic images along the way in the running process of the train;
the image processing module is used for carrying out data analysis on the image acquired by the image acquisition module and storing the analyzed image data information;
the characteristic point matching module is used for storing a characteristic point matching degree threshold value P, calling the analyzed image data information and matching the characteristic points;
and the three-dimensional electronic map database module is used for storing three-dimensional electronic map data, and comprises updated feature point data and geographic coordinates corresponding to the feature points.
In order to improve the success rate of the high-speed camera for acquiring images, the invention determines the corresponding shooting conditions of the high-speed camera during shooting by storing weather factors, light factors and background conditions, thereby better filtering shooting interference and obtaining more optimized three-dimensional characteristic points. In order to realize the matching of the image after being recognized with an electronic map, the invention provides an electronic map data structure, and a construction method of the data structure comprises the following steps:
selecting a train running section, and storing section information of the section in a data form;
determining the attribute of the feature points, and formulating different additional attributes according to the attribute of the feature points, wherein the feature points comprise general points and special points, the general points are feature points on normal terrain, the special points represent feature points on the special terrain, and the normal terrain comprises cities; the special terrain comprises a tunnel, a station, a bridge and a grassland, and corresponding reminding settings are set before the special point arrives, so that the train prepares image acquisition conditions under corresponding backgrounds in advance;
storing the link relation between the characteristic points and storing the distance error range between the characteristic points, wherein the step of establishing the link relation between the characteristic points specifically refers to the step of establishing the actual distance relation and the error distance between the characteristic points and the next characteristic point and the next two characteristic points;
storing focal length, weather, light and filter information, and storing specific forms of various information in corresponding digital forms, wherein the weather factors comprise rainy days, foggy days, snowy days, cloudy days and sunny days, the light factors comprise daytime light, highlight light, night light and evening light, and the filter information comprises a grassland background, a tunnel background and a forest background;
the information is encoded in a data form to form an electronic map data structure, and the electronic map data structure can automatically run in the running process of a train.
There is no absolute sequence relationship between the above steps, and other operations can be added to the above steps, and the steps are not limited to the above steps.
The invention also provides a system for constructing the electronic map data structure based on image matching, which is used for constructing the electronic map data structure based on image matching.
The construction system comprises a road section information storage unit, a feature point unit, an external factor storage unit and a data structure coding unit;
the road section information storage unit is used for storing the road section information in a data form;
the characteristic point unit is used for storing the characteristic point attribute information and the additional attribute information in a datamation mode, extracting data of a characteristic point image before the characteristic point data of the characteristic point unit are stored in a datamation mode, and then storing the extracted image data;
the characteristic point unit is also used for storing the link relation between the characteristic points and the distance error between the characteristic points;
the external factor unit is used for storing various external factors influencing the acquired image, such as focal length, weather, light and a filter;
and the data structure coding unit is used for integrally coding the data information stored in the road section information storage unit, the characteristic point unit and the external factor storage unit to form a complete electronic map data structure.
Referring to fig. 3, the above-mentioned electronic map data structure is exemplarily explained.
The train from the station A to the station B assumes 4 characteristic points, and actually the number of the characteristic points is large in the running process of the train. The characteristic point 1 is an initial characteristic point, and the characteristic point 1 is a train starting point.
The line data structure is as follows:
Line：A-B
Section：section1
feature 1: 2 (points in general, corresponding to characteristic points 2 in the figure)
P _ ABB: 0 (0: general points; 1: station; 2: tunnel; 3: bridge; 4: grassland)
D _ Start: 100 (100 meters distance from the Seciton1 starting point)
Feature points { 1111222233334345554466778889923454555550032233333456756786970. } image matching Feature points (where the data represents Feature point image data, as opposed to specific image data, and is only exemplary listed here)
D _ LFP: 0 (indicating no link property, the feature point is not linked by the previous feature point)
D _ NFP: 500 (distance 500 m from the next characteristic point)
D _ NFP error: 5 (error distance from the next feature +/-5 meters)
D _ NSP 1500 (distance 1500 m from the next two characteristic points)
D _ NSP error: 10 (distance error +/-10 m from the next two characteristic points)
PS _ Spc: 2 (next characteristic point filter, 2 for tunnel background)
Focus: 2 (next characteristic point 2 times focal length)
Weather: 1 (current section weather conditions: 1-rain, 2-fog, 3-sunny, 4-cloudy)
Light: 1 (currently: 1-day, 2-evening, 3-night)
Feature 2: 3 (corresponding to the feature point 3 in the figure) feature point attribute (special point)
P _ ABB: 2 (0: general points; 1: station; 2: tunnel; 3: bridge; 4. grassland)
D _ Start: 600 (distance 600 meters from the starting point of the section)
Feature points { } image matching Feature points
D _ LFP: 500 (distance 500 m from the last characteristic point)
D _ NFP: 1000 (distance 1000 m from the next characteristic point)
D _ NFP error: 10 (distance error +/-10 meters from the next characteristic point)
D _ NSP: 1500 (distance from the next two feature points 5)
D _ NSP error: 10 (distance error +/-10 m from the next two characteristic points)
PS _ Spc: 4 (next characteristic point filter: 4 represents: grassland background)
Focus: 2 (next characteristic point 2 times focal length)
Weather: 1 (current section weather conditions: 1-rain, 2-fog, 3-sunny, 4-cloudy)
Light: 1 (currently: 1-day, 2-evening, 3-night)
Section2：
………………………………………………………………………….
END
When the train acquires the characteristics of the characteristic point 2, the similarity is larger than 75% by comparing with the Feature points data, the current position is determined successfully by comparing, and different image shooting conditions are called according to the terrain where the train is located, the weather, the light and other factors at the time to acquire a more optimized characteristic point. Data in the electronic map data structure are displayed exemplarily, are not constant values, and can be adjusted correspondingly according to actual conditions.
Although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (8)
1. The method for constructing the electronic map data structure based on image matching is characterized in that,
the construction method comprises the following steps:
selecting a train running section, and storing section information of the section in a data form;
determining the attribute of the feature point, and formulating a corresponding additional attribute according to the attribute of the feature point; the attribute of the characteristic point comprises a general point and a special point, and the additional attribute comprises that a reminding setting is additionally added when the special point data is stored;
storing the link relation between the characteristic points and storing the distance error range between the characteristic points;
storing the specific forms of the focal length factor, the weather factor, the light factor and the filter factor in a corresponding digital form;
and coding the stored information in a data form to form an electronic map data structure.
2. The method for constructing an electronic map data structure based on image matching according to claim 1,
the link relation includes establishing a link relation of an actual distance and an error distance between the feature point and the next feature point.
3. The method for constructing an electronic map data structure based on image matching according to claim 1,
the general points are characteristic points on normal terrain, and the normal terrain comprises cities; the special points represent characteristic points in special terrain including tunnels, stations, bridges and grasslands.
4. The method for constructing an electronic map data structure based on image matching according to claim 1,
the weather factors include rainy days, foggy days, snowy days, cloudy days and sunny days, and the light factors include daytime light, highlight light, night light and evening light.
5. The method for constructing an electronic map data structure based on image matching according to claim 1,
the filter factors comprise a grassland background, a tunnel background and a forest background; the focal length factor includes a focal length specific multiple.
6. The system for constructing the electronic map data structure based on image matching is characterized in that,
the system comprises a road section information storage unit, a characteristic point unit, an external factor storage unit and a data structure coding unit;
wherein the content of the first and second substances,
the road section information storage unit is used for storing the road section information in a data form;
the characteristic point unit is used for storing characteristic point attribute information and additional attribute information in a data form, the characteristic point attribute comprises a general point and a special point, and the additional attribute comprises that a reminding setting is additionally added when the special point data is stored;
the characteristic point unit is also used for storing the link relation among the characteristic points and the distance error among the characteristic points;
the external factor unit is used for storing the information of focal length, weather, light and filter factors;
and the data structure coding unit is used for coding the data information stored in the road section information storage unit, the characteristic point unit and the external factor storage unit to form an electronic map data structure.
7. The system for constructing an electronic map data structure based on image matching according to claim 6,
before the feature point data of the feature point unit is stored in a transformed mode, the feature point image is subjected to data extraction, and the extracted image data is stored.
8. The system for constructing an electronic map data structure based on image matching according to claim 6,
the information stored by the external factor unit is stored in a numerical value form, and the specific numerical value corresponds to the corresponding external factor condition.
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