CN116699644B - Marking reliability assessment method based on three-dimensional laser radar - Google Patents
Marking reliability assessment method based on three-dimensional laser radar Download PDFInfo
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- CN116699644B CN116699644B CN202310983274.6A CN202310983274A CN116699644B CN 116699644 B CN116699644 B CN 116699644B CN 202310983274 A CN202310983274 A CN 202310983274A CN 116699644 B CN116699644 B CN 116699644B
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- 238000000034 method Methods 0.000 title claims abstract description 8
- 238000005259 measurement Methods 0.000 claims abstract description 62
- 238000001914 filtration Methods 0.000 claims abstract description 13
- 238000011156 evaluation Methods 0.000 claims abstract description 11
- 238000002310 reflectometry Methods 0.000 claims description 6
- 238000013507 mapping Methods 0.000 claims description 4
- 230000009466 transformation Effects 0.000 claims description 3
- 230000007613 environmental effect Effects 0.000 abstract description 2
- 230000007547 defect Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000002708 enhancing effect Effects 0.000 description 1
- 230000005855 radiation Effects 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- 230000001502 supplementing effect Effects 0.000 description 1
Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/88—Lidar systems specially adapted for specific applications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/55—Specular reflectivity
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/20—Image enhancement or restoration by the use of local operators
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10028—Range image; Depth image; 3D point clouds
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Abstract
The invention discloses a marking reliability evaluation method based on a three-dimensional laser radar, which comprises the following steps: s1, performing comprehensive scanning by using a three-dimensional laser radar to obtain three-dimensional point cloud data of a marking line; s2, filtering the three-dimensional point cloud data of the marking, dividing the filtered three-dimensional point cloud data to obtain a plurality of measuring areas, and calculating the areas of the measuring areas to obtain the total surface area of the marking; s3, selecting a measurement area according to requirements, and acquiring DRI data pairs of each point in point cloud data in the measurement area; s4, calculating the luminous coefficient intensity of the measurement area based on DRI data pairs of each point in the point cloud data in the measurement area and combining the total surface area of the marked line; s5, based on the luminous coefficient intensity of the measuring area, finishing evaluation of the reliability of the marking; the method solves the problems of high measurement difficulty and easy influence of external environmental factors on the measurement result in the prior art.
Description
Technical Field
The invention relates to the technical field of laser radar measurement, in particular to a marking reliability evaluation method based on a three-dimensional laser radar.
Background
The retroreflection coefficient is the reciprocal of the ratio of reflected light intensity to incident light intensity, reflects the quality of the reflection performance of the material, and is an important parameter of the optical property of the material; in the field of road traffic, retroreflective coefficients are widely used for condition assessment and traffic safety management of pavement markings.
The traditional marking reliability evaluation method is to measure through the retroreflection coefficient, usually irradiate the marking by using a light source, and then measure the reflected light intensity and the incident light intensity, but the method has various defects such as high measurement difficulty, low measurement precision, and the measurement result is easily influenced by external environment factors.
Disclosure of Invention
Aiming at the defects in the prior art, the marking reliability evaluation method based on the three-dimensional laser radar solves the problems that the existing method is high in measurement difficulty, low in measurement precision and easy to influence a measurement result by external environmental factors.
In order to achieve the aim of the invention, the invention adopts the following technical scheme: the marking reliability evaluation method based on the three-dimensional laser radar comprises the following steps:
s1, performing comprehensive scanning by using a three-dimensional laser radar to obtain three-dimensional point cloud data of a marking line;
s2, filtering the three-dimensional point cloud data of the marking, dividing the filtered three-dimensional point cloud data to obtain a plurality of measuring areas, and calculating the areas of the measuring areas to obtain the total surface area of the marking;
s3, selecting a measurement area according to requirements, and acquiring DRI data pairs of each point in point cloud data in the measurement area;
s4, calculating the luminous coefficient intensity of the measurement area based on DRI data pairs of each point in the point cloud data in the measurement area and combining the total surface area of the marked line;
s5, based on the luminous coefficient intensity of the measuring area, the reliability assessment of the marked line is completed.
Further: the step S2 comprises the following sub-steps:
s21, filtering the three-dimensional point cloud data of the marked line, and removing noise points and irrelevant points to obtain filtered three-dimensional point cloud data;
s22, dividing the three-dimensional point cloud data after filtering by adopting a K-means algorithm to obtain K measurement areas;
k is the number of measurement areas obtained by dividing the three-dimensional point cloud data after filtering;
s23, calculating the surface areas of the k measuring areas respectively and adding the surface areas to obtain the total surface area of the marked line.
Further: the step S3 comprises the following sub-steps:
s31, selecting a measurement area according to requirements, and mapping point cloud data of the measurement area to a laser radar coordinate system through coordinate system transformation;
s32, calculating the distance between each mapped point in the measurement area and the laser radar position by adopting a Euclidean distance mode;
s33, taking the signal intensity received by the laser radar as reflection intensity, and acquiring a reflection intensity value of each point mapped in the measurement area;
s34, obtaining DRI data pairs of each point in the point cloud data in the measurement area according to the distance between each point mapped in the measurement area and the laser radar position and the reflection intensity value of each point mapped in the measurement area;
wherein the DRI data pair is a data pair of the distance between each point and the laser radar position after mapping-the reflection intensity value of each point.
Further: the step S4 includes the following sub-steps:
s41, fitting the DRI data pair to obtain a reflectivity equation, and calculating the retroreflection coefficient of the measurement area through the reflectivity equation;
s42, calculating the luminous coefficient intensity of the measurement area according to the retroreflection coefficient of the measurement area.
Further: in the step S41, the formula for calculating the retroreflection coefficient is:
C = ∫(R(I)/I) dI
wherein R (-) is the reflectance equation, I is the incident light intensity, and C is the retroreflection coefficient.
Further: in the step S42, the formula for calculating the luminous coefficient intensity is:
F=C×I×S
where F is the luminous intensity coefficient and S is the total surface area of the reticle.
Further: the step S5 includes the following sub-steps:
s51, normalizing the ratio of the luminous coefficient intensity to the surface area of each measuring area, and taking the normalized ratio of the luminous coefficient intensity to the surface area and the retroreflection coefficient as the marking characteristics of each measuring area;
s52, the marking characteristics of each measuring area are obtained regularly, and the marking reliability is evaluated through the change trend of the marking characteristics of each measuring area.
The beneficial effects of the above-mentioned further scheme are: the ratio of the luminous intensity coefficient to the surface area is normalized, and the unit is candela per lux per square meter, so that the change and difference comparison of different marked lines are facilitated.
Drawings
FIG. 1 is a flow chart of a reticle reliability evaluation method according to the present invention.
Detailed Description
0013. The following description of the embodiments of the present invention is provided to facilitate understanding of the present invention by those skilled in the art, but it should be understood that the present invention is not limited to the scope of the embodiments, and all the inventions which make use of the inventive concept are protected by the spirit and scope of the present invention as defined and defined in the appended claims to those skilled in the art.
0014. As shown in fig. 1, in one embodiment of the present invention, there is provided a reticle reliability evaluation method based on a three-dimensional lidar, including the steps of:
s1, performing comprehensive scanning by using a three-dimensional laser radar to obtain three-dimensional point cloud data of a marking line;
s2, filtering the three-dimensional point cloud data of the marking, dividing the filtered three-dimensional point cloud data to obtain a plurality of measuring areas, and calculating the areas of the measuring areas to obtain the total surface area of the marking;
s3, selecting a measurement area according to requirements, and acquiring DRI data pairs of each point in point cloud data in the measurement area;
s4, calculating the luminous coefficient intensity of the measurement area based on DRI data pairs of each point in the point cloud data in the measurement area and combining the total surface area of the marked line;
s5, based on the luminous coefficient intensity of the measuring area, the reliability assessment of the marked line is completed.
0015. In this embodiment, the step S2 includes the following sub-steps:
s21, filtering the three-dimensional point cloud data of the marked line, and removing noise points and irrelevant points to obtain filtered three-dimensional point cloud data;
s22, dividing the three-dimensional point cloud data after filtering by adopting a K-means algorithm to obtain K measurement areas;
k is the number of measurement areas obtained by dividing the three-dimensional point cloud data after filtering;
s23, calculating the surface areas of the k measuring areas respectively and adding the surface areas to obtain the total surface area of the marked line.
0016. In this embodiment, the step S3 includes the following sub-steps:
s31, selecting a measurement area according to requirements, and mapping point cloud data of the measurement area to a laser radar coordinate system through coordinate system transformation;
s32, calculating the distance between each mapped point in the measurement area and the laser radar position by adopting a Euclidean distance mode;
s33, taking the signal intensity received by the laser radar as reflection intensity, and acquiring a reflection intensity value of each point mapped in the measurement area;
s34, obtaining DRI data pairs of each point in the point cloud data in the measurement area according to the distance between each point mapped in the measurement area and the laser radar position and the reflection intensity value of each point mapped in the measurement area;
wherein the DRI data pair is a data pair of the distance between each point and the laser radar position after mapping-the reflection intensity value of each point.
0017. In this embodiment, the step S4 includes the following sub-steps:
s41, fitting the DRI data pair to obtain a reflectivity equation, and calculating the retroreflection coefficient of the measurement area through the reflectivity equation;
in the step S41, the formula for calculating the retroreflection coefficient is:
C = ∫(R(I)/I) dI
wherein R (-) is a reflectance equation, I is the intensity of incident light, and C is the retroreflection coefficient;
s42, calculating the luminous coefficient intensity of the measurement area according to the retroreflection coefficient of the measurement area;
in the step S42, the formula for calculating the luminous coefficient intensity is:
F=C×I×S
where F is the luminous intensity coefficient and S is the total surface area of the reticle.
0018. In this embodiment, the step S5 includes the following sub-steps:
s51, normalizing the ratio of the luminous coefficient intensity to the surface area of each measuring area, and taking the normalized ratio of the luminous coefficient intensity to the surface area and the retroreflection coefficient as the marking characteristics of each measuring area;
the normalized formula is:
wherein I is n The normalized luminous intensity coefficient;Iis the original luminous intensity coefficient; s is the total area of the marked lines; k is the ratio of the light radiation brightness to the illuminance, and can be calculated by photometric parameters.
0019.S52. periodically obtaining the marking characteristics of each measuring area, and finishing the evaluation of marking reliability through the variation trend of the marking characteristics of each measuring area.
0020. The ratio of the light coefficient intensity to the surface area is used for describing the optical characteristics and the luminous characteristics of the region, effectively supplementing the single retroreflection coefficient and enhancing the descriptive property.
0021. Statistical methods can be used to find outliers when evaluating the retroreflection coefficient of each measurement region. In general, the mean and standard deviation of the retroreflection coefficient of each region can be calculated, and then the range of outliers can be determined by adding or subtracting a number of standard deviations from the mean. In general, data points with a retroreflection coefficient exceeding the mean plus or minus 3 standard deviations can be considered outliers. When an area is found to have an abnormally high or low retroreflection coefficient, the area can be further finely scanned to find a specific problem location. Fine scanning may be performed by increasing the scanning density or adjusting parameters of the lidar.
0022. In the description of the present invention, it should be understood that the terms "center," "thickness," "upper," "lower," "horizontal," "top," "bottom," "inner," "outer," "radial," and the like indicate or are based on the orientation or positional relationship shown in the drawings, merely to facilitate description of the present invention and to simplify the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be configured and operated in a particular orientation, and thus should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be interpreted as indicating or implying a relative importance or number of technical features indicated. Thus, a feature defined as "first," "second," "third," or the like, may explicitly or implicitly include one or more such feature.
Claims (3)
1. The marking reliability evaluation method based on the three-dimensional laser radar is characterized by comprising the following steps of: the method comprises the following steps:
s1, performing comprehensive scanning by using a three-dimensional laser radar to obtain three-dimensional point cloud data of a marking line;
s2, filtering the three-dimensional point cloud data of the marking, dividing the filtered three-dimensional point cloud data to obtain a plurality of measuring areas, and calculating the areas of the measuring areas to obtain the total surface area of the marking;
s3, selecting a measurement area according to requirements, and acquiring DRI data pairs of each point in point cloud data in the measurement area;
wherein the DRI data pair is the data pair of the distance between each point and the laser radar position after mapping and the reflection intensity value of each point;
s4, calculating a luminous intensity coefficient of the measurement area based on DRI data pairs of each point in the point cloud data in the measurement area and combining the total surface area of the marked line;
the step S4 includes the following sub-steps:
s41, fitting the DRI data pair to obtain a reflectivity equation, and calculating the retroreflection coefficient of the measurement area through the reflectivity equation;
in the step S41, the formula for calculating the retroreflection coefficient is:
C = ∫(R(I)/I) dI
wherein R (-) is a reflectance equation, I is the intensity of incident light, and C is the retroreflection coefficient;
s42, calculating the luminous intensity coefficient of the measurement area according to the retroreflection coefficient of the measurement area;
in the step S42, the formula for calculating the luminous intensity coefficient is:
F=C×I×S
wherein F is a luminous intensity coefficient, S is the total surface area of the marking;
s5, based on the luminous intensity coefficient of the measuring area, finishing evaluation of the reliability of the marking;
the step S5 includes the following sub-steps:
s51, normalizing the ratio of the luminous intensity coefficient to the surface area of each measuring area, and taking the normalized ratio of the luminous intensity coefficient to the surface area and the retroreflection coefficient as the marking characteristics of each measuring area;
s52, the marking characteristics of each measuring area are obtained regularly, and the marking reliability is evaluated through the change trend of the marking characteristics of each measuring area.
2. The method for evaluating the reliability of a reticle based on a three-dimensional laser radar according to claim 1, wherein the step S2 comprises the following sub-steps:
s21, filtering the three-dimensional point cloud data of the marked line, and removing noise points and irrelevant points to obtain filtered three-dimensional point cloud data;
s22, dividing the three-dimensional point cloud data after filtering by adopting a K-means algorithm to obtain K measurement areas;
k is the number of measurement areas obtained by dividing the three-dimensional point cloud data after filtering;
s23, calculating the surface areas of the k measuring areas respectively and adding the surface areas to obtain the total surface area of the marked line.
3. The method for evaluating the reliability of a reticle based on a three-dimensional laser radar according to claim 1, wherein the step S3 comprises the following sub-steps:
s31, selecting a measurement area according to requirements, and mapping point cloud data of the measurement area to a laser radar coordinate system through coordinate system transformation;
s32, calculating the distance between each mapped point in the measurement area and the laser radar position by adopting a Euclidean distance mode;
s33, taking the signal intensity received by the laser radar as reflection intensity, and acquiring a reflection intensity value of each point mapped in the measurement area;
s34, obtaining DRI data pairs of each point in the point cloud data in the measurement area according to the distance between each point mapped in the measurement area and the laser radar position and the reflection intensity value of each point mapped in the measurement area;
wherein the DRI data pair is a data pair of the distance between each point and the laser radar position after mapping-the reflection intensity value of each point.
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| CN116699644A (en) | 2023-09-05 |
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