CN108645342B - Road width extraction method based on road track and high-resolution image - Google Patents
Road width extraction method based on road track and high-resolution image Download PDFInfo
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- G01B11/00—Measuring arrangements characterised by the use of optical techniques
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Abstract
The invention discloses a road width extraction method based on a road track and a high-resolution image, which comprises the following implementation steps of carrying out edge detection on high-resolution remote sensing data, vectorizing a detection result, generating vector lines, sequentially establishing a buffer area based on adjacent nodes on the road track, cutting the vector lines generated in the previous step, sequentially calculating the length and the slope of the vector lines, taking two vector lines with the length and the slope closest to the road track as the edges of a road, and obtaining the width of the road by utilizing a perpendicular bisector and the maximum probability statistics. The method combines the existing road vector track with the on-site high-resolution image, realizes the automatic screening of the edge through two indexes of length and slope, improves the extraction precision of the road edge, reduces the influence caused by width extraction errors due to the shielding of objects around the road, ensures that the statistical rule accords with the traffic service standard, and has strong applicability.
Description
Technical Field
The invention relates to the technical field of road width extraction, in particular to a road width extraction method based on a road track and a high-resolution image.
Background
The road width refers to the width of a roadway and a sidewalk, and does not include the greening width outside the sidewalk. The road width is determined by the traffic volume, and the road grades are divided into five grades of an expressway, a first-grade road, a second-grade road, a third-grade road and a fourth-grade road according to the use task, the function and the flow of the road. The road width is an important attribute for describing a road, and is also an important index for describing a road grade. The road width not only influences the trip experience of the public, but also influences the trip safety of the public. Therefore, it is necessary to develop an accurate estimation for the width value of the road.
At present, the research of estimating the road width by using the high-resolution remote sensing image is less, the road width is mostly obtained by manual on-site measurement or manual measurement of the high-resolution remote sensing image, a large amount of manpower and material resources are needed, the road width on an area is difficult to obtain, and due to artificial subjective factors, measurement errors are easy to generate. In addition, in the research process of road extraction, some scholars extract road surfaces, further extract the center lines of roads or extract the levels of road widths, and do not research specific width values of roads.
Disclosure of Invention
Based on the technical problems in the background art, the invention provides a road width extraction method based on a road track and a high-resolution image. The method can be used as a tool for extracting the road width in the process of general survey and verification of the road attribute, the efficiency of the general survey and verification work is improved, and the verification of the road construction progress and the extraction of road disasters can be assisted.
The invention provides a road width extraction method based on a road track and a high-resolution image, which comprises the following implementation steps of:
s1: carrying out edge detection on the high-resolution remote sensing data;
s2: vectorizing the generated detection result to generate a vector line;
s3: sequentially establishing buffer areas based on adjacent nodes on the road track, and cutting vector lines generated in the previous step;
s4: sequentially calculating the length and the slope of the vector lines, wherein the two vector lines with the length and the slope closest to the road track are used as the edges of the road;
s5: calculating the length of a line intersecting the edge of the road based on the perpendicular bisector of the track of the road;
s6: according to the characteristic that the width of the road section is uniform, the length value with the highest occurrence probability is used as the width value of the road section.
Preferably, in S1, the edge detection is performed on the high-resolution remote sensing image, and the main purpose of this step is to extract edge lines and provide potential edges for road width estimation.
Preferably, in S2, the vectorization of the edge detection result, that is, the grid data is converted into vector line data of the same geographical projection, and the purpose of this step is that the vector data is easier to perform length and slope calculation relative to the grid data.
Preferably, in S3, a buffer area with a certain width is established by using neighboring nodes on an existing road, the width of the buffer area is also determined by the planar distance between the road track and the road on the high-resolution remote sensing image, a plurality of buffer areas may be generated on one road segment, and vector edges are cut by sequentially using the buffer areas.
Preferably, in S4, traversing each vector line in the buffer area, calculating the length of the vector line, comparing the length with the length of the road between corresponding nodes of the existing road, taking the three vector lines with the closest length as candidate routes, then accumulating the lengths of the candidate vector lines with the slope of the road track close to the slope of the node, determining the ratio of the accumulated value to the length of the road track node according to the situation of the edge, taking the vector line with the ratio greater than the ratio as the edge of the road, wherein the ratio range is generally between 40% and 80%, and the preferred value is 60%.
Preferably, in S5, after the edge of the road is obtained, a perpendicular bisector of the road may be obtained by using two adjacent nodes of the road track, where a midpoint of the two adjacent nodes extends along the perpendicular bisector, and a distance between the midpoint of the two adjacent nodes and an intersection of the grid where the edge of the road is located is the width of the road.
Preferably, in S6, the road segment is made to obtain a plurality of estimated road segment widths, the width estimated values fall within a histogram, and an average value of the interval estimated values with the highest frequency in the histogram is used as the width value of the road segment.
The beneficial effects of the invention are as follows:
1. according to the method, a small buffer area is formed by adjacent nodes of the road track, vector edges are cut, two parameters of length and slope are used as judgment indexes, edge screening is realized through a screening rule, the extraction precision of the road edges is improved, the extraction of the road width is more accurate, and the edge screening rule is suitable for the condition that the road track is overlapped with the road on the remote sensing image and is also suitable for the condition that the road track is offset relative to the road on the remote sensing image;
2. the method utilizes the characteristic that the width of a road section in the road is uniform, the width values obtained by the perpendicular bisectors of the adjacent nodes are placed in the histogram, the average value of the width values in the range with the highest frequency in the histogram is used as the width value of the road section, the method reduces the influence caused by width extraction errors due to shielding of objects around the road, the statistical rules meet the traffic service specifications, and the method has strong applicability.
Drawings
Fig. 1 is a road width extraction flow chart of a road width extraction method based on a road track and a high-resolution image according to the present invention;
FIG. 2 is a schematic diagram of an edge detection result of a road width extraction method based on a road track and a high-resolution image according to the present invention;
FIG. 3 is a simplified front and rear schematic view of a vector edge of a road width extraction method based on a road track and a high-resolution image according to the present invention;
FIG. 4 is a schematic diagram of a road track generation buffer according to the road width extraction method based on a road track and a high-resolution image of the present invention;
FIG. 5 is a schematic diagram of road edge extraction parameters of a road width extraction method based on a road track and a high-resolution image according to the present invention;
FIG. 6 is a road edge extraction flowchart of a road width extraction method based on a road track and a high-resolution image according to the present invention;
FIG. 7 is a road edge screening result diagram of a road width extraction method based on road tracks and high-resolution images according to the present invention;
FIG. 8 is a road width extraction result histogram of a road width extraction method based on road tracks and high-resolution images according to the present invention;
fig. 9 is a schematic diagram of road track and high-resolution image experimental data of a road width extraction method based on a road track and a high-resolution image according to the present invention.
Detailed Description
The embodiments of the present invention will be described clearly and completely with reference to the drawings in the following, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
Referring to fig. 1 to 9, a road width extraction method based on a road track and a high-resolution image includes the following steps:
and carrying out edge detection on the high-resolution image.
The remote sensing image is subjected to edge detection, in this example, edge detection is performed by using a Canny algorithm.
And establishing a buffer area based on the existing road track, and cutting an edge detection result.
1) The method comprises the steps of establishing a buffer area based on an existing road, wherein the width (W) of the buffer area is determined by the plane distance between a road track and a road on a high-resolution remote sensing image, and the buffer area generally comprises the road on the remote sensing image corresponding to the road. For example the width of the buffer zone is 30 meters.
2) And utilizing the generated buffer area to cut the edge detection result. As shown in fig. 2.
Vectorizing the generated edge detection result.
1) And vectorizing the generated raster image data.
2) And simplifying vectorization results. The purpose of this step is to remove the aliasing present in the vector line and smooth the line, as shown in fig. 3.
And sequentially establishing buffer areas based on adjacent nodes on the road track, and cutting the vector lines generated in the previous step.
1) And sequentially generating buffer areas with the width of W by the node sections formed by adjacent nodes of the road track. Because the distances among the nodes are inconsistent and the road has the characteristic of consistent width, the adjacent nodes with the distance between the nodes being less than 3 meters do not generate buffer areas so as to reduce the computation amount.
2) And the generated buffer area clips the vector line generated in the step 3. The schematic is shown in FIG. 4.
And sequentially calculating the length and the slope of the vector lines in the buffer area, wherein the two vector lines with the length and the slope closest to the original road track are used as the edges of the road. The schematic diagram of the parameters of road edge extraction is shown in fig. 5. The flowchart of the road edge extraction is shown in fig. 6.
1) The length of the road track is calculated. The length is calculated as follows, in meters. Wherein, the 1 st i is the ith road section, and the 2 nd i is the ith vector section of the ith road section.
2) The length of the vector line in the buffer is traversed. And selecting three vector lines with the lengths closest to the length of the road track. Each vector line in the buffer, with L(i，i)It is shown that the 1 st i is the ith node end of a road segment, and the 2 nd i is the ith vector segment of the buffer. Assuming that the vector segment has m nodes, the length of each vector line is C(i，i)And (4) showing. C(i，i)Is calculated byThe formula is shown below.
3) The slope of the road track is calculated in degrees.
Slope frThe specific calculation formula of (i, i) is as follows:
fr(i，i)＝tan-1(kr(i，i))
4) and sequentially calculating the slopes of adjacent nodes in the three vector lines, accumulating the lengths of the nodes with the slope value less than 10 degrees different from the slope of the road track, and taking the vector line with the accumulated length value more than 60 percent of the track length as the edge of the route.
Slope f between vector line nodes(i，i)(j) The specific calculation formula of (2) is as follows:
f(i，i)＝tan-1(k(i，i)(j))
with the first node L of the first vector edge on the ith buffer(i，i)(1) (x, y) and a second node L(i，i)(2) (x, y) for example, the calculation formula of the length between nodes is as follows:
vector line L(i，i)The calculation formula of the node sum with the deviation of the slope of the known route track less than 10 degrees is as follows:
wherein n is a vector line L(i，i)To and fromThe number of road segments with a difference in track slope of less than 10 degrees.
If the sum of the lengths of the three vector lines with the slope difference of less than 10% from the known route is more than 60%, selecting the edge of the road with the smallest length difference as the node; if two of the three vector lines are smaller than or equal to 60%, selecting the two vector lines as the road edges of the node; if 2 or more routes in the three vector lines are less than 60%, the extraction of the route edges in the buffer area and the calculation of the road width are abandoned.
The road edge screening result graph is shown in fig. 7.
The length of the intersection with the road edge is calculated based on the perpendicular bisector of the road track.
1) After the edges L (i,1) and L (i,2) of the road are acquired, the vector edge lines are converted into a raster image.
2) By using two adjacent nodes p (i, i) and p (i, i +1) of the road track, the calculation formula of the perpendicular bisector of the road, the slope kz (i, i) and the intercept az (i, i) of the perpendicular bisector can be obtained as follows:
3) the middle points of two adjacent nodes extend towards two sides along the vertical line, and the distance between the middle points and the intersection point of the grids where the road edge is located is the width of the road. Assuming that the intersections of the extended lines with the road edges are X1(i) (X, y) and X2(i) (X, y), the calculation formula of the distance between the two points is:
and according to the characteristic that the width of the same road section is uniform, the width value falls in the histogram, and the average value of the interval values with the highest frequency in the histogram is used as the width value of the road section.
1) Through the 6-step calculation, an estimated value of the width of a plurality of road sections can be obtained for a certain road section.
2) And putting the width value of the road section into a histogram with the value range of 1.25-20.25 meters and the interval of 0.5 meters.
3) And selecting the average value of the interval values with the highest interval frequency as the width value of the road section. As shown in fig. 8.
FIG. 9 is a diagram illustrating exemplary effects of road track data and high-resolution images used in the present invention.
The road width extraction results of the present invention are shown in the following table:
the 'image visual interpretation result' in the table is a result measured from the remote sensing image by manually utilizing related professional software; the approximate result is the normalized representation of the extraction result, and the result shows that the accuracy of the error value within 1m can reach 91.67 percent, and the accuracy requirement of practical application can be met.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (7)
1. A road width extraction method based on a road track and a high-resolution image is characterized by comprising the following implementation steps:
s1: carrying out edge detection on the high-resolution remote sensing data;
s2: vectorizing the generated detection result to generate a vector line;
s3: sequentially establishing buffer areas based on adjacent nodes on the road track, and cutting vector lines generated in the previous step;
s4: calculating the length and the slope of the vector line in sequence, wherein the two vector lines with the length and the slope closest to the road track are used as the edges of the road, and the method comprises the following steps: traversing each vector line in the buffer area, comparing the vector lines with the lengths of roads between nodes corresponding to the existing roads, taking three vector lines with the closest lengths as candidate routes, accumulating the lengths of the candidate vector lines with the node slopes close to the road track slopes, determining the ratio of the accumulated value to the lengths of the road track nodes according to the edge condition, taking the vector line with the ratio larger than the ratio as the edge of the road, wherein the ratio range is generally between 40 and 80 percent;
s5: calculating the length of a line intersecting the edge of the road based on the perpendicular bisector of the track of the road;
s6: according to the characteristic that the width of the road section is uniform, the length value with the highest occurrence probability is used as the width value of the road section.
2. The method for extracting road width based on road track and high resolution image as claimed in claim 1, wherein in S1, edge detection is performed on the high resolution remote sensing image, and the main purpose of this step is to extract edge lines to provide potential edges for road width estimation.
3. The method for extracting road width based on road track and high resolution image as claimed in claim 1, wherein in S2, the vectorization of edge detection results, that is, converting raster data into vector line data of the same geographical projection, is to make the vector data easier to perform length and slope calculation than the raster data.
4. The method for extracting road width based on road track and high-resolution image as claimed in claim 1, wherein in S3, a buffer area with a certain width is established by using the neighboring nodes on the existing road, the width of the buffer area is determined by the planar distance between the road track and the road on the high-resolution remote sensing image, a plurality of buffer areas can be generated on one road segment, and the vector edges are cut by sequentially using the buffer areas.
5. The method as claimed in claim 1, wherein the percentage of S4 is 60%.
6. The method as claimed in claim 1, wherein in S5, after the edge of the road is obtained, a perpendicular bisector of the road is obtained by using two adjacent nodes of the road track, and a distance between a midpoint of the two adjacent nodes and an intersection of the two adjacent nodes and a grid where the edge of the road is located is a distance between the midpoint of the two adjacent nodes and the intersection of the two adjacent nodes and the grid where the edge of the road is located.
7. The method as claimed in claim 1, wherein in step S6, the road segment is estimated to have a plurality of segment widths, the width estimates are located in a histogram, and the average of the second highest interval estimates in the histogram is used as the width of the road segment.
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