CN108801257A - A kind of localization method for indoor automatic parking - Google Patents
A kind of localization method for indoor automatic parking Download PDFInfo
- Publication number
- CN108801257A CN108801257A CN201810297034.XA CN201810297034A CN108801257A CN 108801257 A CN108801257 A CN 108801257A CN 201810297034 A CN201810297034 A CN 201810297034A CN 108801257 A CN108801257 A CN 108801257A
- Authority
- CN
- China
- Prior art keywords
- grid
- binary
- bit
- information
- section
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
- G01C21/206—Instruments for performing navigational calculations specially adapted for indoor navigation
Landscapes
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Automation & Control Theory (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Traffic Control Systems (AREA)
- Image Processing (AREA)
Abstract
The invention discloses a kind of localization methods for indoor automatic parking, include the following steps：(1) grid is sprayed on the road of parking lot indoors, grid uses binary coding；(2) by the corresponding sequence of binary digits typing GIS database of physical location；(3) camera shoots the photo of the grid on ground and uploads onto the server；(4) it identifies gridding information, reads sequence of binary digits；(5) vehicle physical location is inquired in GIS database according to output sequence of binary digits.Present invention incorporates computer vision, the technologies such as position encoded and location-based service, after position data is stored in database, by identifying that the grid finished obtains binary system id information, easy to use, positioning accuracy is higher, vehicle location can be accurately and reliably carried out indoors, had a wide range of application.
Description
Technical field
The present invention relates to vehicle parking method more particularly to a kind of localization methods for indoor automatic parking.
Background technology
With being constantly progressive for science and technology, indoor positioning technologies continue to develop, and have bluetooth indoor positioning technologies, infrared ray
Indoor positioning technologies, UWB indoor location technology, Zigbee indoor positioning technologies, WiFi indoor positioning technologies etc..But these
Technology is inconvenient for use, cannot meet the location requirement of automatic parking.Therefore indoor automatic parking be badly in need of a kind of stabilization and precision compared with
High and easy to use localization method.
Invention content
Goal of the invention：In view of the problems of the existing technology, the object of the present invention is to provide a kind of easy to use and positioning
The higher localization method for indoor automatic parking of precision.
Technical solution：A kind of localization method for indoor automatic parking includes the following steps：
(1) grid is sprayed on the road of parking lot indoors, grid uses binary coding；
(2) by the corresponding sequence of binary digits typing GIS database of physical location；
(3) camera shoots the photo of the grid on ground and uploads onto the server；
(4) it identifies gridding information, reads sequence of binary digits；
(5) vehicle physical location is inquired in GIS database according to output sequence of binary digits.
The step (1) includes following content：
(1.1) it is a meters of a meters of * to use n binary codings, n grid of main part, a sizing grid, then can be with table
Having a lot of social connections for showing is n*a=na meters, the road a length of 2 that can be indicatedn* a=2nA meters, denotable area is na*2nA=n2na2Square
Rice；
(1.2) grid sprays black-and-white two color, and black represents binary digit 1, and white represents binary digit 0；
(1.3) start bit, stop bit and check bit are set；Start bit is black, is set as " 1 ", and stop bit is white, if
It is set to " 0 "；Using even or odd check bit so that the number of " 1 " is always odd number or even number between start bit and stop bit；
(1.4) sequential encoding, the id information of each section from first to last are continuous.
The step (2) includes following content：
In GIS database, the binary system id information and their practical seat of its type of linear section and its both ends
Mark indicates：{S；ID1, (X1, Y1)；ID2,(X2,Y2)}；Circular arc section is with the two of its type, angle, central coordinate of circle and both ends
System id information and their actual coordinate indicate：{C；θ；(X0,Y0)；ID1, (X1, Y1)；ID2,(X2,Y2)}.
The step (4) includes following content：
(4.1) the colored grid image by camera shooting carries out gray processing processing, reduces data volume, reduces memory space
And image processing time；
(4.2) noise spot that introduces when using medium filtering removal shooting grid image, reduce noise to subsequent image at
The interference of reason；
(4.3) binaryzation is carried out to image, the algorithm pair being combined according to balanced and Otsu global thresholds using adaptive optical
Grid image carries out binaryzation, removes the influence of grid image uneven illumination；
(4.4) extract edge feature, calculate total length L, then the coordinate of ith sample point be (Li/ (n+3), a/2), i<
=n+3；
(4.5) it is sampled according to obtained coordinate pair sampled point, dark color is denoted as " 0 ", and light color is denoted as " 1 "；
(4.6) since start bit binary code word is exported to stop bit；No matter the positive and negative traveling of vehicle, first sampled point
With the last one sampled point inevitable one be " 0 ", one be " 1 "；If " 1 " exports binary code word from left to right in left end,
Cast out start bit, stop bit and check bit after verification and obtains an id information；" if 1 " in right end, export from right to left two into
Code word processed casts out start bit, stop bit and check bit and obtains an id information after verification.
The step (5) includes following content：
(5.1) according to the binary system id information detected, the ID is searched between the both ends ID in which section, then actual bit
It sets just on the section；
(5.2) according to the data in the practical section searched out, if { S；ID1, (X1, Y1)；ID2, (X2, Y2) }, i.e. road
Section is linear type, converts (ID-ID1) to decimal number A, converts (ID2-ID1) to decimal number B, then currently practical seat
It is designated as (A (X2-X1)/B, A (Y2-Y1)/B)；If section data are { C；θ；(X0,Y0)；ID1, (X1, Y1)；ID2,(X2,
Y2) }, then arc radius R=√ (X0-X1)2+(Y0-Y1)2, then currently practical coordinate be
Advantageous effect
Compared with prior art, the present invention has following marked improvement：Present invention incorporates computer visions, position encoded
, by identifying that the grid finished obtains binary system id information, make after position data deposit database with technologies such as location-based services
With convenient, positioning accuracy is higher, can accurately and reliably carry out vehicle location indoors, have a wide range of application.
Description of the drawings
Fig. 1 is the flow diagram of construction method of the present invention；
Fig. 2 is the schematic diagram of linear section grid；
Fig. 3 is the schematic diagram in circular arc section；
Fig. 4 is the schematic diagram for calculating sampled point.
Specific implementation mode
Technical scheme of the present invention is described in further detail with reference to embodiment and attached drawing.
As shown in Figure 1, a kind of localization method for indoor automatic parking, includes the following steps：
Step 1, sprays grid indoors on the road of parking lot, grid uses binary coding.It is compiled using 32 binary systems
Code, 32 grids of main part, a sizing grid is 25cm*25cm, then having a lot of social connections for can indicating is 32*0.25=8 meters, can
With the road indicated a length of 232* 0.25=230Rice, denotable area are 8*230=233Square metre, about 8590 square kilometres.Net
Lattice spray black-and-white two color, and black represents binary digit 1, and white represents binary digit 0.Start bit, stop bit and school are set
Test position.Start bit is black, is set as " 1 ", and stop bit is white, is set as " 0 ".Using even parity bit so that start bit and
The number of " 1 " is always even number between stop bit.Sequential encoding, the id information of each section from first to last are continuous.
Step 2, by the corresponding sequence of binary digits typing GIS database of physical location.In GIS database, straight line path
The binary system id information and their actual coordinate at its type of section and its both ends indicate.In this example, linear section
It is expressed as { S；ID1, (X1, Y1)；ID2,(X2,Y2)}；Circular arc section is with the two of its type, central coordinate of circle, angle and both ends
System id information and their actual coordinate indicate.In this example, circular arc section is expressed as { C；θ；(X0,Y0)；ID1,
(X1,Y1)；ID2,(X2,Y2)}.
Step 3, when vehicle drives into parking garage, the photo of the grid on vehicle-mounted camera shooting ground simultaneously uploads to
Server；
Step 4 identifies gridding information, reads sequence of binary digits.The color of each pixel in coloured image have R,
G, tri- components of B determine, and each component has 255 values desirable, and such a pixel can have ten thousand (255*255* more than 1600
255) variation range of color.And the variation range of one pixel of gray level image only has 255 kinds, but gray level image is retouched
State distribution and the feature of the entirety that entire image is still reflected as coloured image and the coloration and brightness degree of part.It will
The colored grid image of camera shooting carries out gray processing processing, reduces data volume, reduces memory space and image processing time.
Some sampling window takes out odd number number and carries out ascending or descending order arrangement from image, the value of each point after sequence count flat
It calculates, the intermediate value after calculating replaces that value to be processed, allows the pixel value of surrounding close to actual value, realizes in image
Value filtering, removal shoot the noise spot introduced when grid image, reduce the interference that noise handles subsequent image.Image is carried out
Binaryzation carries out binaryzation, removal according to the algorithm that balanced and Otsu global thresholds are combined using adaptive optical to grid image
The influence of grid image uneven illumination.The flow of wherein Otsu algorithms is as follows.If image includes L gray level (0,1 ..., L-1),
The pixel points that gray value is i are Ni, and the total pixel points of image are N=N0+N1+...+N (L-1).Gray value is the point of i
General be：Entire image is divided into two class of dark space c1 and clear zone c2 by P (i)=N (i)/N. thresholdings t, then inter-class variance σ is the letter of t
Number：In σ=a1*a2 (u1-u2) ^2 (2) formula, aj is the ratio between area and image gross area of class cj, a1=sum (P (i)) i->t,
A2=1-a1；Uj is the mean value of class cj, u1=sum (i*P (i))/a1 0->T, u2=sum (i*P (i))/a2, t+1->L-1 should
Method selection optimum thresholding t^ keeps inter-class variance maximum, i.e.,：Enable Δ u=u1-u2, σ b=max { a1 (t) * a2 (t) Δs u^2 }.Extraction
The edge feature of image extracts grid from whole image, then calculates grid total length L, then ith sample point
Coordinate is (0.25/2, Li/34).The grid image after binaryzation is sampled according to obtained sample point coordinate, dark color note
For " 0 ", light color is denoted as " 1 ".Since start bit binary code word is exported to stop bit.No matter the positive and negative traveling of vehicle, first
Sampled point and inevitable one of the last one sampled point are " 0 ", and one is " 1 "." if 1 " in left end, export from left to right two into
Code word processed casts out start bit, stop bit and check bit and obtains an id information after verification；If " 1 " is in right end, defeated from right to left
Go out binary code word, start bit, stop bit and check bit are cast out after verification and obtains an id information.
Step 5 inquires vehicle physical location according to output sequence of binary digits in GIS database.According to detection
The binary system id information arrived searches for the ID between the both ends ID in which section, then physical location is just on the section.In this reality
In example, it is assumed that the ID detected is (01000000000000000000000000000000), if the practical section searched out
Data are { S；ID1, (X1, Y1)；ID2, (X2, Y2) }, i.e., section is linear type, converts (ID-ID1) to decimal number 2, will
(ID2-ID1) it is converted into decimal number 11, then currently practical coordinate is (2 (X2-X1)/11,2 (Y2-Y1)/11)；If section number
According to for { C；θ；(X0,Y0)；ID1, (X1, Y1)；ID2, (X2, Y2) }, i.e., section is arc-shaped, enables arc radius R=√ (X0-
X1)2+(Y0-Y1)2, then currently practical coordinate be
Claims (5)
1. a kind of localization method for indoor automatic parking, which is characterized in that include the following steps：
(1) grid is sprayed on the road of parking lot indoors, grid uses binary coding；
(2) by the corresponding sequence of binary digits typing GIS database of physical location；
(3) camera shoots the photo of the grid on ground and uploads onto the server；
(4) it identifies gridding information, reads sequence of binary digits；
(5) vehicle physical location is inquired in GIS database according to output sequence of binary digits.
2. the localization method according to claim 1 for indoor automatic parking, it is characterised in that：Step (1) packet
Include following content：
(1.1) n binary codings are used, n grid of main part, a sizing grid is a meters of a meters of *, then can indicate
It is n*a=na meters to have a lot of social connections, the road a length of 2 that can be indicatedn* a=2nA meters, denotable area is na*2nA=n2na2Square metre；
(1.2) grid sprays black-and-white two color, and black represents binary digit 1, and white represents binary digit 0；
(1.3) start bit, stop bit and check bit are set；Start bit is black, is set as " 1 ", and stop bit is white, is set as
"0"；Using even or odd check bit so that the number of " 1 " is always odd number or even number between start bit and stop bit；
(1.4) sequential encoding, the id information of each section from first to last are continuous.
3. the localization method according to claim 2 for indoor automatic parking, it is characterised in that：Step (2) packet
Include following content：
In GIS database, the binary system id information and their actual coordinate table of its type of linear section and its both ends
Show：{S；ID1, (X1, Y1)；ID2,(X2,Y2)}；Its type of circular arc section, angle, central coordinate of circle and the binary system at both ends
Id information and their actual coordinate indicate：{C；θ；(X0,Y0)；ID1, (X1, Y1)；ID2,(X2,Y2)}.
4. the according to claim 3 kind of localization method for indoor automatic parking, it is characterised in that：The step (4)
Including following content：
(4.1) the colored grid image by camera shooting carries out gray processing processing, reduces data volume, reduces memory space and figure
As processing time；
(4.2) noise spot introduced when medium filtering removal shooting grid image is used, reduces what noise handled subsequent image
Interference；
(4.3) binaryzation is carried out to image, using adaptive optical according to the balanced algorithm being combined with Otsu global thresholds to grid
Image carries out binaryzation, removes the influence of grid image uneven illumination；
(4.4) extract edge feature, calculate total length L, then the coordinate of ith sample point be (Li/ (n+3), a/2), i<=n+
3；
(4.5) it is sampled according to obtained coordinate pair sampled point, dark color is denoted as " 0 ", and light color is denoted as " 1 "；
(4.6) since start bit binary code word is exported to stop bit；No matter the positive and negative traveling of vehicle, first sampled point and most
Inevitable one of the latter sampled point be " 0 ", one be " 1 "；If " 1 " exports binary code word from left to right in left end, verification
After cast out start bit, stop bit and check bit and obtain an id information；If " 1 " exports binary code from right to left in right end
Word casts out start bit, stop bit and check bit and obtains an id information after verification.
5. a kind of localization method for indoor automatic parking according to claim 4, it is characterised in that：The step
(5) include following content：
(5.1) according to the binary system id information that detects, the ID is searched between the both ends ID in which section, then physical location is just
On the section；
(5.2) according to the data in the practical section searched out, if { S；ID1, (X1, Y1)；ID2, (X2, Y2) }, i.e., section is
Linear type, converts (ID-ID1) to decimal number A, converts (ID2-ID1) to decimal number B, then currently practical coordinate is
(A(X2-X1)/B,A(Y2-Y1)/B)；If section data are { C；θ；(X0,Y0)；ID1, (X1, Y1)；ID2, (X2, Y2) }, then
Arc radius R=√ (X0-X1)2+(Y0-Y1)2, then currently practical coordinate be
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810297034.XA CN108801257B (en) | 2018-04-04 | 2018-04-04 | Positioning method for indoor automatic parking |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810297034.XA CN108801257B (en) | 2018-04-04 | 2018-04-04 | Positioning method for indoor automatic parking |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108801257A true CN108801257A (en) | 2018-11-13 |
| CN108801257B CN108801257B (en) | 2021-05-11 |
Family
ID=64094843
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810297034.XA Active CN108801257B (en) | 2018-04-04 | 2018-04-04 | Positioning method for indoor automatic parking |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108801257B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109532824A (en) * | 2018-12-19 | 2019-03-29 | 杭州湘滨电子科技有限公司 | A kind of curb recognition methods that level is parked |
| CN111161449A (en) * | 2020-01-07 | 2020-05-15 | 东南大学 | Vehicle large-scale parking lot interior positioning method based on automobile data recorder image |
| CN113435227A (en) * | 2020-03-23 | 2021-09-24 | 阿里巴巴集团控股有限公司 | Map generation and vehicle positioning method, system, device and storage medium |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030060970A1 (en) * | 2001-09-27 | 2003-03-27 | Siemens Information And Communication Mobile Llc | Method and apparatus for defining location coordinates |
| US20060092016A1 (en) * | 2004-10-20 | 2006-05-04 | Modes Jerold R | Systems, methods and devices for area-based localization |
| CN1996289A (en) * | 2006-12-26 | 2007-07-11 | 董崇军 | Searching and positioning method using electronic map |
| CN102479214A (en) * | 2010-11-30 | 2012-05-30 | 余政 | Positioning method and positioning system based on bar code identification technology and GIS (Geographic Information System) technology |
| CN103292805A (en) * | 2013-05-28 | 2013-09-11 | 武汉理工大学 | Indoor navigation system and indoor navigation method thereof |
| CN104457738A (en) * | 2014-11-11 | 2015-03-25 | 龚斌 | Indoor navigation method based on mobile terminal application |
| CN104596525A (en) * | 2014-12-29 | 2015-05-06 | 西南交通大学 | Vehicle positioning method based on coded graphics |
| CN106169247A (en) * | 2016-08-04 | 2016-11-30 | 上海交通大学 | The garage parking indoor positioning of view-based access control model and map and micro navigation system and method |
| CN106197417A (en) * | 2016-06-22 | 2016-12-07 | 平安科技（深圳）有限公司 | The indoor navigation method of handheld terminal and handheld terminal |
| CN106468553A (en) * | 2016-08-30 | 2017-03-01 | 上海擎朗智能科技有限公司 | A kind of localization method of the mobile object based on road sign |
| CN107301787A (en) * | 2017-07-28 | 2017-10-27 | 东南大学 | Large parking lot positioning and bootstrap technique based on position Quick Response Code |
-
2018
- 2018-04-04 CN CN201810297034.XA patent/CN108801257B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030060970A1 (en) * | 2001-09-27 | 2003-03-27 | Siemens Information And Communication Mobile Llc | Method and apparatus for defining location coordinates |
| US20060092016A1 (en) * | 2004-10-20 | 2006-05-04 | Modes Jerold R | Systems, methods and devices for area-based localization |
| CN1996289A (en) * | 2006-12-26 | 2007-07-11 | 董崇军 | Searching and positioning method using electronic map |
| CN102479214A (en) * | 2010-11-30 | 2012-05-30 | 余政 | Positioning method and positioning system based on bar code identification technology and GIS (Geographic Information System) technology |
| CN103292805A (en) * | 2013-05-28 | 2013-09-11 | 武汉理工大学 | Indoor navigation system and indoor navigation method thereof |
| CN104457738A (en) * | 2014-11-11 | 2015-03-25 | 龚斌 | Indoor navigation method based on mobile terminal application |
| CN104596525A (en) * | 2014-12-29 | 2015-05-06 | 西南交通大学 | Vehicle positioning method based on coded graphics |
| CN106197417A (en) * | 2016-06-22 | 2016-12-07 | 平安科技（深圳）有限公司 | The indoor navigation method of handheld terminal and handheld terminal |
| CN106169247A (en) * | 2016-08-04 | 2016-11-30 | 上海交通大学 | The garage parking indoor positioning of view-based access control model and map and micro navigation system and method |
| CN106468553A (en) * | 2016-08-30 | 2017-03-01 | 上海擎朗智能科技有限公司 | A kind of localization method of the mobile object based on road sign |
| CN107301787A (en) * | 2017-07-28 | 2017-10-27 | 东南大学 | Large parking lot positioning and bootstrap technique based on position Quick Response Code |
Non-Patent Citations (1)
| Title |
|---|
| 胡立栓等: "基于RFID/GIS/GPS的物流商品监控系统模型研究 ", 《测绘与空间地理信息》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109532824A (en) * | 2018-12-19 | 2019-03-29 | 杭州湘滨电子科技有限公司 | A kind of curb recognition methods that level is parked |
| CN109532824B (en) * | 2018-12-19 | 2020-09-01 | 杭州湘滨电子科技有限公司 | Road edge identification method for horizontal parking |
| CN111161449A (en) * | 2020-01-07 | 2020-05-15 | 东南大学 | Vehicle large-scale parking lot interior positioning method based on automobile data recorder image |
| CN113435227A (en) * | 2020-03-23 | 2021-09-24 | 阿里巴巴集团控股有限公司 | Map generation and vehicle positioning method, system, device and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108801257B (en) | 2021-05-11 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10650236B2 (en) | Road detecting method and apparatus | |
| CN108536851B (en) | User identity recognition method based on moving track similarity comparison | |
| CN105469418A (en) | Photogrammetry-based wide-field binocular vision calibration device and calibration method | |
| CN108801257A (en) | A kind of localization method for indoor automatic parking | |
| CN109543600A (en) | A kind of realization drivable region detection method and system and application | |
| CN109459045B (en) | Improved interactive voting matching method for low-frequency GPS track | |
| CN104007760B (en) | Method for self-locating in a kind of autonomous robot vision guided navigation | |
| CN103473774B (en) | A kind of vehicle positioning method based on pavement image characteristic matching | |
| CN109285198B (en) | Method for coding and identifying annular coding mark points | |
| CN105184801A (en) | Optical and SAR image high-precision registration method based on multilevel strategy | |
| CN113238209B (en) | Road perception method, system, equipment and storage medium based on millimeter wave radar | |
| CN108090911A (en) | A kind of offshore naval vessel dividing method of remote sensing image | |
| CN103729863B (en) | Traffic lights automatic location based on autonomous learning is known method for distinguishing | |
| CN103310203B (en) | Pointer type instrument indication value automatic identifying method based on Internet of Things and machine vision | |
| CN115717894A (en) | Vehicle high-precision positioning method based on GPS and common navigation map | |
| CN105809149A (en) | Lane line detection method based on straight lines with maximum length | |
| CN114581887B (en) | Method, device, equipment and computer readable storage medium for detecting lane line | |
| CN110688902B (en) | Method and device for detecting vehicle area in parking space | |
| CN111144452A (en) | Mobile user trip chain extraction method based on signaling data and clustering algorithm | |
| Tsai et al. | Horizontal roadway curvature computation algorithm using vision technology | |
| Ding et al. | Efficient vanishing point detection method in complex urban road environments | |
| CN105444741A (en) | Double view window based route characteristic identifying, deviation measuring, and accurate positioning method | |
| CN112562330A (en) | Method and device for evaluating road operation index, electronic equipment and storage medium | |
| Wang et al. | Pavement marking incorporated with binary code for accurate localization of autonomous vehicles | |
| CN115880683A (en) | Urban waterlogging ponding intelligent water level detection method based on deep learning |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |