CN104964708A - Pavement pit detecting method based on vehicular binocular vision - Google Patents
Pavement pit detecting method based on vehicular binocular vision Download PDFInfo
- Publication number
- CN104964708A CN104964708A CN201510234379.7A CN201510234379A CN104964708A CN 104964708 A CN104964708 A CN 104964708A CN 201510234379 A CN201510234379 A CN 201510234379A CN 104964708 A CN104964708 A CN 104964708A
- Authority
- CN
- China
- Prior art keywords
- road surface
- hole
- groove
- image
- vehicle
- 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
Landscapes
- Traffic Control Systems (AREA)
- Control Of Driving Devices And Active Controlling Of Vehicle (AREA)
- Navigation (AREA)
- Image Processing (AREA)
Abstract
The invention provides a pavement pit detecting method based on vehicular binocular vision. The method singles out a pavement pit by selecting a reasonable threshold of vibration sampling information of a vibration sensor, gives positional information of the pavement pit in combination with GPS information, and records GPS information by using a key manual external trigging device when wheels run over the pavement pit. A binocular camera system samples a tested pavement and outputs an image to a computer. After acquiring the image of the pavement pit, the computer performs preprocessing and an image processing algorithm on the image so as to obtain the area and depth information of the pavement pit. The method may position the pavement pit, optimizes the conventional image processing algorithm, and may accurately achieve a pavement pit area and depth computing function.
Description
Technical field
The present invention relates to field of road detection and image processing field, be specifically related to a kind ofly utilize image processing algorithm to measure the detection method of the position of groove, hole, road surface, area, depth information based on binocular vision.
Background technology
In recent years, expanding economy has driven the increase of vehicle fleet size, the wearing and tearing of accumulating over a long period along with road surface, and the appearance of hole groove is inevitable, and the importance that the detection that therefore groove is cheated on road surface travels for vehicle is self-evident.It is pith in road surface reparation that hole groove detects, and the development of digital image processing techniques allows traditional pavement detection work becomes more intelligent, mechanization more.
But hole, road surface groove is a kind of special road surface breakage form, traditional road surface measuring method, as Bump Integrator, laser range finder etc. all can only obtain the curve in longitudinal profile, road surface, cannot locate the position of hole, road surface groove, more can not obtain its spatial information.Pavement image process based on conventional edge detection algorithm also cannot obtain the edge of this irregular enclosed region of similar road surface hole groove, the sampling of traditional monocular camera road pavement image, the limitation being two dimension due to its planar dimensions also cannot measure the space three-dimensional information that groove is cheated on road surface.
Summary of the invention
The defect of hole, road surface slot space information cannot be recorded in order to solve classic method, present invention incorporates the hardware devices such as GPS, binocular camera, vibration transducer, use vehicle-mounted mode, the position of positioning pit groove, the image of collection hole groove, and utilize image algorithm to calculate area, the depth information of hole groove.
For realizing above-mentioned technical purpose, reach above-mentioned technique effect, the present invention is achieved through the following technical solutions:
Hole, a kind of road surface based on vehicle-mounted binocular vision groove detection method, the method based on hardware comprise main control chip, described main control chip is connected to binocular camera system, GPS positioning system, vibration transducer, artificial external trigger device and computing machine, it is characterized in that, described binocular camera system is installed on road pavement image on vehicle ceiling and gathers, described GPS positioning system is fixed on vehicle ceiling together with binocular camera system, described vibration transducer is fixed in meter panel of motor vehicle, described artificial external trigger device is fixed on copilot panel, described computing machine carries out road surface hole groove area and the groove depth information measuring and calculating of hole, road surface according to the sampled data that main control chip is passed back:
Hole, described road surface groove area measuring method comprises the following steps:
Step 1.1) receive road surface sampled images, demarcate each pixel area occupied simultaneously;
Step 1.2) to image adaptive median filter noise reduction;
Step 1.3) adopt based on the rapid edge-detection of Rule of Region-growth;
Step 1.4) detect whether be closure edge and differentiate, if not, then illustrate be not road surface hole groove, record GPS information, jump to step 1.1 simultaneously), if so, then go to step 1.5 below);
Step 1.5) sum of all pixels on statistical boundary and the sum of all pixels in border;
Step 1.6) combine the area that each pixel area occupied of demarcating finally obtains hole, road surface groove;
Hole, described road surface groove depth measuring method comprises the following steps:
Step 2.1) receive road surface sampled images;
Step 2.2) to image adaptive median filter noise reduction;
Step 2.3) adopt based on the rapid edge-detection of Rule of Region-growth;
Step 2.4) detect whether be closure edge and differentiate, if not, then illustrate be not road surface hole groove, go to step 2.5 below), if so, then jump to step 2.6);
Step 2.5) record GPS information, jump to step 2.1) simultaneously;
Step 2.6) obtain the closure edge of binocular image and obtain binocular image in the same time;
Step 2.7) check whether two width images have corresponding image points and differentiate, if not, then jump to step 2.5), if so, then go to step 2.8 below);
Step 2.8) carry out corresponding image points coupling;
Step 2.9) calculate section, road surface;
Step 2.10) each point in edge is calculated the distance between section, road surface respectively;
Step 2.11) get the degree of depth of peak value as hole, road surface groove.
Further, described binocular camera system is arranged on vehicle ceiling with fixing angle.
Further, described vibration transducer adopts three axis accelerometer.
Further, in described step 1.4) and step 2.5) in, record GPS information at that time when wheel leaks pressure road surface hole groove by artificial external trigger device.
Further, described artificial external trigger device is button.
The invention has the beneficial effects as follows:
The present invention can complete by building of hardware the location that groove is cheated on road surface, in algorithm, optimize traditional image processing algorithm and accurately can realize hole, road surface groove area, depth calculation function, these data shortly can to a great extent for road quality supervision department provides a novel detection technique, for ensureing that road surface running vehicle provides support safely in the future, important practical meaning in engineering can be had again.
Accompanying drawing explanation
Fig. 1 is for being present system structural representation;
Fig. 2 is hole, road surface groove area measuring and calculating process flow diagram;
Fig. 3 is hole, road surface groove depth measuring and calculating process flow diagram;
The different picture point 3 d space coordinate figures of Fig. 4 for getting in the embodiment of the present invention.
Embodiment
Below with reference to the accompanying drawings and in conjunction with the embodiments, describe the present invention in detail.
With reference to shown in Fig. 1, hole, a kind of road surface based on vehicle-mounted binocular vision groove detection method, the method based on hardware comprise main control chip, described main control chip is connected to binocular camera system, GPS positioning system, vibration transducer, artificial external trigger device and computing machine, it is characterized in that, described binocular camera system is installed on road pavement image on vehicle ceiling and gathers, described GPS positioning system is fixed on vehicle ceiling together with binocular camera system, described vibration transducer is fixed in meter panel of motor vehicle, described artificial external trigger device is fixed on copilot panel, described computing machine carries out road surface hole groove area and the groove depth information measuring and calculating of hole, road surface according to the sampled data that main control chip is passed back:
With reference to shown in Fig. 2, hole, described road surface groove area measuring method comprises the following steps:
Step 1.1) receive road surface sampled images, demarcate each pixel area occupied simultaneously;
Step 1.2) to image adaptive median filter noise reduction;
Step 1.3) adopt based on the rapid edge-detection of Rule of Region-growth;
Step 1.4) detect whether be closure edge and differentiate, if not, then illustrate be not road surface hole groove, record GPS information, jump to step 1.1 simultaneously), if so, then go to step 1.5 below);
Step 1.5) sum of all pixels on statistical boundary and the sum of all pixels in border;
Step 1.6) combine the area that each pixel area occupied of demarcating finally obtains hole, road surface groove, particularly in conjunction with the parameter information of demarcation, according to statistics hole groove edge pixel coordinate, sum of all pixels within the scope of the groove of technology hole, and then obtain hole, road surface groove real area;
With reference to shown in Fig. 3, hole, described road surface groove depth measuring method comprises the following steps:
Step 2.1) receive road surface sampled images;
Step 2.2) to image adaptive median filter noise reduction;
Step 2.3) adopt based on the rapid edge-detection of Rule of Region-growth;
Step 2.4) detect whether be closure edge and differentiate, if not, then illustrate be not road surface hole groove, go to step 2.5 below), if so, then jump to step 2.6);
Step 2.5) record GPS information, jump to step 2.1) simultaneously;
Step 2.6) obtain the closure edge of binocular image and obtain binocular image in the same time;
Step 2.7) check whether two width images have corresponding image points and differentiate, if not, then jump to step 2.5), if so, then go to step 2.8 below);
Step 2.8) carry out corresponding image points coupling;
Step 2.9) calculate section, road surface;
Step 2.10) each point in edge is calculated the distance between section, road surface respectively;
Step 2.11) get the degree of depth of peak value as hole, road surface groove.
Described binocular camera system is arranged on vehicle ceiling with fixing angle.
Described vibration transducer adopts three axis accelerometer.
In described step 1.4) and step 2.5) in, record GPS information at that time when wheel leaks pressure road surface hole groove by artificial external trigger device.
Described artificial external trigger device is button.
In the present embodiment, table 1 represents in process of the test, obtains the area of hole, four road surfaces groove, and, utilize the inventive method also can to measuring some object areas in irregular shape accurately:
Table 1 cheat groove image area test data (square measure:
)
In the present embodiment, table 2 is the spatial coordinate value of different picture point:
Table 2 is based on the 3 d space coordinate calculated value of the maximum performance measure corresponding image points coupling of related coefficient
For different spatial coordinates, it can show in three dimensions.In the diagram, setting is as the coordinate system in Fig. 4, and composition graphs 4 can be found out, be positioned at the ordinate put in the middle part of Fig. 4 comparatively large, this road surface, section is lower, and Y value is around relatively low, and this section is relatively high.
As can be seen from Figure 4, the scope of ordinate is 17.122mm-48.772mm.So just extrapolate and need hole, detection road surface groove depth to be about 31.65mm.
The foregoing is only the preferred embodiments of the present invention, be not limited to the present invention, for a person skilled in the art, the present invention can have various modifications and variations.Within the spirit and principles in the present invention all, any amendment done, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.
Claims (5)
1. hole, the road surface based on vehicle-mounted binocular vision groove detection method, the method based on hardware comprise main control chip, described main control chip is connected to binocular camera system, GPS positioning system, vibration transducer, artificial external trigger device and computing machine, it is characterized in that, described binocular camera system is installed on road pavement image on vehicle ceiling and gathers, described GPS positioning system is fixed on vehicle ceiling together with binocular camera system, described vibration transducer is fixed in meter panel of motor vehicle, described artificial external trigger device is fixed on copilot panel, described computing machine carries out road surface hole groove area and the groove depth information measuring and calculating of hole, road surface according to the sampled data that main control chip is passed back:
Hole, described road surface groove area measuring method comprises the following steps:
Step 1.1) receive road surface sampled images, demarcate each pixel area occupied simultaneously;
Step 1.2) to image adaptive median filter noise reduction;
Step 1.3) adopt based on the rapid edge-detection of Rule of Region-growth;
Step 1.4) detect whether be closure edge and differentiate, if not, then illustrate be not road surface hole groove, record GPS information, jump to step 1.1 simultaneously), if so, then go to step 1.5 below);
Step 1.5) sum of all pixels on statistical boundary and the sum of all pixels in border;
Step 1.6) combine the area that each pixel area occupied of demarcating finally obtains hole, road surface groove;
Hole, described road surface groove depth measuring method comprises the following steps:
Step 2.1) receive road surface sampled images;
Step 2.2) to image adaptive median filter noise reduction;
Step 2.3) adopt based on the rapid edge-detection of Rule of Region-growth;
Step 2.4) detect whether be closure edge and differentiate, if not, then illustrate be not road surface hole groove, go to step 2.5 below), if so, then jump to step 2.6);
Step 2.5) record GPS information, jump to step 2.1) simultaneously;
Step 2.6) obtain the closure edge of binocular image and obtain binocular image in the same time;
Step 2.7) check whether two width images have corresponding image points and differentiate, if not, then jump to step 2.5), if so, then go to step 2.8 below);
Step 2.8) carry out corresponding image points coupling;
Step 2.9) calculate section, road surface;
Step 2.10) each point in edge is calculated the distance between section, road surface respectively;
Step 2.11) get the degree of depth of peak value as hole, road surface groove.
2. hole, the road surface based on vehicle-mounted binocular vision according to claim 1 groove detection method, it is characterized in that, described binocular camera system is arranged on vehicle ceiling with fixing angle.
3. hole, the road surface based on vehicle-mounted binocular vision according to claim 1 groove detection method, it is characterized in that, described vibration transducer adopts three axis accelerometer.
4. hole, the road surface based on vehicle-mounted binocular vision according to claim 1 groove detection method, is characterized in that, in described step 1.4) and step 2.5) in, record GPS information at that time when wheel leaks when groove is cheated on pressure road surface by artificial external trigger device.
5. hole, the road surface based on vehicle-mounted binocular vision according to claim 4 groove detection method, it is characterized in that, described artificial external trigger device is button.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201510234379.7A CN104964708B (en) | 2015-08-03 | 2015-08-03 | A kind of road surface pit detection method based on vehicle-mounted binocular vision |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201510234379.7A CN104964708B (en) | 2015-08-03 | 2015-08-03 | A kind of road surface pit detection method based on vehicle-mounted binocular vision |
Publications (2)
Publication Number | Publication Date |
---|---|
CN104964708A true CN104964708A (en) | 2015-10-07 |
CN104964708B CN104964708B (en) | 2017-09-19 |
Family
ID=54218756
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201510234379.7A Expired - Fee Related CN104964708B (en) | 2015-08-03 | 2015-08-03 | A kind of road surface pit detection method based on vehicle-mounted binocular vision |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN104964708B (en) |
Cited By (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN105277144A (en) * | 2015-10-16 | 2016-01-27 | 浙江工业大学 | Land area rapid detection method based on binocular vision and detection device thereof |
CN105463973A (en) * | 2015-12-15 | 2016-04-06 | 长安大学 | Intelligent pit groove repairing vehicle |
CN108360344A (en) * | 2018-02-11 | 2018-08-03 | 云南通衢工程检测有限公司 | Highway technology condition detecting system |
CN109919139A (en) * | 2019-04-01 | 2019-06-21 | 杭州晶一智能科技有限公司 | Pavement behavior rapid detection method based on binocular stereo vision |
CN110208278A (en) * | 2019-07-09 | 2019-09-06 | 电子科技大学 | The apparent slight crack vision measurement system in road surface |
CN111609892A (en) * | 2020-07-01 | 2020-09-01 | 东山县极点工业设计有限公司 | Improved precision evaluation equipment for grooved industrial products |
CN112229362A (en) * | 2020-10-19 | 2021-01-15 | 南京朗禾智能控制研究院有限公司 | Vehicle-mounted device for accurately measuring area in real time |
CN113962301A (en) * | 2021-10-20 | 2022-01-21 | 北京理工大学 | Multi-source input signal fused pavement quality detection method and system |
Citations (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101907448A (en) * | 2010-07-23 | 2010-12-08 | 华南理工大学 | Depth measurement method based on binocular three-dimensional vision |
CN102061659A (en) * | 2010-10-27 | 2011-05-18 | 毛庆洲 | Urban road pavement routine inspection equipment |
CN102607505A (en) * | 2012-03-23 | 2012-07-25 | 中国科学院深圳先进技术研究院 | Road evenness detection method and road evenness detection system |
CN202433311U (en) * | 2011-12-08 | 2012-09-12 | 长安大学 | Device for detecting damage of road surface |
CN102706880A (en) * | 2012-06-26 | 2012-10-03 | 哈尔滨工业大学 | Road information extraction device based on two-dimensional image and depth information and road crack information detection method based on same |
CN102829763A (en) * | 2012-07-30 | 2012-12-19 | 中国人民解放军国防科学技术大学 | Pavement image collecting method and system based on monocular vision location |
US20130169794A1 (en) * | 2011-12-28 | 2013-07-04 | Fujitsu Limited | Road surface inspection device, road surface inspection method and recording medium |
US20130173208A1 (en) * | 2011-12-28 | 2013-07-04 | Fujitsu Limited | Road surface inspection device and recording medium |
US20140086477A1 (en) * | 2012-09-24 | 2014-03-27 | Ricoh Company, Ltd. | Method and device for detecting drivable region of road |
CN104005325A (en) * | 2014-06-17 | 2014-08-27 | 武汉武大卓越科技有限责任公司 | Pavement crack detecting device and method based on depth and gray level images |
CN204039886U (en) * | 2014-05-07 | 2014-12-24 | 长安大学 | A kind of pavement damage crack detection system based on multiple stage camera stereoscopic shooting |
CN104361627A (en) * | 2014-11-07 | 2015-02-18 | 武汉科技大学 | SIFT-based (scale-invariant feature transform) binocular vision three-dimensional image reconstruction method of asphalt pavement micro-texture |
-
2015
- 2015-08-03 CN CN201510234379.7A patent/CN104964708B/en not_active Expired - Fee Related
Patent Citations (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101907448A (en) * | 2010-07-23 | 2010-12-08 | 华南理工大学 | Depth measurement method based on binocular three-dimensional vision |
CN102061659A (en) * | 2010-10-27 | 2011-05-18 | 毛庆洲 | Urban road pavement routine inspection equipment |
CN202433311U (en) * | 2011-12-08 | 2012-09-12 | 长安大学 | Device for detecting damage of road surface |
US20130169794A1 (en) * | 2011-12-28 | 2013-07-04 | Fujitsu Limited | Road surface inspection device, road surface inspection method and recording medium |
US20130173208A1 (en) * | 2011-12-28 | 2013-07-04 | Fujitsu Limited | Road surface inspection device and recording medium |
CN102607505A (en) * | 2012-03-23 | 2012-07-25 | 中国科学院深圳先进技术研究院 | Road evenness detection method and road evenness detection system |
CN102706880A (en) * | 2012-06-26 | 2012-10-03 | 哈尔滨工业大学 | Road information extraction device based on two-dimensional image and depth information and road crack information detection method based on same |
CN102829763A (en) * | 2012-07-30 | 2012-12-19 | 中国人民解放军国防科学技术大学 | Pavement image collecting method and system based on monocular vision location |
US20140086477A1 (en) * | 2012-09-24 | 2014-03-27 | Ricoh Company, Ltd. | Method and device for detecting drivable region of road |
CN204039886U (en) * | 2014-05-07 | 2014-12-24 | 长安大学 | A kind of pavement damage crack detection system based on multiple stage camera stereoscopic shooting |
CN104005325A (en) * | 2014-06-17 | 2014-08-27 | 武汉武大卓越科技有限责任公司 | Pavement crack detecting device and method based on depth and gray level images |
CN104361627A (en) * | 2014-11-07 | 2015-02-18 | 武汉科技大学 | SIFT-based (scale-invariant feature transform) binocular vision three-dimensional image reconstruction method of asphalt pavement micro-texture |
Non-Patent Citations (2)
Title |
---|
张旻: "双目立体视觉在障碍物识别及定位中的应用研究", 《中国优秀硕士学位论文全文数据库》 * |
檀柏红等: "一种基于区域生长进行边缘跟踪测量路面损坏面积的方法", 《天津科技大学学报》 * |
Cited By (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN105277144A (en) * | 2015-10-16 | 2016-01-27 | 浙江工业大学 | Land area rapid detection method based on binocular vision and detection device thereof |
CN105463973A (en) * | 2015-12-15 | 2016-04-06 | 长安大学 | Intelligent pit groove repairing vehicle |
CN105463973B (en) * | 2015-12-15 | 2017-08-04 | 长安大学 | A kind of intelligent pit repairing car |
CN108360344A (en) * | 2018-02-11 | 2018-08-03 | 云南通衢工程检测有限公司 | Highway technology condition detecting system |
CN109919139A (en) * | 2019-04-01 | 2019-06-21 | 杭州晶一智能科技有限公司 | Pavement behavior rapid detection method based on binocular stereo vision |
CN110208278A (en) * | 2019-07-09 | 2019-09-06 | 电子科技大学 | The apparent slight crack vision measurement system in road surface |
CN111609892A (en) * | 2020-07-01 | 2020-09-01 | 东山县极点工业设计有限公司 | Improved precision evaluation equipment for grooved industrial products |
CN111609892B (en) * | 2020-07-01 | 2021-10-29 | 苏州市东挺河智能科技发展有限公司 | Improved precision evaluation equipment for grooved industrial products |
CN112229362A (en) * | 2020-10-19 | 2021-01-15 | 南京朗禾智能控制研究院有限公司 | Vehicle-mounted device for accurately measuring area in real time |
CN113962301A (en) * | 2021-10-20 | 2022-01-21 | 北京理工大学 | Multi-source input signal fused pavement quality detection method and system |
CN113962301B (en) * | 2021-10-20 | 2022-06-17 | 北京理工大学 | Multi-source input signal fused pavement quality detection method and system |
Also Published As
Publication number | Publication date |
---|---|
CN104964708B (en) | 2017-09-19 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN104964708A (en) | Pavement pit detecting method based on vehicular binocular vision | |
WO2021004548A1 (en) | Vehicle speed intelligent measurement method based on binocular stereo vision system | |
CN111551958B (en) | Mining area unmanned high-precision map manufacturing method | |
CN110285793B (en) | Intelligent vehicle track measuring method based on binocular stereo vision system | |
US11486548B2 (en) | System for detecting crack growth of asphalt pavement based on binocular image analysis | |
CN106296814B (en) | Highway maintenance detection and virtual interactive interface method and system | |
CN103530881B (en) | Be applicable to the Outdoor Augmented Reality no marks point Tracing Registration method of mobile terminal | |
Negru et al. | Image based fog detection and visibility estimation for driving assistance systems | |
CN103605978A (en) | Urban illegal building identification system and method based on three-dimensional live-action data | |
US9196160B2 (en) | Vehicle detection apparatus and vehicle detection method | |
CN105225482A (en) | Based on vehicle detecting system and the method for binocular stereo vision | |
KR20180041176A (en) | METHOD, DEVICE, STORAGE MEDIUM AND DEVICE | |
CN104236478A (en) | Automatic vehicle overall size measuring system and method based on vision | |
CN105678288A (en) | Target tracking method and device | |
CN104183127A (en) | Traffic surveillance video detection method and device | |
CN106871906B (en) | Navigation method and device for blind person and terminal equipment | |
WO2021017211A1 (en) | Vehicle positioning method and device employing visual sensing, and vehicle-mounted terminal | |
CN111210477A (en) | Method and system for positioning moving target | |
CN112749584B (en) | Vehicle positioning method based on image detection and vehicle-mounted terminal | |
CN110619674B (en) | Three-dimensional augmented reality equipment and method for accident and alarm scene restoration | |
CN107688174A (en) | A kind of image distance-finding method, system, storage medium and vehicle-mounted visually-perceptible equipment | |
EP4250245A1 (en) | System and method for determining a viewpoint of a traffic camera | |
Tarko et al. | Tscan: Stationary lidar for traffic and safety studies—object detection and tracking | |
CN103093214B (en) | A kind of pedestrian detection method based on vehicle mounted infrared camera | |
CN106127147A (en) | A kind of face depth texture restorative procedure based on three-dimensional data |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
C06 | Publication | ||
PB01 | Publication | ||
C10 | Entry into substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant | ||
CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20170919 Termination date: 20190803 |
|
CF01 | Termination of patent right due to non-payment of annual fee |