CN102663344A - Damaged road detection device based on image segmentation - Google Patents
Damaged road detection device based on image segmentation Download PDFInfo
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- CN102663344A CN102663344A CN201210055687XA CN201210055687A CN102663344A CN 102663344 A CN102663344 A CN 102663344A CN 201210055687X A CN201210055687X A CN 201210055687XA CN 201210055687 A CN201210055687 A CN 201210055687A CN 102663344 A CN102663344 A CN 102663344A
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Abstract
The invention discloses a damaged road detection device based on image segmentation, belonging to the field of image recognition and automatic control. The device includes a CCD camera, image segmentation modules, and an alarm module, wherein a road image that is shot by the CCD camera is processed by the image segmentation modules to estimate data about the damaged road, and the data is further transmitted to the alarm module for alarm processing. The image segmentation modules include an image preprocessing module, an distorted image correction module, a road surface damage image segmentation module, a feature extraction module and an image identification module, wherein distorted image correction is performed after image preprocessing and standardized image data is transmitted to the road surface damage image segmentation module, and then, the image is segmented through the road surface damage image segmentation module and is further transmitted to the feature extraction module for feature extracting , and road damage is identified by the image identification module according to the features. Through performing the segmentation processing method on the entire road surface image, the road damage can be automatically detected.
Description
Technical field
The invention belongs to image recognition and automation field, relate more specifically to a kind of damaged road detection apparatus based on image segmentation.
Background technology
Pavement quality has significant effects to travel safety, comfortableness, economy and highway life cycle.Along with the development of highway communication forwarding business, people have higher requirement to highway pavement quality and maintenance thereof.The road surface breakage data are one of data important in the maintenance of surface management; Because data acquisition, the evaluation of road pavement lack of control system; The quantitative evaluation that the Maintenance Decision making of science and road pavement are damaged causes waste, the pavement quality of maintenance fund to descend and the cost of use increase.
For adapting to modernization, extensive, high-speed and high-quality highway maintenance management expectancy; Many traffic departments have all implemented pavement management system; But the city mainly adopts the method for manual detection to obtain data mostly at present; But manual detection efficiency is low, consuming time, and there is unsafe factor in on-the-spot the detection.Therefore, in the last few years, all attached great importance to the development and application of pavement detection device both at home and abroad.
In the research of pavement detection technical elements the history in more than 30 year has been arranged both at home and abroad, and along with development of high-tech had breakthrough in recent years.According to the national conditions and the demand of various countries, various countries have adopted different research ideas and methods, have formed the detection technique and the checkout equipment of different-style and characteristics.The open-air high-speed photography that France produces, the road surface breakage inspection vehicle of indoors artificial interpretation; It is to adopt the 35mm photographic film that this system gets gordian technique; High-speed camera and Vehicle positioning system realize the data acquisition of synchronous shooting; Video camera is 1/200 of the speed of a motor vehicle, and along with vehicle ' is constantly absorbed the road surface image, the road surface of each influence representative is long to be 6cm * 4.6cm.Detect and generally carry out, join light fixture before the car at night.The image film of picked-up reproduces the road surface breakage situation through developing and printing through indoor interpretation equipment, and the technician is the various pavement diseases of interpretation in view of the above, but the workload of indoor processing is bigger, can not realize real-time detection.
Summary of the invention
1. technical matters to be solved by this invention.
The image segmentation of Road Detection is to be divided into many interesting areas and the corresponding process of the various object targets of image to the target in the image, through could original image being converted into more abstract, compacter form after the image segmentation.
2. the technical scheme that addresses the above problem of the present invention.
Shown in accompanying drawing 1, damaged road detection apparatus comprises ccd video camera, image segmentation module, early warning module; Behind the ccd video camera picked-up road image, after process image segmentation resume module is judged damaged road, be transferred to the early warning module and carry out the early warning processing.
Shown in accompanying drawing 2, the image segmentation module comprises image pre-processing module, distorted image correction module, road surface breakage image division module, characteristic extracting module, picture recognition module; The laggard line distortion image rectification of image pre-service; Standardized image data transmission is divided module to road surface breakage image; Divide after module cuts apart image through road surface breakage image, be transferred to characteristic extracting module and extract characteristic, picture recognition module is by the damaged situation of feature identification road.
The image pre-processing module is improved picture quality, comprises figure image intensifying and return function; Wherein enhancement function is outstanding with feature selecting property, and unnecessary characteristic decays.
The distorted image correction module is proofreaied and correct the geometric distortion of the inside breakage image generation of ccd video camera irradiation.
Road surface breakage image is divided picture size after the module segmentation smaller or equal to 20cm * 20cm, and to satisfy view picture road surface sub-image window number be 2 power series, and sub-piece pixel is smaller or equal to 64 * 64.
Characteristic extracting module adopts sub-image standard deviation matrix description pavement image characteristic.
Picture recognition module adopts the BP network in the artificial nerve network classifier, and network learning procedure comprises forward-propagating and backpropagation, and input information passes to output layer through the hidden layer weighted from input layer during forward-propagating; The output valve and the expectation value that after the action function computing, obtain compare, if error, then error back propagation are arranged; Connecting path through original returns; Through successively revising the neuronic weight coefficient of each layer, reduce error, so circulation is till output meets the demands.
The early warning module receives the damaged road data of picture recognition module output and points out, and guarantees that operating personnel understand the damaged situation of road.
Identification is the main means that road surface breakage automatically detects after the image segmentation, through with view picture pavement image division processing method, makes computation amount, and can survey the damaged situation of road automatically.
Description of drawings
Accompanying drawing 1 is a system construction drawing of the present invention.
Accompanying drawing 2 is image segmentation modular structure figure of the present invention.
Embodiment
Damaged road detection apparatus comprises ccd video camera, image segmentation module, early warning module, behind the ccd video camera picked-up road image, after process image segmentation resume module is judged damaged road, is transferred to the early warning module and carries out the early warning processing.
Select the ccd video camera of two 15 frame/seconds for use, the speed per hour that requires onboard system is 60km/h, detects spatial resolution 2mm/ pel spacing, and ground is 1.8m to the lens apex distance.
The image segmentation module comprises image pre-processing module, distorted image correction module, road surface breakage image division module, characteristic extracting module, picture recognition module; The laggard line distortion image rectification of image pre-service; Standardized image data transmission is divided module to road surface breakage image; Divide after module cuts apart image through road surface breakage image, be transferred to characteristic extracting module and extract characteristic, picture recognition module is by the damaged situation of feature identification road.
The image pre-processing module is improved picture quality, comprises figure image intensifying and return function; Wherein enhancement function is outstanding with feature selecting property, and unnecessary characteristic decays.
The distorted image correction module is proofreaied and correct the geometric distortion of the inside breakage image generation of ccd video camera irradiation.
Road surface breakage image is divided picture size after the module segmentation smaller or equal to 20cm * 20cm, and to satisfy view picture road surface sub-image window number be 2 power series, and sub-piece pixel is smaller or equal to 64 * 64.
Characteristic extracting module adopts sub-image standard deviation matrix description pavement image characteristic.
Picture recognition module adopts the BP network in the artificial nerve network classifier, and network learning procedure comprises forward-propagating and backpropagation, and input information passes to output layer through the hidden layer weighted from input layer during forward-propagating; The output valve and the expectation value that after the action function computing, obtain compare, if error, then error back propagation are arranged; Connecting path through original returns; Through successively revising the neuronic weight coefficient of each layer, reduce error, so circulation is till output meets the demands.
The early warning module receives the damaged road data of picture recognition module output and points out, and guarantees that operating personnel understand the damaged situation of road.
The foregoing description does not limit the present invention in any way, and every employing is equal to the technical scheme that replacement or the mode of equivalent transformation obtain and all drops in protection scope of the present invention.
Claims (6)
1. the damaged road detection apparatus based on image segmentation comprises ccd video camera, image segmentation module, early warning module; Behind the ccd video camera picked-up road image; After process image segmentation resume module is judged damaged road; Be transferred to the early warning module and carry out the early warning processing, it is characterized in that: the image segmentation module comprises image pre-processing module, distorted image correction module, road surface breakage image division module, characteristic extracting module, picture recognition module; The laggard line distortion image rectification of image pre-service; Standardized image data transmission is divided module to road surface breakage image; Divide after module cuts apart image through road surface breakage image, be transferred to characteristic extracting module and extract characteristic, picture recognition module is by the damaged situation of feature identification road.
2. damaged road detection apparatus according to claim 1 is characterized in that: the image pre-processing module is improved picture quality, comprises figure image intensifying and return function; Wherein enhancement function is outstanding with feature selecting property, and unnecessary characteristic decays.
3. damaged road detection apparatus according to claim 1 is characterized in that: the distorted image correction module is proofreaied and correct the geometric distortion of the road surface breakage image generation of ccd video camera irradiation.
4. damaged road detection apparatus according to claim 1; It is characterized in that: the picture size after the road surface breakage image division module segmentation is smaller or equal to 20cm * 20cm; And to satisfy view picture road surface sub-image window number be 2 power series, and sub-piece pixel is smaller or equal to 64 * 64.
5. damaged road detection apparatus according to claim 1 is characterized in that: characteristic extracting module adopts sub-image standard deviation matrix description pavement image characteristic.
6. damaged road detection apparatus according to claim 1 is characterized in that: picture recognition module adopts the BP network in the artificial nerve network classifier, and network learning procedure comprises forward-propagating and backpropagation; Input information passes to output layer through the hidden layer weighted from input layer during forward-propagating; The output valve and the expectation value that after the action function computing, obtain compare, if error, then error back propagation are arranged; Connecting path through original returns; Through successively revising the neuronic weight coefficient of each layer, reduce error, so circulation is till output meets the demands.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104331708A (en) * | 2014-11-05 | 2015-02-04 | 武汉大学 | Automatic detecting and analyzing method and system for crosswalk lines |
| WO2018000731A1 (en) * | 2016-06-28 | 2018-01-04 | 华南理工大学 | Method for automatically detecting curved surface defect and device thereof |
| CN108765404A (en) * | 2018-05-31 | 2018-11-06 | 南京行者易智能交通科技有限公司 | A kind of road damage testing method and device based on deep learning image classification |
| CN110060233A (en) * | 2019-03-20 | 2019-07-26 | 中国农业机械化科学研究院 | A kind of corn ear damage testing method |
| CN111368592A (en) * | 2018-12-25 | 2020-07-03 | 億增营造有限公司 | Intelligent road missing identification method and system |
| WO2020199538A1 (en) * | 2019-04-04 | 2020-10-08 | 中设设计集团股份有限公司 | Bridge key component disease early-warning system and method based on image monitoring data |
| CN111783686A (en) * | 2020-07-03 | 2020-10-16 | 中国交通通信信息中心 | Asphalt pavement health state monitoring system and method |
| CN113537016A (en) * | 2021-07-06 | 2021-10-22 | 南昌市微轲联信息技术有限公司 | Method for automatically detecting and early warning road damage in road patrol |
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Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104331708A (en) * | 2014-11-05 | 2015-02-04 | 武汉大学 | Automatic detecting and analyzing method and system for crosswalk lines |
| CN104331708B (en) * | 2014-11-05 | 2017-11-10 | 武汉大学 | A kind of zebra crossing automatic detection analysis method and system |
| WO2018000731A1 (en) * | 2016-06-28 | 2018-01-04 | 华南理工大学 | Method for automatically detecting curved surface defect and device thereof |
| CN108765404A (en) * | 2018-05-31 | 2018-11-06 | 南京行者易智能交通科技有限公司 | A kind of road damage testing method and device based on deep learning image classification |
| CN111368592A (en) * | 2018-12-25 | 2020-07-03 | 億增营造有限公司 | Intelligent road missing identification method and system |
| CN111368592B (en) * | 2018-12-25 | 2023-02-03 | 億增营造有限公司 | Intelligent road missing identification method and system |
| CN110060233A (en) * | 2019-03-20 | 2019-07-26 | 中国农业机械化科学研究院 | A kind of corn ear damage testing method |
| WO2020199538A1 (en) * | 2019-04-04 | 2020-10-08 | 中设设计集团股份有限公司 | Bridge key component disease early-warning system and method based on image monitoring data |
| CN111783686A (en) * | 2020-07-03 | 2020-10-16 | 中国交通通信信息中心 | Asphalt pavement health state monitoring system and method |
| CN113537016A (en) * | 2021-07-06 | 2021-10-22 | 南昌市微轲联信息技术有限公司 | Method for automatically detecting and early warning road damage in road patrol |
| CN113537016B (en) * | 2021-07-06 | 2023-01-06 | 南昌市微轲联信息技术有限公司 | Method for automatically detecting and early warning road damage in road patrol |
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Application publication date: 20120912 |