CN109632265A - A kind of the unmanned boat water sampling device mated condition detection system and method for view-based access control model - Google Patents
A kind of the unmanned boat water sampling device mated condition detection system and method for view-based access control model Download PDFInfo
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Abstract
一种基于视觉的无人艇采水装置对接状态检测系统及方法，公开了一种应用在无人水质检测艇上对采水装置的对接状态进行实时检测的系统和方法，其中，该检测系统包括视频采集模块、无线图传模块、终端处理及显示模块，该检测方法通过视频采集模块采集图像，无线图传模块发送给终端处理及显示模块，终端处理及显示模块接收图像后，运行兴趣区域阈值检测算法，对图像进行处理和显示，最终得出对接是否成功的结果。本发明的系统容易搭建，易于操作，成本低廉，实现了无人水质检测艇上采水装置对接机构对接状态的自动化检测，提高了无人水质检测艇的自动化程度，更加智能和高效。
A vision-based system and method for detecting the docking state of a water harvesting device for an unmanned boat, discloses a system and method for real-time detection of the docking state of a water harvesting device applied to an unmanned water quality inspection boat, wherein the detection system It includes a video acquisition module, a wireless image transmission module, and a terminal processing and display module. The detection method collects images through the video acquisition module, and the wireless image transmission module sends the image to the terminal processing and display module. After the terminal processing and display module receives the image, it runs the region of interest. The threshold detection algorithm processes and displays the image, and finally obtains the result of whether the docking is successful. The system of the invention is easy to build, easy to operate and low in cost, realizes automatic detection of the docking state of the docking mechanism of the water collection device on the unmanned water quality testing boat, improves the automation degree of the unmanned water quality testing boat, and is more intelligent and efficient.
Description
Technical field
It is specifically a kind of to apply in nothing the present invention relates to unmanned machine technical field more particularly to unmanned water quality detection ship
The system and method that the mated condition of water sampling device is measured in real time on people's water quality detection ship.
Background technique
Currently, the water quality detection of China ocean depends on artificial acquisition testing, testing cost is high, and automation is at low cost,
Risk of going to sea is high, while the discomfort tenant in common's operation due to pollution, high-risk etc. of some sea areas.Increasingly with unmanned boat technology
The development and application of mature and automatic water quality detection equipment, unmanned water quality detection ship come into being, and can be realized adopting automatically for water sample
Collection, distribution and detection, however, being wherein connected to CTD(conductivity-temperature-depth system) the water sampling module and water sample distribution module of hydrophore
Docking mechanism accurately whether docking directly affects water sampling and detection, therefore it is very necessary to the detection of docking mechanism.
Since whole process is in nobody automated processes when unmanned water quality detection ship carries out water quality detection task, people can only be in mother
Ship or bank base remotely monitor, and simple video monitoring needs to spend a large amount of time and efforts of supervisor, and in certain environment
Under it is bad from the picture effect under monitoring screen, can make troubles to artificial monitoring and even make mistakes, this not only causes people
The wasting of resources of power, it is also possible to the error of monitoring result can be brought, it is therefore desirable to which a kind of automatic checkout system is come to docking mechanism
It is monitored in real time.
Summary of the invention
In order to solve the deficiencies in the prior art, the present invention proposes a kind of vision-based inspection system, unmanned water quality detection
The mated condition of water sampling device is monitored in real time on ship, to improve detection accuracy, reduces manpower consumption, and then guarantee water quality prison
Survey task is normally carried out.
The technical problem to be solved by the present invention is to what is be achieved through the following technical solutions:
A kind of unmanned boat water sampling device mated condition detection system of view-based access control model, including video acquisition module, wireless image transmission mould
Block, terminal processes and display module, wherein video acquisition module is mounted on unmanned boat, including alignment water sampling device docking machine
The IP Camera of structure, wireless image transmission module include two groups of radio receiving transmitting modules and antenna, wherein one group of radio receiving transmitting module and
Antenna is arranged on unmanned boat, connect with video acquisition module, and another group of radio receiving transmitting module and antenna are arranged in lash ship or bank
Base is connect with terminal processes and display module, and two groups are connected between radio receiving transmitting module and antenna by wireless telecommunications, the end
End processing and display module include embedded visual detection algorithm and the computer terminal for having display screen.
In the present invention, the camera of the video acquisition module is the camera of fixed focal length, and water dress is adopted in alignment
Setting docking mechanism includes upper docking column, lower docking column and rubber seal, wherein upper docking column is connected with drawing water for water sampling device
Pipeline, lower docking column are connected with the water outlet of CTD hydrophore, and upper docking column is connect with lower docking column by being mutually inserted, rubber
Upper docking column and the lower junction for docking column is arranged in glue sealing ring.
In the present invention, the terminal processes and display module include main interface and sub-interface, and main interface for supervising in real time
Control detection and intelligent early-warning, are provided with display menu frame, parameter set button, detection switch and alarm lamp above, and sub-interface is logical
The parameter set button starting crossed in main interface is provided with parameter setting frame for trained and detection parameters to be arranged above.
A kind of unmanned boat water sampling device mated condition detection method of view-based access control model, comprising the following steps:
(1) video and pictorial information at the camera acquisition water sampling device docking mechanism docking of video acquisition module；
(2) the collected video information of video acquisition module uploads on lash ship or bank base by wireless image transmission module from unmanned boat
Terminal processes and display module；
(3) terminal processes and display module operation docking detection monitoring software, operation docking detection algorithm, by result terminal into
Row display, and carry out flash lamp and voice double knock.
Wherein, the docking detection algorithm of step (3) is interest region threshold detection algorithm (RTD, roi threshold
Detection algorithm), including off-line training and on-line checking stage, the wherein specific steps packet of off-line training step
It includes:
1. by the picture of usually above system acquisition to dock successfully as positive sample, docking failure is negative sample, building instruction
Practice data set, inputted sample color image as algorithm, picture original image size is resolution ratio 1280 × 720；
2. extracting the rectangular area at intermediate docking location is used as area-of-interest (roi), area size for resolution ratio 440 ×
215, background is simple in area-of-interest, and foreground and background is easy to come by color separated；This step had both reduced processing figure
Piece size, but it is relatively simple that algorithm process can be made to get up, and improves algorithm operational efficiency；
3. the color image for the area-of-interest that previous step is obtained carries out gray processing processing, grayscale image is obtained；
4. the gray scale picture that upper step is obtained carries out thresholding processing, the white of the gasket areas of low-light level and high brightness is docked
Columnar region separates, the number of low brightness pixel in statistical regions；
5. by step 1. obtained in training dataset operating procedure 1. ~ 4., obtain the low brightness pixel number C of each samplei, with
The pixel number of sample is variable, docks successful sample and labels positive sample, and the sample for docking failure labels negative sample, training
Classification thresholds t is obtained, so far off-line training process is completed；
The specific steps in the interest region threshold detection algorithm on-line checking stage include:
6. the color image of video acquisition module acquisition is inputted as algorithm, picture size is resolution ratio 1280 × 720；
7. extracting the rectangular area at intermediate docking location as area-of-interest, area size is resolution ratio 440 × 215；
8. the color image for the area-of-interest that previous step is obtained carries out gray processing processing, grayscale image is obtained；
9. the gray scale picture that upper step is obtained carries out thresholding processing, the number Ct of low brightness pixel in statistical regions；
10. using the step classification thresholds t that 5. off-line training obtains as parameter, the low brightness pixel number that is obtained with on-line checking
CtIt compares, if Ct< t, then dock success, conversely, if Ct>=t, then dock and fail, and need to dock again.
In the present invention, due to relatively simple for structure at the docking of water sampling device docking mechanism, only upper and lower two whites
Docking column and a black sealing ring, adjusting suitable camera installation locations just can use a kind of simple pixels statistics
Method realizes docking detection.After docking successfully, the low brightness pixel in picture is less, after docking failure, docks the seam of intercolumniation
Gap is larger, and the low brightness pixel in image is more.For this scene, using interest region threshold detection algorithm, to dock place
Near zone is area-of-interest, using the number of low brightness pixel after image binaryzation in interested candidate regions as threshold value, just
It can simply judge to dock success or failure.This detection algorithm includes off-line training and two stages of on-line monitoring, offline
Training process docks the picture usually acquired successfully for positive sample, and docking failure is negative sample, training classification thresholds,
In the threshold limit value that detection process is obtained using training as Rule of judgment, that is, can determine whether to be butted into function, it is not only simple but also efficient.
Compared with prior art, the present invention is easy to build, easily operated, low in cost, realizes unmanned water quality detection ship
The automatic detection of upper water sampling device docking mechanism mated condition improves the degree of automation of unmanned water quality detection ship, reduces
Manpower consumption, more intelligence and efficiently, meanwhile, display terminal simple interface is easy to operate, automatic docking detection plus intelligence
Audio alert is very humanized, and Man machine interaction is good, and what be can be convenient adopts in water management software as submodule insertion,
It is portable good.
Detailed description of the invention
Fig. 1 is system connection schematic diagram of the invention；
Fig. 2 is workflow schematic diagram of the invention；
Fig. 3 is visual detection algorithm off-line training flow diagram of the invention；
Fig. 4 is visual detection algorithm on-line checking flow diagram of the invention；
Fig. 5 is terminal processes of the invention and display module main interface schematic diagram；
Fig. 6 is terminal processes of the invention and display module sub-interface schematic diagram.
In figure: above docking column 1, rubber seal 2, lower docking column 3, water sampling device docking mechanism 4, camera 5, wireless receipts
Send out module and antenna 6, wireless image transmission module 7, terminal processes and display module 8.
Specific embodiment
Below in conjunction with Figure of description and specific preferred embodiment, the invention will be further described, but not therefore and
It limits the scope of the invention.
Referring to the unmanned boat water sampling device mated condition detection system and method for view-based access control model shown in Fig. 1-6, wherein
In Fig. 1, the unmanned boat water sampling device mated condition detection system of the view-based access control model includes video acquisition module, wireless image transmission mould
Block 7, terminal processes and display module 8, wherein video acquisition module is mounted on unmanned boat, and the network including fixed focal length is taken the photograph
As head 5, alignment water sampling device docking mechanism 4 is arranged, and water sampling device docking mechanism 4 includes upper docking column 1, lower 3 and of docking column
Rubber seal 2, wherein upper docking column 1 is connected with the pumping conduit of water sampling device, lower docking column 3 is connected with CTD hydrophore
Water outlet, upper docking column 1 are connect with lower docking column 3 by being mutually inserted, and the setting of rubber seal 2 is in upper docking column 1 under
Dock the junction of column 3；The wireless image transmission module 7 includes two groups of radio receiving transmitting modules and antenna 6, wherein one group of wireless receiving and dispatching
Module and antenna 6 are arranged on unmanned boat, connect with video acquisition module, and another group of radio receiving transmitting module and the setting of antenna 6 exist
Lash ship or bank base are connect with terminal processes and display module 8, pass through wireless telecommunications between two groups of radio receiving transmitting modules and antenna 6
Connection, the terminal processes and display module 8 include embedded visual detection algorithm and the computer terminal for having display screen, such as Fig. 5
With 6, including main interface and sub-interface, main interface for monitor in real time detection and intelligent early-warning, be provided with above display menu frame,
Parameter set button, detection switch and alarm lamp, sub-interface are started by the parameter set button in main interface, for instruction to be arranged
Experienced and detection parameters, are provided with parameter setting frame above.
Based on above structure, a kind of unmanned boat water sampling device mated condition detection method of view-based access control model, as shown in Fig. 2,
The following steps are included:
(1) video and pictorial information at the camera acquisition water sampling device docking mechanism docking of video acquisition module；
(2) the collected video information of video acquisition module uploads on lash ship or bank base by wireless image transmission module from unmanned boat
Terminal processes and display module；
(3) terminal processes and display module operation docking detection monitoring software, operation docking detection algorithm, by result terminal into
Row display, and carry out flash lamp and voice double knock.
Wherein, the docking detection algorithm of step (3) is interest region threshold detection algorithm, including off-line training and online inspection
In the survey stage, wherein off-line training step is as shown in figure 3, its specific steps includes:
1. by the picture of usually above system acquisition to dock successfully as positive sample, docking failure is negative sample, building instruction
Practice data set, inputted sample color image as algorithm, picture original image size is resolution ratio 1280 × 720；
2. extracting the rectangular area at intermediate docking location as area-of-interest, area size is resolution ratio 440 × 215, sense
Background is simple in interest region, and foreground and background is easy to come by color separated；
3. the color image for the area-of-interest that previous step is obtained carries out gray processing processing, grayscale image is obtained；
4. the gray scale picture that upper step is obtained carries out thresholding processing, the white of the gasket areas of low-light level and high brightness is docked
Columnar region separates, the number of low brightness pixel in statistical regions；
5. by step 1. obtained in training dataset operating procedure 1. ~ 4., obtain the low brightness pixel number C of each samplei, with
The pixel number of sample is variable, docks successful sample and labels positive sample, and the sample for docking failure labels negative sample, training
Classification thresholds t is obtained, so far off-line training process is completed；
The interest region threshold detection algorithm on-line checking stage is as shown in figure 4, its specific steps includes:
6. the color image of video acquisition module acquisition is inputted as algorithm, picture size is resolution ratio 1280 × 720；
7. extracting the rectangular area at intermediate docking location as area-of-interest, area size is resolution ratio 440 × 215；
8. the color image for the area-of-interest that previous step is obtained carries out gray processing processing, grayscale image is obtained；
9. the gray scale picture that upper step is obtained carries out thresholding processing, the number Ct of low brightness pixel in statistical regions；
10. using the step classification thresholds t that 5. off-line training obtains as parameter, the low brightness pixel number that is obtained with on-line checking
CtIt compares, if Ct< t, then dock success, conversely, if Ct>=t, then dock and fail, and need to dock again.
Therefore, easily operated in conjunction with above-mentioned construction and method it can be found that system of the invention is easy to build, it is at low cost
It is honest and clean, the automatic detection of water sampling device docking mechanism mated condition on unmanned water quality detection ship is realized, unmanned water quality is improved
The degree of automation of ship is detected, it is more intelligent and efficient.
Claims (5)
1. a kind of unmanned boat water sampling device mated condition detection system of view-based access control model, it is characterised in that: including video acquisition mould
Block, wireless image transmission module, terminal processes and display module, wherein video acquisition module is mounted on unmanned boat, including alignment is adopted
The IP Camera of water installations docking mechanism, wireless image transmission module include two groups of radio receiving transmitting modules and antenna, wherein one group without
Line transceiver module and antenna are arranged on unmanned boat, connect with video acquisition module, another group of radio receiving transmitting module and antenna are set
It sets in lash ship or bank base, is connect with terminal processes and display module, two groups pass through channel radio between radio receiving transmitting module and antenna
News connection, the terminal processes and display module include embedded visual detection algorithm and the computer terminal for having display screen.
2. the unmanned boat water sampling device mated condition detection system of view-based access control model according to claim 1, it is characterised in that:
The camera of the video acquisition module is the camera of fixed focal length, and the water sampling device docking mechanism of alignment includes upper docking
Column, lower docking column and rubber seal, wherein upper docking column is connected with the pumping conduit of water sampling device, lower docking column is connected with
The water outlet of CTD hydrophore, upper docking column are connect with lower docking column by being mutually inserted, and rubber seal is arranged in upper docking
Column and the lower junction for docking column.
3. the unmanned boat water sampling device mated condition detection system of view-based access control model according to claim 1, it is characterised in that:
The terminal processes and display module include main interface and sub-interface, and main interface detects simultaneously intelligent early-warning for monitoring in real time, on
Face is provided with display menu frame, parameter set button, detection switch and alarm lamp, sub-interface and passes through the parameter setting in main interface
Button starting is provided with parameter setting frame for trained and detection parameters to be arranged above.
4. a kind of unmanned boat water sampling device mated condition detection method of view-based access control model, it is characterised in that: the following steps are included:
Video and pictorial information at the camera acquisition water sampling device docking mechanism docking of video acquisition module；
The collected video information of video acquisition module uploads on lash ship or bank base by wireless image transmission module from unmanned boat
Terminal processes and display module；
Terminal processes and display module operation docking detection monitoring software, operation docking detection algorithm carry out result in terminal
It has been shown that, and carry out flash lamp and voice double knock.
5. the unmanned boat water sampling device mated condition detection method of view-based access control model according to claim 4, it is characterised in that:
The docking detection algorithm is interest region threshold detection algorithm, including off-line training and on-line checking stage, wherein offline instruction
Practice the stage specific steps include:
1. by the picture of usually above system acquisition to dock successfully as positive sample, docking failure is negative sample, building instruction
Practice data set, inputted sample color image as algorithm, picture original image size is resolution ratio 1280 × 720；
2. extracting the rectangular area at intermediate docking location as area-of-interest, area size is resolution ratio 440 × 215, sense
Background is simple in interest region, and foreground and background is easy to come by color separated；
3. the color image for the area-of-interest that previous step is obtained carries out gray processing processing, grayscale image is obtained；
4. the gray scale picture that upper step is obtained carries out thresholding processing, the white of the gasket areas of low-light level and high brightness is docked
Columnar region separates, the number of low brightness pixel in statistical regions；
5. by step 1. obtained in training dataset operating procedure 1. ~ 4., obtain the low brightness pixel number C of each samplei, with
The pixel number of sample is variable, docks successful sample and labels positive sample, and the sample for docking failure labels negative sample, training
Classification thresholds t is obtained, so far off-line training process is completed；
The specific steps in the interest region threshold detection algorithm on-line checking stage include:
6. the color image of video acquisition module acquisition is inputted as algorithm, picture size is resolution ratio 1280 × 720；
7. extracting the rectangular area at intermediate docking location as area-of-interest, area size is resolution ratio 440 × 215；
8. the color image for the area-of-interest that previous step is obtained carries out gray processing processing, grayscale image is obtained；
9. the gray scale picture that upper step is obtained carries out thresholding processing, the number Ct of low brightness pixel in statistical regions；
10. using the step classification thresholds t that 5. off-line training obtains as parameter, the low brightness pixel number C that is obtained with on-line checkingt
It compares, if Ct< t, then dock success, conversely, if Ct>=t, then dock and fail, and need to dock again.
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Effective date of registration: 20221121 Address after: 200444 Room 190, Building A, 5/F, Building 1, No. 1000 Zhenchen Road, Baoshan District, Shanghai Patentee after: Jinghai Intelligent Equipment Co.,Ltd. Address before: 200444 No. 99, upper road, Shanghai, Baoshan District Patentee before: Shanghai University |