CN105785990B - Ship mooring system and obstacle recognition method based on panoramic looking-around - Google Patents
Ship mooring system and obstacle recognition method based on panoramic looking-around Download PDFInfo
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Abstract
A kind of ship mooring system based on panoramic looking-around includes main control module, the battery being connect with main control module and control module of mooring a boat, the display module being connect with main control module, ship's speed sensor and gyro sensor and four cameras being connect with main control module, the main control module includes master controller, the power circuit being connected respectively with master controller, memory, two signal conditioning circuits that four image rectifications connecting with four cameras are connected with signal conditioning module and respectively with the ship's speed sensor and gyro sensor, the main control module also has Cluster Analysis module, Cluster Analysis module is according to the panoramic picture barrier CHT feature for storing in memory and providing to Cluster Analysis module, it is berthed the safety of environment using adaptive threshold cascading linear support vector machines to current preparation , convenience analyzed, to judge whether to need to call to moor a boat control module, moor a boat.
Description
Technical field
The present invention relates to automation field more particularly to a kind of ship mooring systems based on panoramic looking-around.
Background technique
With the development of economy and society, shipping industry is also used in all various aspects of social industry, such as tourist industry, transport
Industry, even military aspect.Even experienced captain can not also accomplish the specific situation in waters fully aware of.However vision
Information is to realize the technical way of environment sensing and monitoring, system intelligence.With Conventional visual context aware systems visual field compared with
Small difference, panoramic vision can be realized 360 degree of horizontal direction, the big visual field monitoring within the scope of 240 degree of vertical direction, wide
Visual angle is that monitoring ambient enviroment provides convenience.
Therefore, it is really necessary to provide a kind of automatic mooring system of the unmanned boat looked around based on three-dimensional panorama.
Summary of the invention
To solve the above-mentioned problems, one aspect of the present invention provides a kind of ship mooring system based on panoramic looking-around,
It is characterized by: the electricity that the ship mooring system based on panoramic looking-around includes main control module, connect with main control module
Pond and control module of mooring a boat, the display module being connect with main control module, ship's speed sensor, gyro sensor and and master control
Four cameras of molding block connection, the main control module includes master controller, the power supply that is connected respectively with master controller
Circuit, memory, four image rectifications being connect with four cameras and signal conditioning module and respectively with the ship's speed pass
Two signal conditioning circuits that sensor is connected with gyro sensor, the main control module also have Cluster Analysis module, institute
It states memory to connect with Cluster Analysis module, the Cluster Analysis module is connect with control module of mooring a boat.
Further, four cameras are separately mounted to the front, rear, left and right outer surface of hull, camera band respectively
There is water-tight device and there is rotatable wide-angle lens.
Further, the application provides a kind of obstacle recognition method: the ship mooring system based on panoramic looking-around
Working method the following steps are included: firstly, four cameras acquire the real-time picture of front, rear, left and right under hull and ship respectively
Face, and real-time pictures are transmitted to main controller；The ship's speed sensor, gyro sensor acquire the traveling speed of ship respectively
Degree and operation orientation；Four image rectifications and signal conditioning module carry out the collected real-time pictures of four cameras
Then four sub-pictures after correction are carried out splicing again, obtain the panoramic picture around hull by correction and signal processing；Institute
State the panoramic picture around display module display hull；Described two signal conditioning circuits are by ship's speed sensor and gyro sensors
The collected information of device is corrected and signal processing, obtains the ship speed of service and specific orientation；It is deposited in the memory
It stores up the collected ship information and provides the data i.e. panoramic picture of clustering to the Cluster Analysis module；It is described poly-
Alanysis module in memory according to storing and providing panoramic picture barrier feature to Cluster Analysis module, using adaptive thresholding
It is worth cascading linear support vector machines and identifies different type barrier, and has to the berth safety of environment, convenience of current preparation
The clustering algorithm of sharp feature is analyzed, to judge whether to need to call control module of mooring a boat, is moored a boat.
Further, the working method of the ship mooring system provided by the present application based on panoramic looking-around further includes cluster mould
Block working method, the cluster module working method is as follows, using the barrier improved in CHT feature extraction panoramic looking-around image
Feature T,
T=G (pc)t(s(pc-p0),s(pc-p1),…,s(pc-p7))
Wherein,
In formula, the joint distribution function of t () function representation symbol difference value；s(pc-pi) indicate current pixel point pcWith i-th
Neighborhood point piBetween symbol difference value, G (pc) it is standard normal gauss of distribution function.
Using the CHT feature of adaptive threshold cascading linear support vector machines identification different type barrier, to all
Sample extraction CHT feature forms training set, is classified using Linear SVM to it, obtains Hyperplane classification device；
Each sample has an output valve i.e. obstacle identity m, calculating to be shown below about Hyperplane classification device,
Wherein, w*, b*It is the parameter of Hyperplane classification device respectively；xnIt, will be each defeated for the CHT feature vector of n-th of sample
Value adds one-dimensional 0-1 uniform random number out, is mapped to two-dimensional space, after the completion of first layer classifier training, according to adaptive
The method for answering threshold value weeds out the sample for being easy classification, retains training sample of the hard samples as second layer classifier,
And so on, to the last one layer of classification, final acquired disturbance species type judge whether to anchor simultaneously
Compared with prior art, the application has the advantages that the application is berthed based on the ship of panoramic looking-around and is
System high reliablity, measurement accuracy is high, installation and debugging are convenient, it is low in energy consumption, be easy to popularization and promotion.
Detailed description of the invention
Fig. 1 is the schematic diagram of panoramic looking-around ship mooring system in the embodiment of the present invention；
Fig. 2 is adaptive threshold cascade classifier training process figure in the embodiment of the present invention；
Fig. 3 is that the 8 neighborhood CHT features that radius is 1 in the embodiment of the present invention detect window decomposition sample graph；
Fig. 4 is the spatial relation graph in CHT characteristic extraction procedure；
Fig. 5 is the pixel amplitude in CHT characteristic extraction procedure；
Fig. 6 is the symbol difference value in CHT characteristic extraction procedure；
Fig. 7 is the weight template in CHT characteristic extraction procedure.
Specific embodiment
It is a kind of ship mooring system based on panoramic looking-around shown in Fig. 1, the ship based on panoramic looking-around, which berths, is
System includes main control module 1, the battery 2 connecting with main control module 1 and control module 3 of mooring a boat, connect with main control module 1
Display module 4, ship's speed sensor 5 and gyro sensor 6 and four cameras 7 being connect with main control module 1, the master
Control module 1 includes master controller 11, the power circuit 12 being connected respectively with master controller 1, memory 13 and four camera shootings
It is first 7 connection four image rectifications and signal conditioning module 14 and respectively with the ship's speed sensor 5 and gyro sensor 6
Two connected signal conditioning circuits 15, the main control module 1 also have a Cluster Analysis module 16, the memory 13 with it is poly-
Alanysis module 16 connects, and the Cluster Analysis module 16 is connect with control module 3 of mooring a boat.
The battery 2 is used to provide electric power for main control module 1, and power circuit 12 described in main control module 1 is used for
Electric power is provided to master controller 11.
The control module 3 of mooring a boat includes manual control module 31 and automatic control module 32.5 He of ship's speed sensor
Gyro sensor 6 is separately fixed at hull surface, for acquiring the travel speed and operation orientation of ship.Described four are taken the photograph
As head 7 is respectively the first camera 7A, second camera 7B, third camera 7C and the 4th camera 7D, first camera shooting
Head 7A, second camera 7B, third camera 7C and the 4th camera 7D are separately mounted to the front, rear, left and right outer surface of hull
On, and the first camera 7A, second camera 7B, third camera 7C and the 4th camera 7D are all made of band water-tight device
And rotatable wide-angle lens.The first camera 7A, second camera 7B, third camera 7C and the 4th camera 7D points
The real-time pictures of front, rear, left and right under hull and ship Yong Yu not acquired.
It is collected all by the ship for storing ship's speed sensor 5 and gyro sensor 6 in the memory 13
Information only.
Four image rectifications and signal conditioning module 14 are respectively image rectification and signal conditioning module 14A, image
Correction and signal conditioning module 14B, image rectification and signal conditioning module 14C and image rectification and signal conditioning module 14D, figure
As correction and signal conditioning module 14A, image rectification and signal conditioning module 14B, image rectification and signal conditioning module 14C and
Image rectification is taken the photograph with the first camera 7A, second camera 7B, third camera 7C and the 4th respectively with signal conditioning module 14D
As head 7D is correspondingly connected with, and the first camera 7A, second camera 7B, third camera 7C and the 4th camera 7D are collected
Image be corrected and signal processing, the image after then again correcting fourth officer carries out splicing, in order to obtain hull
The panoramic picture of surrounding.The output end of the master controller is connected with the input terminal of the display module, for showing hull
The panoramic picture of surrounding.
Described two signal conditioning circuits 15 are respectively the first signal conditioning circuit 15A and second signal conditioning circuit 15B,
The first signal conditioning circuit 15A and second signal conditioning circuit 15B are respectively used to ship's speed sensor 5 and gyro sensors
The collected information of device 6 is corrected and signal processing, obtains the ship speed of service and specific orientation.
The Cluster Analysis module 16 is according to panorama sketch that is storing in memory 13 and providing to Cluster Analysis module 16
As the CHT feature of barrier, different type barrier is identified using adaptive threshold cascading linear support vector machines, to current standard
The standby safety of environment of berthing, convenience are analyzed, to judge whether to need to call control module 3 of mooring a boat, are moored a boat.
If it is suitable for berthing that the result that the Cluster Analysis module 16 obtains, which is current environment, control module 3 of mooring a boat described in calling is described
Control module of mooring a boat 16 is corresponding to call manual control module 31 or automatic control module 32 manually control under state
Moor a boat or automatic control state under moor a boat.
The working method of ship mooring system in the application based on panoramic looking-around the following steps are included:
Firstly, four cameras 7 acquire the real-time pictures of front, rear, left and right under hull and ship respectively, and by real-time pictures
It is transmitted to main controller；
The ship's speed sensor 5, gyro sensor 6 acquire the travel speed and operation orientation of ship respectively；
Four image rectifications are corrected four collected real-time pictures of camera 7 with signal conditioning module 14
With signal processing, four sub-pictures after correction are then subjected to splicing again, obtain the panoramic picture around hull；
The display module 4 shows the panoramic picture around hull；
Ship's speed sensor 5 and the collected information of gyro sensor 6 are carried out school by described two signal conditioning circuits 15
Just with signal processing, the ship speed of service and specific orientation are obtained；
The collected ship information is stored in the memory 13 and provides cluster to the Cluster Analysis module 16
The data of analysis；
The Cluster Analysis module 16 is according to panorama sketch that is storing in memory 13 and providing to Cluster Analysis module 16
As barrier CHT feature, the berth safety of environment, convenience of current preparation is analyzed, to judge whether to need to adjust
With control module 3 of mooring a boat, moor a boat.
Using the barrier feature T improved in CHT feature extraction panoramic looking-around image.
T=G (pc)t(s(pc-p0),s(pc-p1),…,s(pc-p7))
Wherein:
In formula, the joint distribution function of t () function representation symbol difference value；s(pc-pi) indicate current pixel point pcWith i-th
Neighborhood point piBetween symbol difference value.G(pc) it is standard normal gauss of distribution function.
As shown in Fig. 2, in order to improve detection of obstacles performance, using a kind of adaptive threshold cascading linear support vector machines
Identify the CHT feature of different type barrier.Training set is formed to all sample extraction CHT features, using Linear SVM to it
Classify, obtains Hyperplane classification device.Each sample has an output valve i.e. obstacle identity m about the classifier,
Its calculating is shown below:
Wherein, w*, b*It is the parameter of Hyperplane classification device respectively；xnFor the CHT feature vector of n-th of sample.In order to make this
Output valve has two-dimensional visualization characteristic, and each output valve is added one-dimensional 0-1 uniform random number, is mapped to two-dimentional sky
Between.After the completion of first layer classifier training, the sample for being easy classification is weeded out according to the method for adaptive threshold, reservation is difficult to point
From training sample of the sample as second layer classifier.And so on, to the last one layer of classification, final acquired disturbance species
Type judges whether to anchor simultaneously.
If it is suitable for berthing that the result that the Cluster Analysis module 16 is analyzed, which is current environment, moors a boat described in calling and control mould
Block 3, the control module 3 of mooring a boat is corresponding to call manual control module 31 or automatic control module 32 to carry out manually controlling shape
Mooring a boat under mooring a boat under state or automatic control state；If the result that the Cluster Analysis module 16 is analyzed be current environment not
It is suitable for berthing, then the control module 3 of mooring a boat is never called, without mooring a boat.
Above-mentioned CHT feature is a kind of a kind of textural characteristics with compared with high rule complexity.The 8 neighborhood CHT that radius is 1 are special
It is as shown in Figure 3 to levy extraction process.And as shown in figure 4, pixel p is calculated to be currentcWith the spatial relation graph between neighborhood point, according to
Secondary number clockwise are as follows: p0~p7；Fig. 5 show the gray scale amplitude of current pixel point.According to the magnitude relation, picture can be obtained
Symbol difference value between vegetarian refreshments, such as formula (1), (2) are shown:
T=t (s (pc-p0),s(pc-p1),…,s(pc-p7)) (1)
Wherein:
In formula, the joint distribution function of t () function representation symbol difference value；s(pc-pi) indicate current pixel point pcWith i-th
Neighborhood point piBetween symbol difference value.As shown in fig. 6, being all corresponding symbol difference values of neighborhood point.Fig. 7 gives CHT
The weight template of feature calculation, at this time current pixel point pcCorrespondence CHT value can be calculated by formula (3):
In formula, N is neighborhood territory pixel point quantity, and R is that CHT calculates radius, and the CHT value that can be calculated current pixel point is 47.
It is not difficult to find out that relativeness of the CHT value only between pixel is related, and it is unrelated with specific pixel amplitude.
Claims (2)
1. a kind of obstacle recognition method of the ship mooring system based on panoramic looking-around, the ship based on panoramic looking-around stop
Pool system includes main control module, the battery connecting with main control module and control module of mooring a boat, connect with main control module
Display module, ship's speed sensor, gyro sensor and four cameras being connect with main control module, the master control molding
Block includes master controller, the power circuit being connected respectively with master controller, memory, four figures connecting with four cameras
Two signal conditions being connected with signal conditioning module and respectively with the ship's speed sensor and gyro sensor as correction
Circuit, the main control module also have Cluster Analysis module, and the memory is connect with Cluster Analysis module, the cluster point
Analysis module is connect with control module of mooring a boat；Four cameras are separately mounted to the front, rear, left and right outer surface of hull；
It is characterized by: the obstacle recognition method the following steps are included:
Firstly, four cameras acquire the real-time pictures of front, rear, left and right under hull and ship respectively, and real-time pictures are transmitted to
Main controller；
The ship's speed sensor, gyro sensor acquire the travel speed of ship respectively and operation orientation is believed as ship
Breath；
Four image rectifications and signal conditioning module is corrected to four collected real-time pictures of camera and signal
Then four sub-pictures after correction are carried out splicing again, obtain the panoramic picture around hull by processing；
The display module shows the panoramic picture around hull；
Described two signal conditioning circuits by ship's speed sensor and the collected ship information of gyro sensor be corrected with
Signal processing obtains the ship speed of service and specific orientation；
The collected ship information is stored in the memory and provides the number of clustering to the Cluster Analysis module
According to i.e. panoramic picture；
The Cluster Analysis module is adopted according to storing in memory and providing panoramic picture barrier feature to Cluster Analysis module
Different type barrier is identified with adaptive threshold cascading linear support vector machines, and is berthed the safety of environment to current preparation
Property, convenience favorable characteristics clustering algorithm analyzed, to judge whether to need to call to moor a boat control module, moored
Ship.
2. obstacle recognition method as described in claim 1, it is characterised in that: cluster module working method is as follows: using and change
Barrier feature T into CHT feature extraction panoramic looking-around image,
T=G (pc)t(s(pc-p0),s(pc-p1),…,s(pc-p7))
Wherein,
In formula, the joint distribution function of t () function representation symbol difference value；s(pc-pi) indicate current pixel point pcWith the i-th neighborhood
Point piBetween symbol difference value, G (pc) it is standard normal gauss of distribution function；
Using the CHT feature of adaptive threshold cascading linear support vector machines identification different type barrier；
Training set is formed to all sample extraction CHT features, is classified using Linear SVM to it, Hyperplane classification is obtained
Device；
Each sample has an output valve i.e. obstacle identity m, calculating to be shown below about Hyperplane classification device,
Wherein, w*, b*It is the parameter of Hyperplane classification device respectively；xnFor the CHT feature vector of n-th of sample, by each output valve
One-dimensional 0-1 uniform random number is added, is mapped to two-dimensional space, it, will be according to adaptive after the completion of first layer classifier training
The method of threshold value rejects training sample of the sample retained after the sample of part as second layer classifier, and so on, until most
Later layer classification, final acquired disturbance species type judge whether to anchor simultaneously.
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