CN102622487B - A kind of automatic ticket checker (gate) sensor placement Computer Aided Design & Imitation system - Google Patents
A kind of automatic ticket checker (gate) sensor placement Computer Aided Design & Imitation system Download PDFInfo
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- CN102622487B CN102622487B CN201210075595.8A CN201210075595A CN102622487B CN 102622487 B CN102622487 B CN 102622487B CN 201210075595 A CN201210075595 A CN 201210075595A CN 102622487 B CN102622487 B CN 102622487B
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Abstract
The invention discloses a kind of automatic ticket checker (gate) sensor placement Computer Aided Design & Imitation system, comprise the following steps: (card) people that takes ticket under taking a large amount of different specified conditions makes example storehouse by the video file of automatic ticket checker (gate); By using Video Quality Metric software, the conversion of original video example storehouse is made sample set by using simulation software that video clip is combined sensor placement's coordinate file of specifying; The function utilizing simulation software to emulate emulates sample set, generates training set; Training set is trained thus sets up neural network model.Set up test set; By using in simulation software, test set being tested, obtaining the percent of pass destination file of this cover sensor placement design.The present invention adopt computer simulation technique effectively reduce sensor placement design in manpower, financial resources and material resources.
Description
Technical field
The present invention relates to a kind of automatic ticket checker (gate) sensor placement Computer Aided Design & Imitation system, belong to automatic ticket checker and gate inhibition's design field.
Background technology
(card) people that in actual life, takes ticket is very complicated by the behavior produced time automatic ticket checker (gate), the behavior such as often can run into (card) people leap that takes ticket, lower brill, trail.In order to effectively examination takes ticket, whether (card) people is legal passes through, or carrying child, luggage, pet are passed through, the necessary sensor installation system of automatic ticket checker (gate), and adopt special sensing algorithm, the behavior that (card) people that takes ticket passes through is judged.Simultaneously, there is very large limitation in traditional automatic ticket checker (gate) sensor placement, rely on designer completely and pass through experience accumulation, at the ad-hoc location sensor installation of automatic ticket checker (gate), this method wastes time and energy, once complete sensor placement's design, just must recruit employ a large amount of personnel ceaselessly by automatic ticket checker (gate) model machine with stream of people's environment that is virtually reality like reality, and final product is not because being detected by real human flow, and there is unforeseen problem; And at present especially in field of track traffic, the mode that domestic and international market adopts is the demand according to passenger flow and different user, the newly-built rail line of every bar generally all adopts dissimilar automatic ticket checker, this just proposes challenge to the traditional design mode of automatic ticket checker sensor, and traditional manual type cannot meet a large amount of new product needs increased again.
Summary of the invention
The object of the invention is to, thering is provided a kind of adopts Computer Simulation to produce 1,000,000 grades of stream of people's samples, and according to newly-designed sensor placement, automatically generate by artificial neural network (card) people behavior that takes ticket and screen algorithm, make traditional handicraft need the model machine development cost of several moon, hundreds of people, unit up to a million, once shorten to several days, automatic ticket checker (gate) the sensor placement Computer Aided Design & Imitation system that can finish the work of several expert engineer, several notebook computers.
For solving the problems of the technologies described above, the present invention adopts following technical scheme: a kind of automatic ticket checker (gate) sensor placement Computer Aided Design & Imitation system, comprises the following steps:
S1, (card) people that takes ticket under taking a large amount of different specified conditions makes example storehouse L by the video file of automatic ticket checker (gate);
S2, is converted into video clip M by using Video Quality Metric software by original video example storehouse L;
S3, to combine by using simulation software a set of sensor placement coordinate file XY specified and adds software inhouse in the lump to and make sample set N by video clip M;
S4, the function utilizing simulation software to emulate emulates sample set N, generates the data streaming file training set P of special format;
S5, by using the function of the neural metwork training in simulation software, training data streaming file training set P thus setting up neural network model.
S6, sets up data streaming file test set Q by the step of above S1 ~ S4;
S7, by using the function of the neural network test in simulation software, in the neural network model set up after step S5 completes, data streaming file test set Q is tested, obtain (card) people percent of pass destination file F that takes ticket of each attribute of this cover sensor placement design.
The step of Video Quality Metric software is:
S21, original video example storehouse L pass through setting and the file size setting of specific threshold, become black white binarization video clip M from color video file translations;
S22, extracts the Coordinate generation file of automatic ticket checker (gate) in original video example storehouse L.
The step of simulation software is:
S31, input pickup layout coordinate file XY, judge whether editor's training set sample; Be then enter step S32-S34, set up training set P; No, then enter step S32-S34 and set up test set Q.
S32, training video file set storage directory after selection binaryzation;
S33, edits the Parameter File T of this video clip and imports;
S34, imports the gate coordinate in this video and forms sample set N; Enter step S41;
S41, emulates training set P or test set Q; Enter step S51;
S51, neural network is trained training set P simulation result;
S52, produces neural network model; Enter step S71;
S71, the neural network under this model is tested test set simulation result;
S72, produces percent of pass destination file F.
The present invention's computing machine can be perfect gradually example storehouse in sample emulation, the method of neural metwork training test, (card) people percent of pass form document that takes ticket under horizontal a few cover automatic ticket checker (gate) sensor placements design proposal can be drawn, then, these forms of longitudinal comparison again, after considering, the design proposal that a set of sensor placement scheme is new type auto ticket checking machine (gate) can be selected.
Pass through foregoing description, visible, the method is used to design new type auto ticket checking machine (gate), not only do not employ manpower up to a hundred carrys out testing sensor layout rationality by gate, unit up to a million is not spent to make model machine yet, just in this cover Computer Aided Design & Imitation system, revise sensor placement's parameter, just can obtain corresponding (card) people percent of pass form document that takes ticket, thus can determine whether can as sensor placement's design proposal of novel gate.
Than traditional sensors layout design method, advantage of the present invention is apparent, greatly improve work efficiency, significantly save the input of manpower and materials, the more important thing is that the rationality to the design of automatic ticket checker (gate) sensor placement proposes method and the foundation of perspective study.
Accompanying drawing illustrates:
Fig. 1 is system architecture diagram of the present invention;
Fig. 2 is working-flow figure of the present invention;
Fig. 3 is Video Quality Metric software workflow figure of the present invention;
Fig. 4 is simulation software of the present invention workflow diagram.
Below in conjunction with the drawings and specific embodiments, the present invention is further illustrated.
Embodiment
Embodiments of the invention:
As Figure 1-4, example is: be subway and design a new type auto ticket checking machine, one of to require being have anti-pinch passenger adjunct (such as draw-bar box etc.) function.This is used to of the present invention to execute step as follows:
First step: generate the passenger's percent of pass destination file F1 under an a set of automatic ticket checker sensor design scheme applied.Be divided into following several little step:
As shown in Figure 2:
S1, take a large amount of passenger and make original video example storehouse L by the video file of gate.
This step can be selected to take at certain subway station, also can select to build scene in intra-company, utilizes own automatic ticket checker, asks employee to work together and replaces passenger to be taken by gate.This large quantities of video file as source document, will be made into library file, can directly call afterwards, and without the need to again taking, but the file that constantly can add new element is to enrich storehouse body.
S2, open Video Quality Metric software, original video example storehouse L is converted into the video clip M of special format.
The catalogue that file after this step only need set the catalogue and conversion needing the source document transformed to deposit is saved and some parameters, then click " conversion " key, software automatically performs task.
S3, open simulation software, a set of sensor placement coordinate file XY combined by video clip M on organic type adds software inhouse in the lump to and makes sample set N.
This step method is similar to S2, and the good parameter of option and installment on software interface, click a key, software automatically performs task.
S4, the function utilizing simulation software to emulate emulate sample set N, generate the data streaming file training collection P of special format.
This step method is similar to S2, S3, and the good parameter of option and installment on software interface, click a key, software automatically performs task.
S5, by using the function of the neural metwork training in simulation software, data streaming file training collection P being trained thus sets up neural network model.
This step method is similar to S2, S3, S4, and the good parameter of option and installment on software interface, click a key, software automatically performs task.
S6, method establishment data streaming file test set Q with above S1 ~ S4.
S7, by using the function of the neural network test in simulation software, in the neural network model set up after S5 does, passenger's percent of pass destination file F1 of each attribute of this cover sensor placement design obtains to the Q test of data streaming file test set.
As shown in Figure 3:
The step of Video Quality Metric software is:
S21, original video example storehouse L pass through setting and the file size setting of specific threshold, become black white binarization video clip M from color video file translations;
S22, extracts the Coordinate generation file of automatic ticket checker (gate) in original video example storehouse L.
As shown in Figure 4:
The step of simulation software is:
S31, input pickup layout coordinate file XY, judge whether editor's training set sample; Be then enter step S32-S34, set up training set P; No, then enter step S32-S34 and set up test set Q.
S32, training video file set M storage directory after selection binaryzation;
S33, edits the Parameter File T of this video clip and imports;
S34, imports the gate coordinate in this video and forms sample set N; Enter step S41;
S41, emulates training set P or test set Q; Enter step S51;
S51, neural network is trained training set P simulation result;
S52, produces neural network model; Enter step S71;
S71, the neural network under this model is tested test set simulation result;
S72, produces percent of pass destination file F1.
Second largest step: generate one should require newly-designed a set of automatic ticket checker sensor design scheme under passenger's percent of pass destination file F2.The several little step performed can not be done with S2 ~ S7, S1 in first step, repeats no more here.
The third-largest step: compare the index in F1 and F2 destination file, particularly " adjunct ", if the data in F2 comparatively F1 have dropped, that illustrates that new departure is not as existing program, otherwise, then illustrate, new departure function in this respect has improvement, can consider the final plan this scheme designed as the sensor placement of new type auto ticket checking machine.
In a word, the present invention can be applied in passenger that various automatic ticket checker (gate) produces result of passing through and depends on the precision that sensor placement designs completely.The present invention is just available to sensor placement's method for designing of high effectively, the high automatic ticket checker accurately of slip-stick artist one.As shown in Figure 1, its Neutron module 1 is the original video files of taken of passengers by automatic ticket checker, is disposable action, does not need all to do this link at every turn, but can not timing non-quantitative to video set do supplement and perfect; Submodule 2 is Video Quality Metric software of the present invention, and its internal work flow process figure is shown in Fig. 3.
The main source code of part is as follows:
Submodule 3 is a whole set of sensor design scheme; Submodule 4 is simulation software of the present invention, and its internal work flow process figure is shown in Fig. 4.Wherein M1, M2 can be identical, and certain T1, T2 are also just identical, but test set should be the subset of training set usually.The main source code of part is as follows:
Submodule 5 is the final purpose conclusion content of the present invention, this different file obtained by comparing Ge Tao sensor placement design proposal, and obtain preferably sensor placement's design proposal as sensor placement's design proposal of new type auto ticket checking machine.Whole workflow diagram of the present invention is shown in Fig. 2.
Claims (1)
1. automatic ticket checker (gate) sensor placement Computer Aided Design & Imitation system, is characterized in that: comprise the following steps:
S1, (card) people that takes ticket under taking a large amount of different specified conditions makes example storehouse L by the video file of automatic ticket checker (gate);
S2, by using Video Quality Metric software that original video example storehouse L is converted into video clip M,
The step of described Video Quality Metric software is:
S21, original video example storehouse L pass through setting and the file size setting of specific threshold, become black white binarization video clip M from color video file translations;
S22, extracts the Coordinate generation file of automatic ticket checker (gate) in original video example storehouse L;
S3, to combine by using simulation software a set of sensor placement coordinate file XY specified and adds software inhouse in the lump to and make sample set N by video clip M;
S4, the function utilizing simulation software to emulate emulates sample set N, generates the data streaming file training set P of special format;
S5, by using the function of the neural metwork training in simulation software, training data streaming file training set P thus setting up neural network model;
S6, sets up data streaming file test set Q by the step of above S1 ~ S4;
S7, by using the function of the neural network test in simulation software, in the neural network model set up after step S5 completes, data streaming file test set Q is tested, obtain (card) people percent of pass destination file F that takes ticket of each attribute of this cover sensor placement design;
The step of described simulation software is:
S31, input pickup layout coordinate file XY, judge whether editor's training set sample; Be then enter step S32-S34, set up training set P; No, then enter step S32-S34 and set up test set Q;
S32, training video file set storage directory after selection binaryzation;
S33, edits the Parameter File T of this video clip and imports;
S34, imports the ticket checking machine coordinate in this video and forms sample set N; Enter step S41;
S41, emulates training set P or test set Q; Enter step S51;
S51, neural network is trained training set P simulation result;
S52, produces neural network model; Enter step S71;
S71, the neural network under this model is tested test set simulation result;
S72, produces percent of pass.
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Citations (2)
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| CN101482981A (en) * | 2008-04-09 | 2009-07-15 | 天津市先志越洋科技有限公司 | License event recognition method for special shearing type door gate machine used in urban track traffic |
| CN101826200A (en) * | 2010-04-02 | 2010-09-08 | 北京交通大学 | Method for evaluating operating effect of urban track traffic hub |
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN101482981A (en) * | 2008-04-09 | 2009-07-15 | 天津市先志越洋科技有限公司 | License event recognition method for special shearing type door gate machine used in urban track traffic |
| CN101826200A (en) * | 2010-04-02 | 2010-09-08 | 北京交通大学 | Method for evaluating operating effect of urban track traffic hub |
Non-Patent Citations (2)
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| 城市轨道交通中闸机智能识别系统及其识别技术的研究;曲日;《中国优秀博硕士学位论文全文数据库(博士) 信息科技辑》;20060715(第7期);正文第29页倒数第1段—第42页倒数第1段 * |
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