CN114160447A - Advanced machine inspection system and method - Google Patents
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- CN114160447A CN114160447A CN202111380942.3A CN202111380942A CN114160447A CN 114160447 A CN114160447 A CN 114160447A CN 202111380942 A CN202111380942 A CN 202111380942A CN 114160447 A CN114160447 A CN 114160447A
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- 238000007689 inspection Methods 0.000 title claims abstract description 35
- 238000000034 method Methods 0.000 title claims abstract description 28
- 238000007789 sealing Methods 0.000 claims abstract description 21
- 238000012795 verification Methods 0.000 claims description 16
- 238000004891 communication Methods 0.000 claims description 12
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
- B07C5/34—Sorting according to other particular properties
- B07C5/342—Sorting according to other particular properties according to optical properties, e.g. colour
- B07C5/3422—Sorting according to other particular properties according to optical properties, e.g. colour using video scanning devices, e.g. TV-cameras
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
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Abstract
The application relates to an advanced machine inspection system and a method, which belong to the technical field of safety inspection, and the system comprises: the first image acquisition module is used for acquiring a machine check image of the luggage; the image classification module is used for classifying the machine-detected images and outputting classification instructions; the luggage sorting module is used for sorting the luggage based on the sorting instruction and obtaining normal luggage and problem luggage; the identification sealing module is used for receiving the problem luggage and sealing the problem luggage; the luggage identification module is used for identifying the sealed problem luggage and generating an identification result; and the alarm module is used for generating alarm information based on the identification result. The method and the device have the effects of automatically sorting, marking and intercepting the luggage needing unpacking inspection, thereby improving the overall clearance efficiency of passengers.
Description
Technical Field
The present application relates to the field of security detection technologies, and in particular, to an advanced machine inspection system and method.
Background
At present, with the continuous enhancement of external communication and cooperation between countries, international trade is developed more and more rapidly; in addition, international traffic such as international travel is more frequent, and a large number of passengers enter and exit every day, wherein some passengers may carry some prohibited articles, so that checking the consigned luggage of the passengers entering and exiting is very important.
Most of the existing inspection methods adopt a more traditional mode, namely that after the luggage is carried off from the airplane, the luggage is simply sorted and transmitted to a luggage turntable and then is extracted by passengers; the exit is checked through an X-ray machine, the staff beside the X-ray machine judges manually, and the box is opened for checking when illegal articles exist. Through this kind of mode, the staff is difficult to distinguish the luggage that carries contraband, needs the check one by one, opens the case again and examines to the inefficiency ratio is lower.
Disclosure of Invention
In order to reduce the difficulty of distinguishing problem luggage from normal luggage by workers and improve the passing efficiency, the application provides an advanced machine inspection system and method.
In a first aspect, the present application provides an advanced machine inspection system, which adopts the following technical scheme:
an advanced screening system comprising:
the first image acquisition module is used for acquiring a machine check image of the luggage;
the input end of the image classification module is connected with the output end of the first image acquisition module and is used for classifying the machine-detected images and outputting a classification instruction;
and the input end of the luggage sorting module is connected with the output end of the image classification module and is used for sorting the luggage based on the classification instruction and obtaining normal luggage and problem luggage.
The identification sealing module is used for receiving the problem luggage and sealing the problem luggage;
the luggage identification module is used for identifying the sealed problem luggage and generating an identification result;
and the input end of the alarm module is connected with the output end of the luggage identification module and is used for generating alarm information based on the identification result.
By adopting the technical scheme, the first image acquisition module acquires the machine-inspected image of the luggage, then the image is sent to the image classification module, the image classification module judges the received machine-inspected image, corresponding classification instructions are output according to the judgment result, then the luggage sorting module sorts the luggage according to the received classification instructions, and the luggage is divided into two categories of problem luggage and normal luggage. The identification is executed and is sealed the module and is executed and seal the problem luggage that the sorting module conveying was come, the identification is executed and is sealed the module and will be executed and sealed good luggage and send luggage identification module to, luggage identification module discerns the luggage of receiving, and judge whether be problem luggage, if no, then normally current, otherwise, send the recognition result for alarm module, alarm module is after receiving the recognition result, generate alarm information, thereby remind the staff, through this process, the degree of difficulty of distinguishing luggage has been reduced, the work load has been reduced, clearance efficiency has been improved.
Preferably, the method further comprises the following steps:
the luggage scanning module is used for reading luggage strips preset on a luggage box and acquiring passenger information, wherein the passenger information comprises an initial face image;
and the luggage binding module is used for performing association binding on the initial face image and the machine check image.
By adopting the technical scheme, the luggage scanning module acquires the passenger information by scanning the luggage strip, wherein the passenger information comprises an initial face image, a name and the like of a passenger; and then the baggage binding module performs associated binding on the obtained initial face image and the previously obtained machine check image. Therefore, the problem luggage and the passengers are bound, the subsequent problem luggage interception is facilitated, and the working efficiency is improved.
Preferably, the method further comprises the following steps:
and the luggage adjusting module is used for adjusting the distance and the posture of the luggage.
Through adopting above-mentioned technical scheme, luggage is all comparatively chaotic after unloading from the aircraft, before sealing, also need adjust the luggage gesture, is convenient for seal, and luggage adjustment module is at first to carry out the roll adjustment to the luggage that unloads to avoid as far as possible because luggage mixes when leading to first image acquisition module to acquire the luggage image together, the possibility that the inaccurate condition of luggage image acquisition takes place. And the posture of the luggage can be adjusted, so that the luggage can be placed, the sealing is convenient, the following steps can be better executed, and the working efficiency is improved.
Preferably, the method further comprises the following steps:
a second image acquisition module for acquiring a first baggage image of the problematic baggage;
a face image acquisition module, configured to acquire the initial face image corresponding to the first baggage image as a first face image;
the face image recognition module is used for acquiring a second face image of the passenger;
the first image judgment module is connected with the output end of the face image recognition module at one input end and the face image acquisition module at the other input end, and is used for judging whether the second face image is matched with the first face image or not and acquiring a first matching result;
and the input end of the first warning module is connected with the output end of the first image judgment module, and when the first matching result is successful, the first warning module is used for outputting first warning information.
By adopting the technical scheme, firstly, the second image acquisition module acquires a first baggage image of problematic baggage and sends the first baggage image to the identification and verification module, then the face image acquisition module acquires an initial face image corresponding to the first baggage image as a first face image and sends the first face image to the first image judgment module, and the face image identification module acquires a second face image of a passenger who takes the baggage and leaves and sends the second face image to the first image judgment module. The first image judging module matches the second face image with the first face image, judges whether the first face image is matched with the second face image or not and obtains a first matching result.
When the first matching result is successful, the passenger associated with the problem luggage is found through the proof, the first warning module outputs alarm information at the moment, and the worker can be prompted, so that the passenger bound with the problem luggage can be accurately intercepted, and the recognition effect is improved.
Preferably, the baggage identification module includes:
the third image acquisition module is used for acquiring a second luggage image of the luggage;
and the input end of the second image judgment module is connected with the third image acquisition module and is used for judging whether the second luggage image contains a customs supervision belt which is sealed or not, and obtaining and outputting a judgment result.
By adopting the technical scheme, the third image acquisition module acquires a second luggage image of the luggage and sends the second luggage image to the second image judgment module. And the second image judging module judges whether the second luggage image contains a customs supervision band or not, and obtains and outputs a judgment result. Therefore, the problem luggage can be identified, the identification accuracy is improved, and the possibility of missing detection of the problem luggage is reduced.
Preferably, the baggage identification module further comprises:
an input end of the identification and verification module is connected with an output end of the second image judgment module, and the other input end of the identification and verification module is connected with a third image acquisition module, and when the judgment result is yes, the identification and verification module is used for judging whether the second baggage image is matched with the first baggage image or not and acquiring a second matching result;
and the input end of the second warning module is connected with the output end of the identification and verification module, and when the judgment result and the second matching result are both yes, the second warning module is used for outputting second warning information.
By adopting the technical scheme, when the judgment result is yes, whether the second baggage image is matched with the first baggage image or not is judged based on the received second baggage image and the first baggage image, and a second matching result is obtained.
And outputting second alarm information when the judgment result and the second matching result are both yes. Therefore, the obtained custom customs supervision band identification result specially made by customs can be verified, and the false alarm rate is reduced.
Preferably, the method further comprises the following steps:
the output end of the video shooting module is connected with a network communication module, and the video shooting module is used for shooting the problem luggage after the problem luggage is identified, generating an evidence video and sending the evidence video to the network communication module;
and the network communication module is used for sending the evidence video to a terminal.
Through adopting above-mentioned technical scheme, after discerning problem luggage, the video is shot the module and can be shot to problem luggage and make a video recording, generates the evidence video recording to can send through network communication module, the user can receive and save the evidence video recording through equipment such as terminal, thereby provides support for subsequent investigation.
On the other hand, the application provides an advanced machine inspection method, which adopts the following technical scheme:
an advanced machine inspection method, comprising:
acquiring a machine check image of the luggage;
classifying the machine-detected images and outputting a classification instruction;
and sorting the luggage based on the classification instruction, and obtaining normal luggage and problem luggage.
Sealing the problem luggage;
identifying the sealed problem luggage and generating an identification result;
and generating alarm information based on the identification result.
By adopting the technical scheme, after the luggage is unloaded from the airplane, the machine-detected image of the luggage is obtained when the luggage passes through the X-ray machine, the machine-detected image is sent to the centralized image judging platform, the platform judges the machine-detected image and outputs a corresponding classification instruction, and the conveyed luggage is classified according to the obtained classification instruction and is divided into normal luggage and problem luggage, so that the workload is reduced, and the working efficiency is improved.
After the letter sorting is accomplished, execute to seal problem luggage, when the passenger draws problem luggage and prepares to leave, discern the judgement to the passenger that carries problem luggage and problem luggage, and generate the recognition result, when the recognition result is normal luggage, then normally pass, if the recognition result is problem luggage, then generate alarm information, remind the staff, the problem luggage of avoiding carrying forbidden article as far as possible leaves the customs, causes the potential safety hazard.
Preferably, the obtaining of the normal baggage and the problem baggage further comprises:
acquiring a first baggage image of the problematic baggage;
acquiring the initial face image corresponding to the first baggage image as a first face image;
acquiring a second face image of the passenger;
judging whether the second face image is matched with the first face image or not, and obtaining a first matching result;
and outputting first alarm information when the first matching result is that the matching is successful.
By adopting the technical scheme, after the problem luggage and the normal luggage are obtained, the first luggage image of the problem luggage is firstly obtained, then the initial face image corresponding to the first luggage image is obtained and is used as the first face image, then the second face image of the passenger is obtained, then whether the second face image is matched with the first face image is judged, and the first matching result is obtained.
And outputting first alarm information when the first matching result is that the matching is successful. Therefore, the staff is reminded to bring the passengers and the problem luggage to the designated area for unpacking inspection, the difficulty of distinguishing the luggage is reduced, the workload is reduced, and the clearance efficiency is improved.
To sum up, the application comprises the following beneficial technical effects:
1. the machine-detected image is acquired through the first image acquisition module, then the image classification module classifies the machine-detected image, then the luggage sorting module sorts luggage according to the classification instruction output by the image classification module to obtain normal luggage and problem luggage, then the luggage sealing module seals the problem luggage, the luggage identification module identifies the problem luggage to be sealed, and after the problem luggage is identified, the alarm module generates alarm information. Through applying for sealing problem luggage to problem luggage is discerned in the exit, can greatly reduced discern the degree of difficulty of problem luggage and normal luggage, and normal luggage and problem luggage can be fine are distinguished, reduce the loaded down with trivial details nature of luggage inspection, not only can avoid the problem luggage that has forbidden article to be taken out the customs, also can avoid the appearance of this kind of condition of latency overlength as far as possible, improves current efficiency.
Drawings
Fig. 1 is a block diagram of an overall structure of an advanced machine inspection system according to an embodiment of the present disclosure;
FIG. 2 is a block diagram of a baggage binding configuration according to an embodiment of the present application;
FIG. 3 is a block diagram of a baggage reconciliation module according to an embodiment of the present application;
FIG. 4 is a block diagram of a face recognition system according to an embodiment of the present application;
FIG. 5 is a block diagram illustrating an embodiment of the present application for determining whether a customs surveillance zone is present in a second baggage image;
FIG. 6 is a block diagram of an embodiment of the present application for identification verification;
FIG. 7 is a block diagram of an embodiment of the present application in which evidence video is captured and stored;
FIG. 8 is a schematic overall flow chart of a prior machine inspection method provided herein;
fig. 9 is a detailed flowchart illustrating baggage identification and interception in an advanced screening method according to the present application.
Description of reference numerals:
1. a first image acquisition module; 2. an image classification module; 3. a baggage sorting module; 4. identifying a sealing module; 5. a baggage identification module; 6. an alarm module; 7. a baggage scanning module; 8. a luggage binding module; 9. a baggage adjustment module; 10. a second image acquisition module; 11. a face image acquisition module; 12. a face image recognition module; 13. a first image judgment module; 14. a first warning module; 15. a third image acquisition module; 16. a second image judgment module; 17. an identification verification module; 18. a second warning module 19 and a video shooting module; 20. and a network communication module.
Detailed Description
The present application is described in further detail below with reference to figures 1-9.
The embodiment of the application discloses an advanced machine inspection system.
Referring to fig. 1, the advanced screening system includes:
the first image acquisition module 1 is used for acquiring a machine check image of the luggage;
the image classification module 2 is used for classifying the machine-detected images and outputting classification instructions;
and the luggage sorting module 3 is used for sorting the luggage based on the sorting instruction and obtaining normal luggage and problem luggage.
The mark sealing module 4 is used for receiving the problem luggage and sealing the problem luggage;
the luggage identification module 5 is used for identifying the sealed problem luggage and generating an identification result;
and the alarm module 6 is used for generating alarm information based on the identification result.
When the luggage is unloaded from the airplane and then put on the luggage line, the luggage is transported through the conveyor belt, and when the luggage passes through the X-ray machine, the first image acquisition module 1 acquires the machine inspection image of the luggage, wherein the machine inspection image refers to the image of the luggage shot by the X-ray machine and mainly shows whether forbidden articles exist in the luggage.
The first image acquisition module 1 sends the acquired machine-detected image to the image classification module 2, after the image classification module 2 receives the machine-detected image, the luggage is classified into two categories by judging whether forbidden articles exist in the luggage, if the forbidden articles exist, the luggage is classified as problem luggage, and if the forbidden articles exist, the luggage is normal luggage.
The separation process of the image classification module 2 can be screening in a manual selection mode, the image classification module 2 transmits the received machine-detected image to a display, and then whether forbidden articles exist in the machine-detected image is judged manually. If yes, selecting the corresponding machine inspection image and classifying the machine inspection image into a problem baggage picture, and if not, selecting the corresponding machine inspection image and classifying the machine inspection image into a normal baggage picture. And then outputting a classification instruction according to the problem baggage picture and the normal baggage picture.
Meanwhile, the centralized image reviewing system identifies the face image information of the passenger corresponding to the luggage classified as problem luggage in the machine check image.
The baggage sorting module 3 sorts the baggage according to the received sorting instructions, for which the baggage sorting module 3 sorts it onto a further line, which may be a spare line, for example. If the luggage is normal luggage, the luggage sorting module 3 does not sort the luggage, and the luggage normally passes to the luggage turntable and can be extracted by passengers. Thereby reducing the manual sorting part, improving the efficiency and saving the manpower.
When the luggage is judged to be the problem luggage and sorted to the standby line, the mark sealing module 44 seals the conveyed problem luggage in a way that a customs supervision belt specially made by customs is wound on the luggage case, the process is finished by a full-automatic unattended packer, and after the sealing is finished, the conveyor belt conveys the sealed problem luggage to the position of the luggage identification module 5.
The luggage identification module 5 identifies the luggage transmitted, the luggage identification module 5 acquires the image of the luggage, and judges whether the acquired image has a customs supervision band or not based on an image algorithm, if not, the acquired identification result is normal luggage, otherwise, the identification result is problem luggage. The baggage identification module 5 then sends the identification result to the alarm module 6.
Alarm module 6 generates the warning suggestion after receiving the recognition result, and this suggestion can have different forms, for example the red light of short buzzing and scintillation to carry out obvious suggestion to problem luggage, be convenient for distinguish problem luggage and normal luggage, and in time discern, thereby indicate to the staff that problem luggage is, avoid having the luggage of forbidden article to be taken away from the customs, consequently bring safety problem and potential safety hazard. If the green light is used, the luggage is proved to be normal luggage, and the luggage can normally leave the security inspection opening.
In another embodiment, before baggage identification, baggage binding is required to facilitate the implementation of the subsequent scheme, and referring to fig. 2, the baggage binding process is mainly completed by the following modules:
the luggage scanning module 7 is used for reading luggage strips preset on a luggage case and acquiring an initial face image;
and the luggage binding module 8 is used for performing association binding on the initial face image and the machine check image.
Wherein, the output end of the luggage scanning module 7 is electrically connected with the input end of the luggage binding module 8.
Luggage can pass through luggage scanning module 7 after unloading from the aircraft, and luggage scanning module 7 acquires passenger information through scanning the luggage strip, and wherein, the luggage strip is when carrying out the luggage consignment, is fixed in the mark strip on the luggage, has bar code or two-dimensional code on the mark strip, can acquire passenger information through reading bar code or two-dimensional code. The passenger information comprises an initial face image, a name and the like of the passenger, the luggage scanning module 7 can be code scanning equipment, and then the initial face image is sent to the luggage binding module 8; the luggage binding module 8 binds the received machine check image and the initial face image in a correlation mode to realize binding of luggage and passengers, so that the belonger of the luggage can be determined quickly when the problem luggage is detected, and the efficiency of finding the problem luggage and the belonger is improved.
Further, in order to improve the accuracy of the machine inspection image acquisition and to make the process of sealing the baggage more stable, referring to fig. 3, in another embodiment, the machine inspection system further includes the following modules:
and the luggage adjusting module 9 is used for adjusting the distance and the posture of the luggage.
Before luggage needs to carry out the acquisition of machine-detected image through the X-ray machine, luggage adjustment module 9 adjusts the distance between the luggage, thereby avoid the distance between the luggage too near, the machine-detected image that leads to obtaining is not clear enough or chaotic, influence the work of follow-up module, carry out the roll adjustment and mainly accomplish by the roll adjustment device on the conveyer belt, the roll adjustment device here comprises fan-shaped laser scanner and roll adjustment belt, when detecting luggage, laser range finder top-down sends a sectorial range finding laser, measure the distance between the luggage, and adjust by the roll adjustment belt, the slew velocity of roll adjustment belt can be adjusted according to the distance between the luggage that records, and then can make the distance between the luggage on conveyer belt and the range finding belt change, make the distance between two adjacent luggage comparatively fixed.
After the X-ray machine, problem luggage needs to be sealed, and as some luggage possibly has a skew angle, the angle of the problem luggage can be adjusted through adjusting equipment or a mechanical arm arranged on two sides of a conveyor belt, the adjusting mode can be to acquire the image of the luggage, then whether the angle of the luggage in the image is the same as the preset angle is judged based on an image algorithm, and if the angle is different, an adjusting instruction is output to control the mechanical arm to adjust the luggage to the preset angle. Subsequent sealing can be convenient for to seal problem luggage more accurately, raise the efficiency.
Further, after the baggage and passenger are associated, further inspection is required to further improve the accuracy of the security check. Specifically, referring to fig. 4, in another embodiment, the method further includes:
a second image acquisition module 10 for acquiring a first baggage image of the problematic baggage;
a face image obtaining module 11, configured to obtain an initial face image corresponding to the first baggage image as a first face image;
the face image recognition module 12 is used for acquiring a second face image of the passenger;
a first image judgment module 13, one input end of which is connected with the output end of the face image recognition module 12, and the other input end of which is connected with the face image acquisition module 11, for judging whether the second face image is matched with the first face image, and obtaining a first matching result;
and the input end of the first warning module 14 is connected with the output end of the first image judging module 13, and when the first matching result is successful, the first warning module is used for outputting first warning information.
One input end of the first image judgment module 13 is electrically connected with the output end of the face image recognition module 12, the other input end of the first image judgment module 13 is connected with the face image acquisition module 11, and the output end of the first image judgment module 13 is electrically connected with the input end of the first warning module 14.
After the classification of the luggage is completed, the second image obtaining module 10 obtains a first luggage image of the luggage in question, and the face image obtaining module 11 obtains an initial face image corresponding to the first luggage image as a first face image, that is, a face image obtained by recognition in a luggage strip fixed on the luggage in question is obtained, and the face image is used as the first face image; when the passenger takes the problem baggage and leaves, the face image recognition module 12 obtains the face image of the passenger, that is, obtains the second face image, and sends the second face image to the first image judgment module 13. The first image judgment module 13 receives the first face image sent by the face image acquisition module 11, matches the second face image with the first face image, judges whether the matching between the second face image and the first face image is successful, and obtains a first matching result.
If the first match is successful, then the passenger photographed is the passenger associated with the problem baggage, thus proving a potential safety hazard. At this time, the first warning module 14 receives the first matching result and outputs warning information to remind the staff that the passenger associated with the problem baggage will pass through the passage.
Meanwhile, the alarm information can be a sound alarm or a light alarm, or both, such as a rapid buzzer alarm or a rapidly flashing red light. The problem luggage can be identified in time, all passenger luggage does not need to be checked, long-time waiting is avoided, and passing efficiency is improved.
Further, referring to fig. 5, the baggage identification module 5 includes the following modules:
a third image acquisition module 15 for acquiring a second baggage image of the baggage;
and the input end of the second image judging module 16 is connected with the third image obtaining module 15, and is used for judging whether the second luggage image contains a customs supervision band specially made by customs, and obtaining and outputting a judgment result.
Wherein, the output end of the third image obtaining module 15 is electrically connected with the input end of the second image judging module 16.
When the passenger leaves the turntable with the luggage, the third image acquisition module 15 firstly acquires a second luggage image of the luggage and sends the second luggage image to the second image judgment module 16, and when the problem luggage is identified to contain the customs supervision belt, the second image judgment module 16 acquires and outputs a judgment result. And support is provided for reminding workers to intercept the problem luggage and bringing the problem luggage to a specified area for unpacking inspection in the follow-up process.
The identification mode of the customs supervision belt can be that the second luggage image is compared with a preset image, the preset image contains the customs supervision belt, whether a part matched with the customs supervision belt in the preset image exists in the second luggage image or not is judged through an image algorithm, and if the part matched with the customs supervision belt exists in the second luggage image, the second luggage image is proved to contain the customs supervision belt. Similarly, the second baggage image may be manually inspected and a determination may be made as to whether a customs surveillance tape is present in the image.
Further, in order to reduce the false alarm rate, referring to fig. 6, the baggage identification module 5 further includes:
an identification and verification module 17, one input end of which is connected with the output end of the second image judgment module 16, and the other input end of which is connected with the third image acquisition module 15, and when the judgment result is yes, the identification and verification module is used for judging whether the second baggage image is matched with the first baggage image or not and acquiring a second matching result;
and the input end of the second warning module 18 is connected with the output end of the identification and verification module 17, and when the judgment result and the second matching result are both yes, the second warning module is used for outputting second warning information.
One input end of the identification and verification module 17 is electrically connected with the output end of the second image judgment module 16, the other input end of the identification and verification module is electrically connected with the third image acquisition module 15, and the input end of the second warning module 18 is electrically connected with the output end of the identification and verification module 17.
When the customs supervision band specially made for the customs on the luggage is successfully identified, the problem of identification error may exist, so that the obtained second luggage image is matched with the first luggage image, whether the two images are matched is judged, and the judgment result is obtained. The judgment mode can be judged by judging whether the appearance, the color and the size of the luggage are the same or not.
And when the judgment result and the second matching result are both yes, the fact that the luggage contains the monitoring band is proved, and meanwhile, the luggage is matched with the first luggage image is proved, the luggage is proved to be the problem luggage at the moment, and the second alarm information is output at the moment. Therefore, the obtained custom customs supervision band identification result specially made by customs can be verified, and the false alarm rate is reduced.
Further, for the subsequent query of the evidence of the problem baggage, referring to fig. 7, in another embodiment, the following modules are further included:
the video shooting module 19 is used for shooting the problem luggage after the problem luggage is identified and generating an evidence video;
and the network communication module 20 is used for sending the evidence video to the terminal.
After the problem luggage is identified, the video shooting module 19 may shoot and shoot the problem luggage to generate an evidence video, and send the evidence video to the network communication module 20, and then the network communication module 20 continues to send the evidence video to a terminal device, such as a mobile phone or a tablet computer, and the evidence video may be received and stored by the terminal device, thereby providing support for subsequent verification.
The implementation principle of the advanced machine inspection system in the embodiment of the application is as follows: firstly, acquiring a machine-check image of the luggage, classifying the luggage according to the machine-check image, outputting a classification instruction, sorting the luggage according to the classification instruction, sorting out normal luggage and problem luggage, controlling the problem luggage and passengers corresponding to the problem luggage, associating the first face image with the first luggage image, and sealing the problem luggage.
The method comprises the steps that a passenger obtains a second face image of the passenger when taking luggage, the passenger obtains the second face image of the passenger when taking problematic luggage and leaving, whether the first face image is matched with the second face image is judged, and when the first face image is matched with the second face image, a first matching result is output as success; and when the first face image and the second face image are not matched, outputting a first matching result as unsuccessful. When the matching result is unsuccessful, the passenger and the baggage pass normally, when the first matching result is successful, alarm information is output, meanwhile, a second baggage image of the baggage is obtained, whether a customs supervision band specially made by customs exists in the second baggage image is judged, and when the customs supervision band specially made by customs exists, the judgment result is obtained and output.
In order to reduce the false alarm rate of customs supervision band identification specially made for customs, judging whether the first luggage image is matched with the second luggage image, and outputting a second matching result if the first luggage image is matched with the second luggage image; and when the first baggage image and the second baggage image do not match, outputting that the second matching result is negative. And when the second matching result is negative, the alarm information is false alarm, and when the second matching result is positive, the identification result of the problem luggage is proved to be correct, and the alarm information is output. Therefore, the management of the luggage is further enhanced, unnecessary troubles are reduced, the false alarm rate is reduced, and the clearance efficiency is improved.
The embodiment of the application discloses a prior machine inspection method, which achieves the same technical effect as the prior machine inspection system.
Referring to fig. 8, the advanced machine inspection method includes:
s1, acquiring a machine inspection image of the luggage;
s2, classifying based on the machine-detected image, and outputting a classification instruction;
and S3, sorting the luggage based on the classification instruction, and obtaining normal luggage and problem luggage.
S4, receiving problem luggage and sealing;
s5, identifying the luggage based on the sealed problem and generating an identification result;
and S6, generating alarm information based on the identification result.
Specifically, in the checking process, firstly, machine-check images of the luggage to be checked are obtained, then the machine-check images are separated, a classification instruction is output according to the classified machine-check images, and meanwhile, the image centralized review system is used for carrying out image information on the problematic luggage and the face image information of the passenger corresponding to the problematic luggage. The baggage is then sorted according to the sorting instructions so that normal baggage and problem baggage can be obtained from the sorted screening images. Normal luggage normally passes at the main line, and the spare line is then sorted to the problem luggage, carries out subsequent processing to improve work efficiency.
After the letter sorting is accomplished, execute to seal problem luggage, when the passenger draws problem luggage and prepares to leave, discern the judgement to the passenger that carries problem luggage and problem luggage, and generate the recognition result, when the recognition result is normal luggage, then normally pass, if the recognition result is problem luggage, then generate alarm information, remind the staff, the problem luggage of avoiding carrying forbidden article as far as possible leaves the customs, causes the potential safety hazard.
Further, referring to fig. 9, after obtaining the normal baggage and the problem baggage, the method further includes:
s7, acquiring a first luggage image of the problem luggage;
s8, acquiring an initial face image corresponding to the first baggage image as a first face image;
s9, acquiring a second face image of the passenger;
s10, judging whether the second face image is matched with the first face image or not, and obtaining a first matching result;
s11, outputting first alarm information when the first matching result is that the matching is successful.
Specifically, after the problem baggage and the normal baggage are obtained, a first baggage image of the problem baggage, that is, an image classified as the problem baggage, is first acquired, and an initial face image corresponding to the first baggage image is acquired as a first face image.
When the passenger takes the luggage and leaves, the face image of the passenger is obtained, namely the second face image of the passenger is obtained. And then judging whether the second face image is matched with the first face image.
When the first face image is matched with the second face image, outputting a first matching result as success; and when the first face image and the second face image are not matched, outputting a first matching result as unsuccessful. When the matching result is unsuccessful, the passenger and the luggage normally pass, when the first matching result is successful, the passenger is proved probably to carry dangerous goods by a high probability, and the inspection personnel can be reminded by outputting first alarm information at the moment, so that the passing passenger and luggage are inspected, and the security inspection effect is improved.
The above embodiments are preferred embodiments of the present application, and the protection scope of the present application is not limited by the above embodiments, so: all equivalent changes made according to the structure, shape and principle of the present application shall be covered by the protection scope of the present application.
Claims (9)
1. An advanced screening system, comprising:
the first image acquisition module (1) is used for acquiring a machine check image of the luggage;
the input end of the image classification module (2) is connected with the output end of the first image acquisition module (1) and is used for classifying the machine-detected images and outputting a classification instruction;
the input end of the luggage sorting module (3) is connected with the output end of the image classification module (2) and is used for sorting the luggage based on the classification instruction and obtaining normal luggage and problem luggage;
the identification sealing module (4) is used for receiving the problem luggage and sealing the problem luggage;
the luggage identification module (5) is used for identifying the sealed problem luggage and generating an identification result;
and the input end of the alarm module (6) is connected with the output end of the luggage identification module (5) and is used for generating alarm information based on the identification result.
2. The system of claim 1, further comprising:
the luggage scanning module (7) is used for reading luggage strips preset on a luggage case and acquiring an initial face image;
and the luggage binding module (8) is used for performing association binding on the initial face image and the machine check image.
3. The system of claim 1, further comprising:
and the luggage adjusting module (9) is used for adjusting the distance and the posture of the luggage.
4. The system of claim 1, further comprising:
a second image acquisition module (10) for acquiring a first baggage image of the problematic baggage;
a face image acquisition module (11) for acquiring the initial face image corresponding to the first baggage image as a first face image;
the face image recognition module (12) is used for acquiring a second face image of the passenger;
a first image judgment module (13), one input end of which is connected with the output end of the face image recognition module (12), and the other input end of which is connected with the face image acquisition module (11), and is used for judging whether the second face image is matched with the first face image and obtaining a first matching result;
and the input end of the first warning module (14) is connected with the output end of the first image judging module (13), and when the first matching result is successful, the first warning module is used for outputting first warning information.
5. The system according to claim 1, characterized in that the baggage identification module (5) comprises:
a third image acquisition module (15) for acquiring a second baggage image of the baggage;
and the input end of the second image judging module (16) is connected with the third image acquiring module (15) and is used for judging whether the second luggage image contains a sealed customs supervision belt or not, and acquiring and outputting a judgment result.
6. The system according to claim 5, wherein the baggage identification module (5) further comprises:
the recognition and verification module (17) has one input end connected with the output end of the second image judgment module (16) and the other input end connected with the third image acquisition module (15), and is used for judging whether the second baggage image is matched with the first baggage image or not and obtaining a second matching result when the judgment result is yes;
and the input end of the second warning module (18) is connected with the output end of the identification and verification module (17), and when the judgment result and the second matching result are both yes, the second warning module is used for outputting second warning information.
7. The system of claim 1, further comprising:
the video shooting module (19) is connected with a network communication module (20) at the output end, and is used for shooting the problem luggage after the problem luggage is identified, generating an evidence video and sending the evidence video to the network communication module (20);
and the network communication module (20) is used for sending the evidence video to a terminal.
8. An advanced machine inspection method, comprising:
acquiring a machine check image of the luggage;
classifying the machine-detected images and outputting a classification instruction;
sorting the luggage based on the classification instruction, and obtaining normal luggage and problem luggage;
receiving the problem luggage and sealing;
identifying the sealed problem luggage and generating an identification result;
and generating alarm information based on the identification result.
9. The method of claim 8, wherein obtaining normal and problem baggage further comprises:
acquiring a first baggage image of the problematic baggage;
acquiring the initial face image corresponding to the first baggage image as a first face image;
acquiring a second face image of the passenger;
judging whether the second face image is matched with the first face image or not, and obtaining a first matching result;
and outputting first alarm information when the first matching result is that the matching is successful.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115112508A (en) * | 2022-08-29 | 2022-09-27 | 民航成都物流技术有限公司 | Device and method for identifying soft and hard bags of consigned luggage in civil aviation airport |
| CN117110334A (en) * | 2023-10-23 | 2023-11-24 | 昆明昆船智慧机场技术有限公司 | Luggage safety inspection system and luggage safety inspection method |
Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1173574A (en) * | 1996-01-09 | 1998-02-18 | 卡罗马工业有限公司 | Daul flush cistern button arrangement |
| US20040199403A1 (en) * | 2002-06-26 | 2004-10-07 | Mohan Ananda | Method and apparatus for transporting passenger baggage |
| JP2005040478A (en) * | 2003-07-25 | 2005-02-17 | Sankyo Kk | Game machine |
| US20060243071A1 (en) * | 2004-09-10 | 2006-11-02 | Sagi-Dolev Alysia M | Multi-threat detection system |
| CN101216140A (en) * | 2007-12-26 | 2008-07-09 | 万永明 | Magnetic pressure leak blockage device pole shoe capable of automatically adapting to container arc degree |
| CN101266710A (en) * | 2007-03-14 | 2008-09-17 | 中国科学院自动化研究所 | An all-weather intelligent video analysis monitoring method based on a rule |
| CN101440676A (en) * | 2008-12-22 | 2009-05-27 | 北京中星微电子有限公司 | Intelligent anti-theft door lock based on cam and warning processing method thereof |
| CN101748931A (en) * | 2008-12-02 | 2010-06-23 | 河南省电力公司南阳供电公司 | Master key capable of displaying use times for electric utility use |
| CN103110576A (en) * | 2013-03-11 | 2013-05-22 | 河北凯盛医药科技有限公司 | Lentinan injection preparation and preparation method thereof |
| CN108073577A (en) * | 2016-11-08 | 2018-05-25 | 中国电信股份有限公司 | A kind of alarm method and system based on recognition of face |
| CN110860480A (en) * | 2019-12-20 | 2020-03-06 | 昆明昆船逻根机场系统有限公司 | Method and system for processing transfer baggage of international and international transfer international link flights |
| CN112182270A (en) * | 2019-07-03 | 2021-01-05 | 北京中兴宇泰科技有限公司 | Matching system and matching method for baggage image and passenger information |
| CN212872942U (en) * | 2020-08-24 | 2021-04-02 | 北京航星机器制造有限公司 | Automatic security inspection system |
| CN113239758A (en) * | 2021-04-28 | 2021-08-10 | 深圳市海清视讯科技有限公司 | Elevator monitoring method and system based on face matching and electric vehicle matching |
| CN113252712A (en) * | 2021-04-22 | 2021-08-13 | 盛视科技股份有限公司 | Early machine-inspection baggage risk interception system and method |
-
2021
- 2021-11-20 CN CN202111380942.3A patent/CN114160447B/en active Active
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1173574A (en) * | 1996-01-09 | 1998-02-18 | 卡罗马工业有限公司 | Daul flush cistern button arrangement |
| US20040199403A1 (en) * | 2002-06-26 | 2004-10-07 | Mohan Ananda | Method and apparatus for transporting passenger baggage |
| JP2005040478A (en) * | 2003-07-25 | 2005-02-17 | Sankyo Kk | Game machine |
| US20060243071A1 (en) * | 2004-09-10 | 2006-11-02 | Sagi-Dolev Alysia M | Multi-threat detection system |
| CN101266710A (en) * | 2007-03-14 | 2008-09-17 | 中国科学院自动化研究所 | An all-weather intelligent video analysis monitoring method based on a rule |
| CN101216140A (en) * | 2007-12-26 | 2008-07-09 | 万永明 | Magnetic pressure leak blockage device pole shoe capable of automatically adapting to container arc degree |
| CN101748931A (en) * | 2008-12-02 | 2010-06-23 | 河南省电力公司南阳供电公司 | Master key capable of displaying use times for electric utility use |
| CN101440676A (en) * | 2008-12-22 | 2009-05-27 | 北京中星微电子有限公司 | Intelligent anti-theft door lock based on cam and warning processing method thereof |
| CN103110576A (en) * | 2013-03-11 | 2013-05-22 | 河北凯盛医药科技有限公司 | Lentinan injection preparation and preparation method thereof |
| CN108073577A (en) * | 2016-11-08 | 2018-05-25 | 中国电信股份有限公司 | A kind of alarm method and system based on recognition of face |
| CN112182270A (en) * | 2019-07-03 | 2021-01-05 | 北京中兴宇泰科技有限公司 | Matching system and matching method for baggage image and passenger information |
| CN110860480A (en) * | 2019-12-20 | 2020-03-06 | 昆明昆船逻根机场系统有限公司 | Method and system for processing transfer baggage of international and international transfer international link flights |
| CN212872942U (en) * | 2020-08-24 | 2021-04-02 | 北京航星机器制造有限公司 | Automatic security inspection system |
| CN113252712A (en) * | 2021-04-22 | 2021-08-13 | 盛视科技股份有限公司 | Early machine-inspection baggage risk interception system and method |
| CN113239758A (en) * | 2021-04-28 | 2021-08-10 | 深圳市海清视讯科技有限公司 | Elevator monitoring method and system based on face matching and electric vehicle matching |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115112508A (en) * | 2022-08-29 | 2022-09-27 | 民航成都物流技术有限公司 | Device and method for identifying soft and hard bags of consigned luggage in civil aviation airport |
| CN115112508B (en) * | 2022-08-29 | 2023-01-24 | 民航成都物流技术有限公司 | Device and method for identifying soft and hard bags of consigned luggage in civil aviation airport |
| CN117110334A (en) * | 2023-10-23 | 2023-11-24 | 昆明昆船智慧机场技术有限公司 | Luggage safety inspection system and luggage safety inspection method |
| CN117110334B (en) * | 2023-10-23 | 2024-01-12 | 昆明昆船智慧机场技术有限公司 | Luggage safety inspection system and luggage safety inspection method |
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