CN110989022A - Scanning method of plane security check system, security check system and storage medium - Google Patents
Scanning method of plane security check system, security check system and storage medium Download PDFInfo
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- CN110989022A CN110989022A CN201911134885.3A CN201911134885A CN110989022A CN 110989022 A CN110989022 A CN 110989022A CN 201911134885 A CN201911134885 A CN 201911134885A CN 110989022 A CN110989022 A CN 110989022A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V8/00—Prospecting or detecting by optical means
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
Abstract
The application is applicable to the technical field of security inspection, and provides a scanning method of a planar security inspection system, the security inspection system and a storage medium, wherein the security inspection system comprises: a first planar scan switch array and a second planar scan switch array, the method comprising: performing plane scanning from the left to the right or from the right to the left on the front surface of the human body to be detected through a first plane scanning switch array in the security inspection system to obtain a first plane scanning signal; performing plane scanning from the top to the bottom or from the bottom to the top on the back of the human body to be detected through a second plane scanning switch array in the security inspection system to obtain a second plane scanning signal; obtaining a scanning result according to the obtained first plane scanning signal and the second plane scanning signal; by the method and the device, the omission factor of the security inspection instrument can be reduced on the premise of not increasing the hardware cost of the security inspection system.
Description
Technical Field
The present application belongs to the field of security inspection technology, and in particular, to a scanning method of a planar security inspection system, a security inspection system, and a storage medium.
Background
The millimeter wave band signal, as a millimeter wave band between far infrared wave and microwave, has the characteristic of penetrating through objects such as plasma, dust, clothes and the like, so that the working band is not limited and is harmless to human bodies. Based on the relevant characteristics, the security check instrument adopting the millimeter wave band is more suitable for being applied to public places with large people flow, such as airports, subways and the like.
At present, the missing rate of the millimeter wave security check instrument is relatively high, and in order to reduce the missing rate of the security check instrument, the detection precision of the switch array is improved from the perspective of hardware, however, the cost of the security check instrument is undoubtedly improved.
Disclosure of Invention
In view of this, embodiments of the present application provide a scanning method for a planar security inspection system, a security inspection system, and a storage medium, so as to reduce the missing rate of a security inspection apparatus on the premise of not increasing the hardware cost of the security inspection system.
A first aspect of an embodiment of the present application provides a scanning method for a planar security inspection system, where the security inspection system includes: a first planar scanning switch array and a second planar scanning switch array, the scanning method comprising:
performing plane scanning from the left to the right or from the right to the left on the front surface of the human body to be detected through a first plane scanning switch array in the security inspection system to obtain a first plane scanning signal;
performing plane scanning from the top to the bottom or from the bottom to the top on the back of the human body to be detected through a second plane scanning switch array in the security inspection system to obtain a second plane scanning signal;
and obtaining a scanning result according to the obtained first plane scanning signal and the second plane scanning signal.
A second aspect of an embodiment of the present application provides a security inspection system, including:
a security inspection step comprising a linear edge;
the horizontal rail is arranged on one side of the linear edge of the safety inspection pedal;
the vertical bracket is perpendicular to the horizontal rail and arranged in the horizontal rail, and the vertical bracket translates along the horizontal rail when moving;
the first plane scanning switch array is vertically distributed on the vertical support;
the vertical rail is arranged on the other side, opposite to the linear edge, of the security inspection pedal;
the horizontal bracket is perpendicular to the vertical rail and arranged in the vertical rail, and the horizontal bracket translates along the vertical rail when moving;
the second plane scanning switch array is horizontally distributed on the horizontal bracket;
the present invention also relates to a computer program product stored in a memory and operable on the processor, the computer program product being adapted to perform the steps of the method provided by the first aspect of the embodiments of the present application when executed by the processor.
A third aspect of embodiments of the present application provides a computer-readable storage medium storing a computer program that, when executed by one or more processors, performs the steps of the method provided by the first aspect of embodiments of the present application.
The embodiment of the application provides a scanning method of a plane security check system, wherein the plane security check system comprises: the first planar scanning switch array and the second planar scanning switch array are used for carrying out planar scanning from the left to the right or planar scanning from the right to the left on the front surface of the human body to be detected through the first planar scanning switch array in the security inspection system to obtain a first planar scanning signal; performing plane scanning from the top to the bottom or from the bottom to the top on the back of the human body to be detected through a second plane scanning switch array in the security inspection system to obtain a second plane scanning signal; and obtaining a scanning result according to the obtained first plane scanning signal and the second plane scanning signal. The primary scanning is realized by arranging the first planar scanning switch array on the front side of the human body, the secondary planar scanning switch array is arranged on the back side of the human body, the primary scanning is realized, the scanning accuracy is improved by fusing a front scanning result and a back scanning result, and the omission factor is reduced.
The security inspection system and the storage medium provided by the embodiment of the application have the same beneficial effects as the scanning method, and are not repeated herein.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a schematic flow chart illustrating an implementation of a scanning method of a planar security inspection system according to an embodiment of the present application;
FIG. 2 is a schematic structural diagram of a security inspection step in a security inspection system provided in an embodiment of the present application;
fig. 3 is a schematic structural diagram of a security inspection system provided in an embodiment of the present application;
wherein, 1, a security inspection pedal; 2. a horizontal rail; 3. a straight line edge; 4. a vertical support; 5. a vertical track; 6. a first planar scanning switch array; 7. and (4) a horizontal bracket.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the present application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the specification of the present application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to a determination" or "in response to a detection". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
In order to explain the technical solution described in the present application, the following description will be given by way of specific examples.
Fig. 1 is a schematic flow chart of an implementation of a scanning method of a planar security inspection system according to an embodiment of the present application, where as shown in the figure, the method includes the following steps:
step S101, performing plane scanning from left to right or from right to left on the front surface of the human body to be detected through a first plane scanning switch array in the security inspection system to obtain a first plane scanning signal.
In the embodiment of the application, the security inspection system applied to the scanning method comprises a first planar scanning switch array and a second planar scanning switch array. Illustratively, the security check system includes:
a security inspection step comprising a linear edge;
the horizontal rail is arranged on one side of the linear edge of the safety inspection pedal;
the vertical bracket is perpendicular to the horizontal rail and arranged in the horizontal rail, and rotates along the horizontal rail when moving;
the first plane scanning switch array is vertically distributed on the vertical support;
the vertical rail is arranged on the other side, opposite to the linear edge, of the security inspection pedal;
the horizontal bracket is perpendicular to the vertical rail and arranged in the vertical rail, and the horizontal bracket translates along the vertical rail when moving;
the second plane scanning switch array is horizontally distributed on the horizontal bracket;
in this embodiment, the first planar scanning switch array includes a plurality of pairs of switch antennas, each pair of switch antennas has an independent control switch, that is, each pair of switch antennas does not interfere with each other, and the switch antennas include: the device comprises a pair of transmitting antenna and a pair of receiving antenna, wherein the transmitting antenna can transmit millimeter wave signals and also can transmit terahertz signals, the millimeter wave signals meet a shelter and an obstacle in the transmission process of the millimeter wave signals, such as a human body to be subjected to security inspection, and the millimeter wave signals return and are received by the receiving antenna. The first planar scanning switch array is a plurality of pairs of vertically distributed switch antennas, the first planar scanning switch array is translated from left to right or from right to left on the front surface of a human body, and the switch antennas face the human body all the time in the translation process.
The first planar scanning switch array may be shifted in steps in the shifting process, for example, the first planar scanning switch array may stop moving every step by a certain distance, after the step, the transmitting antenna in the switch antenna transmits the millimeter waves, the receiving antenna in the switch antenna receives the reflected millimeter waves, and then the step shifting is continuously performed according to a certain distance, … …, after the step shift scanning is finished, all millimeter wave signals received by the receiving antenna in the switch antenna constitute a first planar scanning signal.
As another embodiment of the present application, the obtaining a first planar scanning signal by performing planar scanning from left to right or planar scanning from right to left on the front surface of the human body to be detected through the first planar scanning switch array in the security inspection system includes:
step continuous millimeter wave signals are transmitted through a transmitting antenna array in a first plane scanning switch array in the security inspection system, and first scanning signals corresponding to the step continuous millimeter wave signals are received through a receiving antenna array in the first plane scanning switch array in the security inspection system;
taking the serial number of the scanning switch array receiving the current first scanning signal and the receiving serial number of the current first scanning signal as the coordinate of the current first scanning signal;
and after the translation scanning is finished, generating first plane scanning signals according to the direction of the translation scanning and the coordinates of each first scanning signal.
In this embodiment of the application, the pairs of switch antennas in the first planar scanning switch array are uniformly distributed, and meanwhile, since the first planar scanning switch array is moved in a stepping manner during the scanning process, each pair of switch antennas may be numbered, for example, the pairs of switch antennas vertically distributed in the first planar scanning switch array are numbered 1, 2, 3, …, and N from bottom to top, respectively. Where N represents the logarithm of the switch antennas in the first planar scanning switch array. In the step shifting process, each step is performed once, corresponding to obtaining a reflected millimeter wave signal, numbering may be performed according to a receiving sequence, for example, a coordinate of a millimeter wave signal received for the first time by a switch antenna numbered 1 is (1, 1), and a coordinate of a millimeter wave signal received for the jth time by a switch wire numbered i is (j, i). And arranging all millimeter wave signals received by the first plane scanning switch array according to the coordinates to obtain a first plane scanning signal.
It should be noted that the numbering sequence may also be from top to bottom, and the translation sequence may be from left to right or from right to left, which is not limited herein.
And step S102, carrying out plane scanning from the top to the bottom or from the bottom to the top on the back of the human body to be detected through a second plane scanning switch array in the security inspection system to obtain a second plane scanning signal.
In this embodiment, the second planar scanning switch array includes a plurality of pairs of switch antennas, each pair of switch antennas has an independent control switch, that is, each pair of switch antennas does not interfere with each other, and the switch antennas include: the device comprises a pair of transmitting antenna and a pair of receiving antenna, wherein the transmitting antenna can transmit millimeter wave signals and also can transmit terahertz signals, the millimeter wave signals meet a shelter and an obstacle in the transmission process of the millimeter wave signals, such as a human body to be subjected to security inspection, and the millimeter wave signals return and are received by the receiving antenna. The second planar scanning switch array is a plurality of pairs of switch antennas which are horizontally distributed, the second planar scanning switch is translated on the back of the human body from top to bottom or from bottom to top, and the switch antennas face the back of the human body all the time in the translation process.
The second planar scanning switch array may be shifted in steps in the shifting process, for example, the shifting process is stopped every certain distance, the transmitting antenna in the switch antenna transmits millimeter waves after the shifting process is stopped, the receiving antenna in the switch antenna receives the reflected millimeter waves, then the shifting process is continued according to a certain distance, … …, and after the stepping shifting scan is finished, all millimeter wave signals received by the receiving antenna in the switch antenna form a second planar scanning signal.
As another embodiment of the present application, the obtaining a second planar scanning signal by performing planar scanning from top to bottom or planar scanning from bottom to top on the back of the human body to be detected by using a second planar scanning switch array in the security inspection system includes:
transmitting stepping continuous millimeter wave signals through a transmitting antenna array in a second planar scanning switch array in the security inspection system, and receiving second scanning signals corresponding to the stepping continuous millimeter wave signals through a receiving antenna array in the second planar scanning switch array in the security inspection system;
taking the number of the scanning switch array receiving the current second scanning signal and the receiving serial number of the current second scanning signal as the coordinate of the current second scanning signal;
and after the plane scanning is finished, generating second plane scanning signals according to the plane scanning direction and the coordinates of each second scanning signal.
In the embodiment of the present application, the plurality of pairs of switch antennas in the second planar scanning switch array are uniformly distributed, and meanwhile, since the second planar scanning switch array is shifted in a stepping manner during the scanning process, each pair of switch antennas may be numbered, for example, the plurality of pairs of switch antennas horizontally distributed in the second planar scanning switch array are numbered from left to right as 1, 2, 3, …, and M, respectively. Where M represents the logarithm of the switched antennas in the second planar scanning switch array. In the step shifting process, each step is performed once, corresponding to obtaining a reflected millimeter wave signal, numbering may be performed in the order of reception, for example, the coordinate of the millimeter wave signal received for the first time by the switch antenna numbered 1 is (1, 1), and the coordinate of the millimeter wave signal received for the qth time by the switch wire numbered p is (p, q). And arranging all millimeter wave signals received by the second planar scanning switch array according to coordinates to obtain a second planar scanning signal.
It should be noted that the numbering order may also be from right to left, and the translation order may be from top to bottom or from bottom to top, which is not limited herein.
Step S103, obtaining a scanning result according to the obtained first plane scanning signal and the second plane scanning signal.
In the embodiment of the application, the obtained first plane scanning signal can obtain a scanned image of the front side of a human body, the obtained second plane scanning signal can obtain a scanned image of the back side of the human body, and then the scanned image of the front side of the human body and the scanned image of the back side of the human body are subjected to fusion enhancement processing, so that a final scanning result can be obtained.
It should be noted here that, since there may be a difference in the coordinate setting directions of the first planar scanning signal and the second planar scanning signal, it is necessary to make the directions of the front side image and the back side image coincide by rotation processing and/or inversion processing.
As another embodiment of the present application, performing fusion enhancement processing on the front image and the back image, and obtaining a scanning result includes:
constructing a cascaded three-level neural network model, wherein a first-level neural network is a double-input neural network;
training the constructed three-level neural network model through training samples in the training sample set to obtain a trained three-level neural network model;
and inputting the front image and the back image into the trained three-level neural network model, wherein the output of the second-level neural network is a scanning result.
In the embodiment of the application, the front image and the back image can be fused through the neural network model to obtain a relatively accurate scanning image, so that the missing rate is reduced; the fused image can be subjected to enhancement processing (such as sharpening processing) through a neural network model so as to obtain a more accurate scanning image, and the missing rate is further reduced.
The first-stage neural network model is used for fusing the front image and the back image to obtain a fused image, so that double input is required; the second-level neural network is used for enhancing the fusion image to obtain a clear fusion image; the third-stage neural network is used for training the second-stage neural network. In the training process, three levels of neural networks are cascaded together for training, after the training is finished, when the front image and the back image are subjected to fusion enhancement processing, the third level of neural network is removed, the cascaded first level of neural network and second level of neural network are reserved, and the result output by the second level of neural network is the scanning result after the fusion enhancement processing.
As another embodiment of the present application, the training the constructed three-level neural network model through the training samples in the training sample set, and obtaining the trained three-level neural network model includes:
the first iterative training process:
inputting a sample image pair in a training sample set into a first-stage neural network to obtain a first-stage output image, wherein the sample image pair comprises: a front image and a back image;
inputting the first-stage output image into a second-stage neural network to obtain a second-stage first output image, and setting the label of the second-stage first output image to be 0;
setting the label of the high-definition image in the high-definition sample set as 1, training a third-level neural network by the high-definition image and the second-level first output image, and obtaining the trained third-level neural network;
inputting the sample image pair into a second-level neural network to obtain a second-level second output image, setting the label of the second-level second output image as 1, and inputting the second-level second output image into a third-level neural network after the training;
setting the parameters of the third-stage neural network after the training to be not updated, and training the second-stage neural network reversely to obtain the second-stage neural network after the training;
and obtaining a loss function of the first-stage neural network, reversely training the first-stage neural network based on the loss function of the first-stage neural network, and obtaining the trained first-stage neural network.
As another embodiment of the present application, the training process is iterated for the ith time, where i is an integer greater than 1:
inputting a sample image pair in a training sample set into a first-stage neural network after last training to obtain a first-stage output image, wherein the sample image pair comprises: a pair of front and back images;
inputting the first-stage output image into a second-stage neural network after last training to obtain a second-stage first output image, and setting the label of the second-stage first output image to be 0;
setting the label of the high-definition image in the high-definition sample set as 1, training the high-definition image and the second-stage first output image to train the last trained third-stage neural network, and obtaining the trained third-stage neural network;
inputting the sample image pair into a second-level neural network trained last time to obtain a second-level second output image, setting the label of the second-level second output image to be 1, and inputting the second-level second output image into a third-level neural network trained this time;
setting the parameters of the third-stage neural network after the current training as non-updating, reversely training the second-stage neural network after the last training, and obtaining the second-stage neural network after the current training;
and obtaining a loss function of the first-stage neural network, reversely training the last trained first-stage neural network based on the loss function of the first-stage neural network, and obtaining the trained first-stage neural network.
In the art, the training process of a neural network model (also called convolutional neural network model) is divided into a forward propagation process and a backward propagation process. And (3) forward propagation process: processing the image to be processed through the constructed neural network model to obtain an output image or an output result; and (3) a back propagation process: updating parameters of the neural network based on back propagation of differences (loss functions) between the output image or output results and labels of the input image; obtaining a trained neural network model after convergence of the neural network model. And processing the image to be processed through the trained neural network model to obtain an output image.
The first-stage neural network model of the embodiment of the application is used for fusing the front image and the back image together, namely, the fused image finally output by the first-stage neural network model needs to have smaller difference with the content characteristics of the front image and needs to have smaller difference with the content characteristics of the back image. Thus, the loss function of the first stage neural network can be set to:
recording the absolute value of the difference value of the SIFT features of the front image in the first-stage output image (image output by the first-stage neural network in the training process) and the sample image pair as a first loss function, recording the absolute value of the difference value of the SIFT features of the back image in the first-stage output image (image output by the first-stage neural network in the training process) and the sample image pair as a second loss function, and taking the sum of the first loss function and the second loss function as the loss function of the first-stage neural network.
Of course, the input front and back images are pairs of sample images during each training session. The scanning method provided by the embodiment of the application does not need to output images with label values, so that the training samples adopted by the training method do not need to be samples with labels in a sample library, and only a certain number of human body samples are scanned by the security inspection system provided by the embodiment of the application.
The second-level neural network and the third-level neural network provided by the embodiment of the application need to be cascaded together for training, the second-level neural network is an image enhancement network, an original sample (such as an output image of the first-level neural network) is input, and the original sample is packaged into a clearer image by the second-level neural network for output; the resolution of the original sample can be lower, and the resolution of the output image is higher, which is the process of image sharp reconstruction. The third stage neural network may be used as a second classifier. After the image output by the second-level neural network is input into the third-level neural network, the third-level neural network can judge whether the image is a clear image packaged by the neural network or is a clear image originally. The output value is typically a value in the range of 0-1, e.g., an output value greater than 0.5 would identify the input sample as an image of inherently high resolution, and an output value less than 0.5 would identify the input sample as a sharpened image.
In the training process, the third-level network model is expected to obtain a judgment result close to 1 for the input image with higher original definition, and obtain a judgment result close to 0 for the input image subjected to the definition processing of the second-level neural network, so that the third-level neural network model is perfect, and the purpose of good judgment is achieved. Therefore, the loss function of the third-level neural network is expected to be as good as the result of an originally clear image is larger, and the result of an image passing through the second-level neural network is as good as the result is smaller, so the loss function when the third-level neural network is trained is as follows:
the high-definition image (the image which is originally clear in the sample library and can be formed by the image collected by the high-definition device) is input into the inverse of the output function of the third-level neural network, and the output function of the second-level first output image (the image which is subjected to the sharpening processing by the second-level neural network) which is input into the third-level neural network is added.
In the embodiment of the present application, the loss function when the third-level neural network is trained may also be understood as that the discrimination result after the image that is originally clear in the high-definition sample set is input to the third-level neural network is infinite (tends to 1), and the discrimination result after the image that is subjected to the sharpening processing by the second-level neural network is infinite (tends to 0), because it is desirable that the loss function is smaller and better in the training process, the loss function of the third-level neural network may be formed by adding the reciprocal of the discrimination function after the image that is originally clear in the high-definition sample set is input to the third-level neural network and the discrimination function after the image that is subjected to the sharpening processing by the second-level neural network is input to the third-level neural network.
Since the second-stage neural network model is used for generating the sharpened image, it is desirable that the ability of the second-stage neural network model for generating the sharpened image is as strong as possible in the training process, but to what extent, the third-stage neural network model cannot judge whether the sharpened image generated by the second-stage neural network model is originally high in definition or is generated with high definition (which also means that the sharpened image generated by the second-stage neural network is sufficiently clear and natural). The sharpened image generated by the second-stage neural network model is stronger and is generated and reproduced, so that the sharpened image generated by the second-stage neural network is collectively referred to as a false image, and naturally, either the sharpened image generated by the second-stage neural network model is a true image, for example, a high-definition image in a high-definition sample set (it should be noted that the high-definition image is used to indicate that the image fused with the first-stage neural network is sharper) can be used as a true sample.
When the second-level neural network model is trained, no real image is needed, as long as the image output by the first level is input, after the second-level output image is obtained, whether the difference between the second-level output image and the real image is small enough is judged, if the difference between the image output by the second level and the real image is small enough, the second-level neural network model can be considered to be well trained, so that the corresponding loss function is trained in the second-level neural network, only the result of judging the false image generated by the second-level neural network model by the third-level neural network model is closer to 1, the judgment result of the false image generated by the second-level neural network model after being input into the third-level neural network model is larger and better, and the loss function in the second-level neural network training can be obtained: and when the second-stage neural network is trained, the output image of the second-stage neural network is input into the inverse of the output function of the third-stage neural network.
After the loss function of the three-level neural network is determined, a three-level neural network model can be trained. In the training process, front images and back images obtained by scanning a human body in advance can be associated in pairs, the images form a training sample set, and each pair of front images and back images can become a sample image pair.
The forward propagation process:
inputting a pair of front images and back images into a first-stage neural network to obtain a first-stage output image;
inputting the first-stage output image into a second-stage neural network to obtain a second-stage first output image, and setting the label of the second-stage first output image to be 0;
setting the label of the high-definition image in the high-definition sample set as 1, and inputting the high-definition image and the second-stage first output image into a third-stage neural network to obtain a judgment result;
and (3) a back propagation process:
and (3) reverse updating of a third-level neural network: and training the third-stage neural network based on the loss function of the third-stage neural network and the discrimination result of the third-stage neural network to obtain the trained third-stage neural network.
And (3) reverse updating of the second-level neural network: inputting the sample image pair into a second-level neural network to obtain a second-level second output image, setting the label of the second-level second output image as 1, and inputting the second-level second output image into a third-level neural network after the training;
and setting the parameters of the third-stage neural network after the training to be not updated, and reversely updating the parameters in the second-stage neural network based on the judgment result of the third-stage neural network and the loss function of the second-stage neural network to obtain the second-stage neural network after the training.
Reverse updating of the first-stage neural network: and reversely training the first-stage neural network based on the loss function of the first-stage neural network to obtain the trained first-stage neural network.
The subsequent training process is similar to the first training process and will not be described herein.
Therefore, the training process of the three-level neural network is not an independent circulation process, and the mutually-associated samples are adopted in each circulation process, so that the association connection between the three-level neural network is more matched, and the robustness is better.
The mark of the end of the constructed three-level neural network training is as follows: the number of cycles, for example, 1000 cycles, may be set, and when the cycle is stopped after 1000 cycles, the trained tertiary neural network is obtained, the tertiary neural network is removed, and the remaining first-stage neural network and second-stage neural network are cascaded to form the network model capable of realizing the fusion enhancement of the front image and the back image.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.
Fig. 2 and fig. 3 are schematic structural diagrams of a planar security inspection system provided in an embodiment of the present application, and for convenience of description, only parts related to the embodiment of the present application are shown.
The planar security inspection system comprises:
a security inspection step comprising a linear edge;
the horizontal rail is arranged on one side of the linear edge of the safety inspection pedal;
the vertical bracket is perpendicular to the horizontal rail and arranged in the horizontal rail, and rotates along the horizontal rail when moving;
the first plane scanning switch array is vertically distributed on the vertical support;
the vertical rail is arranged on the other side, opposite to the linear edge, of the security inspection pedal;
the horizontal bracket is perpendicular to the vertical rail and arranged in the vertical rail, and the horizontal bracket translates along the vertical rail when moving;
the second plane scanning switch array is horizontally distributed on the horizontal bracket;
a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps in the above scanning method embodiments when executing the computer program.
In the embodiment of the present application, the steps in the above embodiment of the scanning method, which are implemented when the processor executes the computer program, may be steps S101 to S103 shown in fig. 1.
Illustratively, the computer program may be partitioned into one or more modules/units that are stored in the memory and executed by the processor to accomplish the present application. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used for describing the execution process of the computer program in the security check system. For example, the computer program may be divided into a plurality of modules or units.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory may be an internal storage unit of the security system, such as a hard disk or a memory of the security system. The memory may also be an external storage device of the security check system, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the security check system. The memory may also include both an internal storage unit and an external storage device of the security system. The memory is used for storing the computer program and other programs and data required by the security check system. The memory may also be used to temporarily store data that has been output or is to be output.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed security inspection system and scanning method may be implemented in other ways. For example, the above described embodiments of the security system are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the processes in the method of the embodiments described above may be implemented by a computer program, which may be stored in a computer readable storage medium and used by a processor to implement the steps of the embodiments of the scanning method described above. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain other components which may be suitably increased or decreased as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media which may not include electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.
Claims (10)
1. A scanning method for a planar security inspection system, the security inspection system comprising: a first planar scanning switch array and a second planar scanning switch array, the scanning method comprising:
performing plane scanning from the left to the right or from the right to the left on the front surface of the human body to be detected through a first plane scanning switch array in the security inspection system to obtain a first plane scanning signal;
performing plane scanning from the top to the bottom or from the bottom to the top on the back of the human body to be detected through a second plane scanning switch array in the security inspection system to obtain a second plane scanning signal;
and obtaining a scanning result according to the obtained first plane scanning signal and the second plane scanning signal.
2. The scanning method of the planar security inspection system according to claim 1, wherein the obtaining of the first planar scanning signal by the first planar scanning switch array in the security inspection system performs the planar scanning from the left to the right or the planar scanning from the right to the left on the front surface of the human body to be inspected comprises:
step continuous millimeter wave signals are transmitted through a transmitting antenna array in a first plane scanning switch array in the security inspection system, and first scanning signals corresponding to the step continuous millimeter wave signals are received through a receiving antenna array in the first plane scanning switch array in the security inspection system;
taking the serial number of the scanning switch array receiving the current first scanning signal and the receiving serial number of the current first scanning signal as the coordinate of the current first scanning signal;
and after the first plane scanning is finished, generating first plane scanning signals according to the direction of the first plane scanning and the coordinates of each first scanning signal.
3. The scanning method of the planar security inspection system according to claim 2, wherein the obtaining of the second planar scanning signal by performing the planar scanning from the top to the bottom or the planar scanning from the bottom to the top on the back of the human body to be inspected through the second planar scanning switch array in the security inspection system comprises:
transmitting stepping continuous millimeter wave signals through a transmitting antenna array in a second planar scanning switch array in the security inspection system, and receiving second scanning signals corresponding to the stepping continuous millimeter wave signals through a receiving antenna array in the second planar scanning switch array in the security inspection system;
taking the number of the scanning switch array receiving the current second scanning signal and the receiving serial number of the current second scanning signal as the coordinate of the current second scanning signal;
and after the second plane scanning is finished, generating second plane scanning signals according to the direction of the second plane scanning and the coordinates of each second scanning signal.
4. The scanning method of the planar security inspection system according to claim 1, wherein the obtaining of the scanning result according to the obtained first planar scanning signal and the second planar scanning signal comprises:
generating a front image according to the first plane scanning signal;
generating a back image according to the second plane scanning signal;
and performing fusion enhancement processing on the front image and the back image to obtain a scanning result.
5. The scanning method of the planar security inspection system according to claim 4, wherein the performing the fusion enhancement processing on the front image and the back image to obtain the scanning result comprises:
constructing a cascaded three-level neural network model, wherein a first-level neural network is a double-input neural network;
training the constructed three-level neural network model through training samples in the training sample set to obtain a trained three-level neural network model;
and inputting the front image and the back image into the trained three-level neural network model, wherein the output of the second-level neural network is a scanning result.
6. The scanning method of a semi-rotational semi-planar security inspection system of claim 5, wherein the training the constructed tertiary neural network model through the training samples in the training sample set to obtain the trained tertiary neural network model comprises:
the first iterative training process:
inputting a sample image pair in a training sample set into a first-stage neural network to obtain a first-stage output image, wherein the sample image pair comprises: a pair of front and back images;
inputting the first-stage output image into a second-stage neural network to obtain a second-stage first output image, and setting the label of the second-stage first output image to be 0;
setting the label of the high-definition image in the high-definition sample set as 1, training a third-level neural network by the high-definition image and the second-level first output image, and obtaining the trained third-level neural network;
inputting the sample image pair into a second-level neural network to obtain a second-level second output image, setting the label of the second-level second output image as 1, and inputting the second-level second output image into a third-level neural network after the training;
setting the parameters of the third-stage neural network after the training to be not updated, and training the second-stage neural network reversely to obtain the second-stage neural network after the training;
and obtaining a loss function of the first-stage neural network, reversely training the first-stage neural network based on the loss function of the first-stage neural network, and obtaining the trained first-stage neural network.
7. The scanning method of a semi-rotational semi-planar security inspection system of claim 6, wherein the training the constructed tertiary neural network model through the training samples in the training sample set to obtain the trained tertiary neural network model comprises:
an ith iterative training process, wherein i is an integer greater than 1:
inputting a sample image pair in a training sample set into a first-stage neural network after last training to obtain a first-stage output image, wherein the sample image pair comprises: a pair of front and back images;
inputting the first-stage output image into a second-stage neural network after last training to obtain a second-stage first output image, and setting the label of the second-stage first output image to be 0;
setting the label of the high-definition image in the high-definition sample set as 1, training the high-definition image and the second-stage first output image to train the last trained third-stage neural network, and obtaining the trained third-stage neural network;
inputting the sample image pair into a second-level neural network trained last time to obtain a second-level second output image, setting the label of the second-level second output image to be 1, and inputting the second-level second output image into a third-level neural network trained this time;
setting the parameters of the third-stage neural network after the current training as non-updating, reversely training the second-stage neural network after the last training, and obtaining the second-stage neural network after the current training;
and obtaining a loss function of the first-stage neural network, reversely training the last trained first-stage neural network based on the loss function of the first-stage neural network, and obtaining the trained first-stage neural network.
8. The scanning method of a semi-rotational semi-planar security inspection system of claim 6 or 7, wherein said obtaining a loss function of the first stage neural network comprises:
recording the absolute value of the difference value of the SIFT features of the front images in the first-stage output image and the sample image pair as a first loss function, recording the absolute value of the difference value of the SIFT features of the back images in the first-stage output image and the sample image pair as a second loss function, and taking the sum of the first loss function and the second loss function as the loss function of the first-stage neural network;
the loss function when training the second stage neural network is: the reciprocal of an output function of the second-stage second output image after being input into the third-stage neural network;
the loss function when training the third-level neural network is: and adding the reciprocal of the output function of the high-definition image after being input into the third-level neural network and the output function of the second-level first output image after being input into the third-level neural network.
9. A planar security inspection system, comprising:
a security inspection step comprising a linear edge;
the horizontal rail is arranged on one side of the linear edge of the safety inspection pedal;
the vertical bracket is perpendicular to the horizontal rail and arranged in the horizontal rail, and the vertical bracket translates along the horizontal rail when moving;
the first plane scanning switch array is vertically distributed on the vertical support;
the vertical rail is arranged on the other side, opposite to the linear edge, of the security inspection pedal;
the horizontal bracket is perpendicular to the vertical rail and arranged in the vertical rail, and the horizontal bracket translates along the vertical rail when moving;
the second plane scanning switch array is horizontally distributed on the horizontal bracket;
memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the method according to any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by one or more processors, implements the steps of the method according to any one of claims 1 to 7.
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