CN117243642B - Intelligent throat swab sampling equipment control system based on machine vision - Google Patents

Intelligent throat swab sampling equipment control system based on machine vision Download PDF

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CN117243642B
CN117243642B CN202311524290.5A CN202311524290A CN117243642B CN 117243642 B CN117243642 B CN 117243642B CN 202311524290 A CN202311524290 A CN 202311524290A CN 117243642 B CN117243642 B CN 117243642B
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user
module
face image
sampling
eye
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CN117243642A (en
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单艳梅
徐清顺
王涛
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Shandong Huangshengtang Pharmaceutical Co ltd
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Shandong Huangshengtang Pharmaceutical Co ltd
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B10/00—Other methods or instruments for diagnosis, e.g. instruments for taking a cell sample, for biopsy, for vaccination diagnosis; Sex determination; Ovulation-period determination; Throat striking implements
    • A61B10/0045—Devices for taking samples of body liquids
    • A61B10/0051—Devices for taking samples of body liquids for taking saliva or sputum samples
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/20—Surgical navigation systems; Devices for tracking or guiding surgical instruments, e.g. for frameless stereotaxis
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/30—Surgical robots
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G06V10/26—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G06V10/30—Noise filtering
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/56—Extraction of image or video features relating to colour
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/16—Human faces, e.g. facial parts, sketches or expressions
    • G06V40/161—Detection; Localisation; Normalisation
    • G06V40/166—Detection; Localisation; Normalisation using acquisition arrangements
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/18—Eye characteristics, e.g. of the iris
    • G06V40/193—Preprocessing; Feature extraction
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/20—Surgical navigation systems; Devices for tracking or guiding surgical instruments, e.g. for frameless stereotaxis
    • A61B2034/2046—Tracking techniques
    • A61B2034/2065—Tracking using image or pattern recognition
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/30—Surgical robots
    • A61B2034/302—Surgical robots specifically adapted for manipulations within body cavities, e.g. within abdominal or thoracic cavities
    • 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
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • 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
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Abstract

The invention relates to the technical field of throat swab sampling, in particular to an intelligent throat swab sampling equipment control system based on machine vision, which comprises a control terminal, an acquisition layer, an identification layer and a control layer, wherein the acquisition layer is arranged on the control terminal; the control terminal is a main control terminal of the system and is used for sending out an execution command; the sampling device triggers the operation of the acquisition layer based on gravity sensing in real time, the operation of the acquisition layer continuously acquires face image data of a user, validity analysis is carried out on the acquired face image data of the user, and the face image of the user is selected based on a validity analysis result.

Description

Intelligent throat swab sampling equipment control system based on machine vision
Technical Field
The invention relates to the technical field of throat swab sampling, in particular to an intelligent throat swab sampling equipment control system based on machine vision.
Background
The throat swab sampling is also called nucleic acid sampling, the substance of the nucleic acid sampling is nucleic acid of virus, the nucleic acid detection is to find whether the foreign invasion virus nucleic acid exists in the respiratory tract specimen, blood or excrement of a human body or not to determine whether the human body is infected by the virus, and when the sampling requirement is large, the intelligent throat swab sampling equipment is often used for realizing unmanned sampling work, so that the labor cost and the cross infection in the sampling process are greatly reduced.
At present, when an intelligent throat swab automatic sampling device is used for sampling a throat swab of a user, the correction with the oral cavity of the user is usually completed according to visual detection, and although the throat swab sampling work can be completed, the angle fine adjustment of the sampling end on the device is not performed according to the head angle of the user, so that the sampling end on the device directly stretches into the oral cavity of the user, and discomfort or scratch of the mucous membrane in the oral cavity of the user can be easily caused.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides an intelligent throat swab sampling equipment control system based on machine vision, which solves the technical problems in the background art.
In order to achieve the above purpose, the invention is realized by the following technical scheme:
an intelligent throat swab sampling equipment control system based on machine vision comprises a control terminal, an acquisition layer, an identification layer and a control layer;
the control terminal is a main control terminal of the system and is used for sending out an execution command;
the sampling device triggers the operation of the acquisition layer based on gravity sensing in real time, the operation of the acquisition layer continuously acquires face image data of a user, validity analysis is carried out on the acquired face image data of the user, a face image of the user is selected based on a validity analysis result, the selected face image of the user is sent to the recognition layer, the recognition layer further analyzes eye view angle distribution of the user based on the received face image of the user, the control layer sets sampling device adjusting logic, and synchronously receives analysis results of eye view angle distribution of the user in the recognition layer, and the operation adjustment of the sampling device is controlled based on the sampling device adjusting logic and the analysis results of eye view angle distribution of the user, and throat swab sampling is carried out on the user after adjustment;
the recognition layer comprises a receiving module, a processing module and an identification module, wherein the receiving module is used for receiving the user face images selected in the acquisition layer, the processing module is used for carrying out noise reduction processing on the user face images received by the receiving module, the identification module is used for acquiring eye images in the user face image data, analyzing the eye view angle distribution of the user based on the user eye images, and sending the analysis obtained user eye view angle distribution result to the control layer in real time;
the user eye viewing angle distribution analysis logic is expressed as:
；
wherein:distributing characteristic representation values for the upper left region of the eye image in the face image data of the user; />To identify a set of region pixels; />Color feature vectors for the 1 st group of pixel blocks in the upper left region of the eye image; />Is the weight;representing values for the distribution characteristics of the region right above the eye image in the face image data of the user; />Color feature vectors of the 1 st group of pixel blocks in the region right above the eye image;
before application, the user eye visual angle distribution analysis logic performs equal division on the user eye image, the areas obtained by the division areas are all the above identification areas, the division result is a 3×3 sub-image matrix, and the sub-image matrix is respectively marked as: when the user eye view angle distribution analysis logic is applied, two groups of sub-image matrixes are selected to be applied to the operation of the user eye view angle distribution analysis logic, and the two groups of sub-image matrixes can be selected as follows: left upper part and right upper part; right upper, upper right; upper right, right; left upper, right left; right left, lower left; lower left, right lower; lower right; lower right, right; the correspondence is expressed as: UL, U; u, UR; UR, R; UL, L; l, DL; DL, D; D. DR; DR, R.
Furthermore, the sampling equipment comprises a positioning station, a sampling station, a processing station and a control station, wherein the positioning vacancy is used for positioning the head placing posture of a user, the sampling station is used for collecting a user throat swab sample, the processing station is used for recovering the collected user throat swab sample, and the control station is used for controlling the operation of the positioning station, the sampling station and the processing station;
the positioning station is provided with a gravity sensor, when the gravity sensor senses that the real-time bearing weight of a positioning vacancy changes, the gravity sensor triggers the acquisition layer to operate, the positioning station operates in a stage for supporting the chin of a user, the head of the user is arranged on the positioning station, the sampling station operates in a stage for automatic alignment, the sampling end of the throat swab is aligned to the mouth of the user, and after the sampling end of the throat swab is aligned to the mouth of the user, the throat swab sampling operation is further operated and executed.
Further, the acquisition layer comprises a camera module, an analysis module and a selection module, wherein the camera module is used for acquiring the user face image, the analysis module is used for analyzing the validity of the user face image, the selection module is used for receiving the validity analysis result of the analysis module on the user face image, selecting the user face image based on the validity analysis result of the user face image, and feeding back the selected user face image to the recognition layer;
the camera module is arranged on the lower level of the sampling device, the camera module and the voice module are deployed on the sampling device, the camera module and the voice module participate in system operation through wireless data transmission, the voice module is used for sending voice notification to inform a user to see the camera module and do not move the head, a system end user inputs user face image acquisition frequency in the control terminal, and the camera module obtains user face image acquisition frequency in the control terminal and applies operation.
Still further, the validity analysis logic of the analysis module operation phase for the user face image is expressed as:
；
wherein:the effective value of the face image is the user; />The distance from the left eye of the user to the camera module in the face image of the user is set; />The distance from the right eye of the user to the camera module in the face image of the user is provided; the distance from the left eye or the right eye of the user to the camera module in the face image of the user is expressed as:
；
wherein: the spatial coordinates of the camera module areThe spatial coordinates of the left eye or the right eye of the user in the user face image are +.>，/>Are known;
wherein,the closer the value of (2) is to 1, the more effective the user face image collected by the camera module is, and the user face image received by the identification layer is the calculated effective value of the user face image +.>Spatial coordinates of the left or right eye of the user applied closest to 1 +.>The user face image.
Further, the coordinates of the user face image are known based on the positioning station of the sampling device, denoted (x, y), thenIn (I)>Is of known useFind +.>The logic of the calculation is expressed as:
；
wherein;is a scale factor; (/>，/>) For correspondence in user face image (x, y)Coordinates of (c); />The ratio of the corresponding orthogonal rotation matrix to its translation vector in the user face image (x, y); />Is a perspective projection matrix;
wherein,during the calculation, the calculation is performed based on a plane defined by the camera end of the camera module and the camera angle and a plane where the face image (x, y) of the user is located.
Further, in the operation stage of the processing module, the user face image after the noise reduction processing is performed on the user face image is output through the following formula:
；
wherein:the user face image is output after the noise reduction processing; />For neighborhood->Pixel sums within;pixels for a point in the original user face image (x, y)A value;
wherein,。
further, the weightThe value is 0.5 or 1, and the weight is +.>When the value is 1 and the identification area is in a non-positive direction, the weight is +.>The value is 0.5.
Further, the control layer comprises a setting module, a logic module and a control module, wherein the setting module is used for setting sampling equipment adjusting logic, the logic module is used for acquiring an identification area applied when analyzing the eye visual angle distribution of a user in the identification layer, the sampling equipment adjusting logic is configured based on the identification area, the control module is used for receiving the sampling equipment adjusting logic configured in the logic module and the analysis result of the eye visual angle distribution of the user, and the sampling equipment is controlled to operate based on the analysis result of the eye visual angle distribution of the user and the sampling equipment adjusting logic, so that the adjustment operation of a sampling station is completed;
the angle of the sampling station is adjusted by the adjusting operation of the sampling station of the sampling equipment.
Still further, the sampling device adjustment logic set in the setting module is:
；
wherein:to adjust the angle; />For adjusting the coefficient;
wherein, in the sampling device adjusting logicThe middle and middle molecules always apply the feature representation value obtained by the non-positive direction identification area to subtract the feature representation value obtained by the positive direction identification area, the denominator always applies the feature representation value obtained by the positive direction identification area to adjust the coefficient ∈ ->Is subject to the values->The greater the value of +.>The larger the value of +.>The smaller the value of (c) is,setting logic with smaller value of +.>L in the drawing represents the arm span of the sampling station, and the angle is adjusted>After the acquisition, synchronously acquiring a positive direction identification area, and applying an adjusting angle to a sampling station of sampling equipment when the positive direction identification area is right or right downwardWhen the upward adjustment is carried out and the positive direction identification area is right left or right upward, the sampling station of the sampling equipment applies an adjustment angle +.>Downward adjustment.
Furthermore, the control terminal is electrically connected with an analysis module selection module through a medium, the analysis module is connected with the camera module and the voice module through a local area network for data sharing, the camera module is electrically connected with the voice module through the medium, the selection module is electrically connected with a receiving module through the medium, the receiving module is electrically connected with a processing module and an identification module through the medium, the identification module is electrically connected with a setting module through the medium, and the setting module is electrically connected with a logic module and a control module through the medium.
Compared with the known public technology, the technical scheme provided by the invention has the following beneficial effects:
1. the invention provides an intelligent throat swab sampling equipment control system based on machine vision, which can acquire face images of a user in the running process, further acquire eye images of the user in the face image data of the user, further correct and regulate sampling equipment based on eye image analysis of the user, ensure that the sampling equipment runs more comfortably in the process of acquiring throat swab samples of the user, and avoid uncomfortable sampling process or harm to mucous membrane of the inner wall of an oral cavity of the user caused by inconsistent sampling posture of a sampling end of the sampling equipment as far as possible.
2. In the running process of the system, the intelligent control effect is further brought to the system under the running state of the configuration sampling equipment through the deployment of the sensing function, so that the system can run synchronously along with the sampling behavior of a user, and meanwhile, after the face images of the user are acquired, the face images of the user are further selected by the appointed logic, so that the optimal face images of the user are selected to further analyze the eye images of the user, and the running precision of the system is improved.
3. In the running process of the system, the details of the face images of the user can be further highlighted through the noise reduction processing of the face images of the user, so that the accuracy of the running control result of the system is further improved.
4. The invention controls the operation of the acquisition equipment by the appointed adjusting logic, so that the sampling equipment with the system can stably finish the adjustment of the sampling end in an adaptive way when a user performs throat swab sampling, and in the application stage of the adjusting logic, multiple groups of data can be acquired by dividing the eye images, and then the adjusting result is obtained based on the divided sub-eye images, so that the robustness of the obtaining process of the adjusting result is better, and the adjusting response is sharper.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It is evident that the drawings in the following description are only some embodiments of the present invention and that other drawings may be obtained from these drawings without inventive effort for a person of ordinary skill in the art.
FIG. 1 is a schematic diagram of a machine vision-based control system for an intelligent pharyngeal swab sampling device;
FIG. 2 is a schematic diagram showing the principle of a working station of the sampling device in the invention;
FIG. 3 is a schematic view of the segmentation result of an eye image according to the present invention;
reference numerals in the drawings represent respectively: 1. the distance from the eyes of the user to the camera module in the face image of the user.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It will be apparent that the described embodiments are some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention is further described below with reference to examples.
Embodiment one:
the control system of the intelligent throat swab sampling device based on machine vision in the embodiment comprises a control terminal, an acquisition layer, an identification layer and a control layer as shown in fig. 1;
the control terminal is a main control terminal of the system and is used for sending out an execution command;
the sampling device triggers the operation of the acquisition layer based on gravity sensing in real time, the operation of the acquisition layer continuously acquires face image data of a user, validity analysis is carried out on the acquired face image data of the user, a face image of the user is selected based on a validity analysis result, the selected face image of the user is sent to the recognition layer, the recognition layer further analyzes eye view angle distribution of the user based on the received face image of the user, the control layer sets sampling device adjusting logic, and synchronously receives analysis results of eye view angle distribution of the user in the recognition layer, and the operation adjustment of the sampling device is controlled based on the sampling device adjusting logic and the analysis results of eye view angle distribution of the user, and throat swab sampling is carried out on the user after adjustment;
the recognition layer comprises a receiving module, a processing module and an identification module, wherein the receiving module is used for receiving the user face images selected in the acquisition layer, the processing module is used for carrying out noise reduction processing on the user face images received by the receiving module, the identification module is used for acquiring eye images in the user face image data, analyzing the eye view angle distribution of the user based on the user eye images, and sending the analysis obtained user eye view angle distribution result to the control layer in real time;
the user eye viewing angle distribution analysis logic is expressed as:
；
wherein:distributing characteristic representation values for the upper left region of the eye image in the face image data of the user; />To identify a set of region pixels; />Color feature vectors for the 1 st group of pixel blocks in the upper left region of the eye image; />Is the weight;representing values for the distribution characteristics of the region right above the eye image in the face image data of the user; />Color feature vectors of the 1 st group of pixel blocks in the region right above the eye image;
before application, the user eye visual angle distribution analysis logic performs equal division on the user eye image, the areas obtained by the division areas are all the above identification areas, the division result is a 3×3 sub-image matrix, and the sub-image matrix is respectively marked as: when the user eye view angle distribution analysis logic is applied, two groups of sub-image matrixes are selected to be applied to the operation of the user eye view angle distribution analysis logic, and the two groups of sub-image matrixes can be selected as follows: left upper part and right upper part; right upper, upper right; upper right, right; left upper, right left; right left, lower left; lower left, right lower; lower right; lower right, right; the correspondence is expressed as: UL, U; u, UR; UR, R; UL, L; l, DL; DL, D; D. DR; DR, R;
the sampling equipment comprises a positioning station, a sampling station, a processing station and a control station, wherein the positioning vacancy is used for positioning the head placing gesture of a user, the sampling station is used for collecting a throat swab sample of the user, the processing station is used for recovering the collected throat swab sample of the user, and the control station is used for controlling the operation of the positioning station, the sampling station and the processing station;
the positioning station is provided with a gravity sensor, when the gravity sensor senses that the real-time bearing weight of a positioning vacancy changes, the gravity sensor triggers the operation of the acquisition layer, the operation stage of the positioning station supports the chin of a user, the head of the user is arranged above the positioning station, the operation stage of the sampling station automatically performs alignment, the sampling end of the throat swab is aligned to the mouth of the user, and after the sampling end of the throat swab is aligned to the mouth of the user, the throat swab sampling operation is further performed;
the acquisition layer comprises a camera module, an analysis module and a selection module, wherein the camera module is used for acquiring the user face image, the analysis module is used for analyzing the effectiveness of the user face image, the selection module is used for receiving the effectiveness analysis result of the analysis module on the user face image, selecting the user face image based on the effectiveness analysis result of the user face image, and feeding back the selected user face image to the recognition layer;
the camera module and the voice module are deployed on the sampling equipment, and participate in system operation through wireless data transmission, and the voice module is used for sending voice notification to inform a user to look at the camera module and do not move the head, a system end user inputs user face image acquisition frequency in the control terminal, and the camera module acquires the user face image acquisition frequency in the control terminal and applies operation;
weighting ofThe value is 0.5 or 1, and the weight is +.>When the value is 1 and the identification area is in a non-positive direction, the weight is +.>The value is 0.5;
the control layer comprises a setting module, a logic module and a control module, wherein the setting module is used for setting sampling equipment adjusting logic, the logic module is used for acquiring an identification area applied when analyzing the eye view angle distribution of a user in the identification layer, the sampling equipment adjusting logic is configured based on the identification area, the control module is used for receiving the sampling equipment adjusting logic configured in the logic module and the analysis result of the eye view angle distribution of the user, and the sampling equipment is controlled to operate based on the analysis result of the eye view angle distribution of the user and the sampling equipment adjusting logic, so that the adjustment operation of a sampling station is completed;
the angle of the sampling station is adjusted by the adjustment operation of the sampling station of the sampling equipment;
the sampling device adjusting logic set in the setting module is as follows:
；
wherein:to adjust the angle; />For adjusting the coefficient;
wherein, in the sampling device adjusting logicThe middle and middle molecules always apply the feature representation value obtained by the non-positive direction identification area to subtract the feature representation value obtained by the positive direction identification area, the denominator always applies the feature representation value obtained by the positive direction identification area to adjust the coefficient ∈ ->Is subject to the values->The greater the value of +.>The larger the value of +.>The smaller the value of (c) is,setting logic with smaller value of +.>L in the drawing represents the arm span of the sampling station, and the angle is adjusted>After the calculation, the positive direction identification area is synchronously obtainedWhen the domain is right or right downward, the sampling station of the sampling equipment applies an adjusting angleWhen the upward adjustment is carried out and the positive direction identification area is right left or right upward, the sampling station of the sampling equipment applies an adjustment angle +.>Downward adjustment;
the control terminal is electrically connected with an analysis module selection module through a medium, the analysis module is connected with a camera module and a voice module through a local area network for data sharing, the camera module is electrically connected with the voice module through the medium, the selection module is electrically connected with a receiving module through the medium, the receiving module is electrically connected with a processing module and an identification module through the medium, the identification module is electrically connected with a setting module through the medium, and the setting module is electrically connected with a logic module and a control module through the medium.
In the embodiment, a gravity sensor on the acquisition device senses that the bearing gravity changes to trigger the system to operate, a camera module operates on the acquisition user face image, an analysis module synchronously analyzes the effectiveness of the user face image, a selection module operates at the rear end to receive the effectiveness analysis result of the user face image in the analysis module, the user face image is selected based on the effectiveness analysis result of the user face image, the selected user face image is fed back to an identification layer, a receiving module operates to receive the user face image selected in the acquisition layer, a processing module carries out noise reduction processing on the user face image received by the receiving module in real time, then the identification module acquires eye images in user face image data, analyzes the eye view angle distribution of a user based on the eye view angle distribution of the user, and sends the analysis result to a control layer in real time, a setting module further sets sampling device adjusting logic, when the logic module operates to acquire the eye view angle distribution of the user in the user, the sampling device adjusting logic is configured based on the identification area, finally the sampling device adjusting logic is configured in the control module receives the sampling device adjusting logic and the eye view angle distribution analysis result based on the user eye view angle distribution and the sampling device adjusting logic is operated, and the sampling station adjusting logic is completed;
the regulation control value finally output by the system operation is further perfected through the recorded formula, and a stable regulation control effect is brought to the sampling equipment;
referring to fig. 2, the figure further shows the specific station deployment result of the sampling device, and further shows the validity analysis logic basis of the analysis module for the face image of the user;
referring to fig. 3, the segmentation logic for an image of a user's eye is shown.
Embodiment two:
the validity analysis logic of the analysis module operation stage for the user face image is expressed as follows:
；
wherein:the effective value of the face image is the user; />The distance from the left eye of the user to the camera module in the face image of the user is set; />The distance from the right eye of the user to the camera module in the face image of the user is provided; the distance from the left eye or the right eye of the user to the camera module in the face image of the user is expressed as:
；
wherein: the spatial coordinates of the camera module areSpace sitting of left eye or right eye of user in user face imageMarked as->，/>Are known;
wherein,the closer the value of (2) is to 1, the more effective the user face image collected by the camera module is, and the user face image received by the identification layer is the calculated effective value of the user face image +.>Spatial coordinates of the left or right eye of the user applied closest to 1 +.>A face image of the user;
the coordinates of the user face image are known based on the positioning station of the sampling device, denoted (x, y), thenIn (I)>Is of known useFind +.>The logic of the calculation is expressed as:
；
wherein;is a scale factor; (/>，/>) For correspondence in user face image (x, y)Coordinates of (c); />The ratio of the corresponding orthogonal rotation matrix to its translation vector in the user face image (x, y); />Is a perspective projection matrix;
wherein,during the calculation, the calculation is performed based on a plane defined by the camera end of the camera module and the camera angle and a plane where the face image (x, y) of the user is located.
The validity analysis logic of the user face image in the operation stage of the analysis module is further limited through the formula calculation, so that the acquisition layer provides the optimal user face image to the receiving module in the identification layer for further operation of the identification layer and the control layer based on the analysis result of the validity analysis logic.
Embodiment III:
and in the operation stage of the processing module, outputting the user face image after the noise reduction processing of the user face image by the following formula:
；
wherein:the user face image is output after the noise reduction processing; />For neighborhood->Pixel sums within;pixel values for a point in the original user face image (x, y);
wherein,。
through the formula calculation, noise reduction processing is brought to the user face image data, so that the user face image of the identification module running application in the identification layer in the system tends to be more refined, and the accuracy of the control result of the system running output on the acquisition equipment is further improved.
In summary, the system in the above embodiment can collect facial images of the user in the running process, so as to further obtain eye images of the user in facial image data of the user, and further correct and adjust the sampling device based on eye image analysis of the user, so that the sampling device runs and collects throat swab samples of the user more comfortably, and discomfort in the sampling process or damage to mucous membrane of the oral cavity of the user caused by inconsistent sampling posture of the sampling end of the sampling device and the oral cavity of the user are avoided as much as possible; in the running process of the system, the intelligent control effect is further brought to the system under the running state of the configuration sampling equipment through the deployment of the sensing function, so that the system can run synchronously along with the sampling behavior of a user, and meanwhile, after the face images of the user are acquired, the face images of the user are further selected by a designated logic so as to achieve the purpose of selecting the optimal face images of the user to further analyze the eye images of the user, thereby improving the running precision of the system; meanwhile, in the running process of the system, the details of the face images of the user can be further highlighted through the noise reduction processing of the face images of the user, so that the accuracy of the running control result of the system is further improved; in addition, the system controls the operation of the acquisition equipment by the appointed adjusting logic, so that the sampling equipment with the system can stably finish sampling end adjustment in an adaptive manner when a user performs throat swab sampling, in an adjusting logic application stage, multiple groups of data can be acquired by dividing an eye image, and then an adjusting result is obtained based on the divided sub-eye images, so that the robustness of the obtaining process of the adjusting result is better, and the adjusting response is sharper.
The above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims (3)

1. The intelligent throat swab sampling equipment control system based on machine vision is characterized by comprising a control terminal, an acquisition layer, an identification layer and a control layer;
the control terminal is a main control terminal of the system and is used for sending out an execution command;
the sampling device triggers the operation of the acquisition layer based on gravity sensing in real time, the operation of the acquisition layer continuously acquires face image data of a user, validity analysis is carried out on the acquired face image data of the user, a face image of the user is selected based on a validity analysis result, the selected face image of the user is sent to the recognition layer, the recognition layer further analyzes eye view angle distribution of the user based on the received face image of the user, the control layer sets sampling device adjusting logic, and synchronously receives analysis results of eye view angle distribution of the user in the recognition layer, and the operation adjustment of the sampling device is controlled based on the sampling device adjusting logic and the analysis results of eye view angle distribution of the user, and throat swab sampling is carried out on the user after adjustment;
the recognition layer comprises a receiving module, a processing module and an identification module, wherein the receiving module is used for receiving the user face images selected in the acquisition layer, the processing module is used for carrying out noise reduction processing on the user face images received by the receiving module, the identification module is used for acquiring eye images in the user face image data, analyzing the eye view angle distribution of the user based on the user eye images, and sending the analysis obtained user eye view angle distribution result to the control layer in real time;
the user eye viewing angle distribution analysis logic is expressed as:
；
wherein:distributing characteristic representation values for the upper left region of the eye image in the face image data of the user; />To identify a set of region pixels; />Color feature vectors for the 1 st group of pixel blocks in the upper left region of the eye image; />Is the weight; />Representing values for the distribution characteristics of the region right above the eye image in the face image data of the user; />Color feature vectors of the 1 st group of pixel blocks in the region right above the eye image;
before application, the user eye visual angle distribution analysis logic performs equal division on the user eye image, the areas obtained by the division areas are all the above identification areas, the division result is a 3×3 sub-image matrix, and the sub-image matrix is respectively marked as: when the user eye view angle distribution analysis logic is applied, two groups of sub-image matrixes are selected to be applied to the operation of the user eye view angle distribution analysis logic, and the two groups of sub-image matrixes can be selected as follows: left upper part and right upper part; right upper, upper right; upper right, right; left upper, right left; right left, lower left; lower left, right lower; lower right; lower right, right; the correspondence is expressed as: UL, U; u, UR; UR, R; UL, L; l, DL; DL, D; D. DR; DR, R;
the acquisition layer comprises a camera module, an analysis module and a selection module, wherein the camera module is used for acquiring the user face image, the analysis module is used for analyzing the effectiveness of the user face image, the selection module is used for receiving the effectiveness analysis result of the analysis module on the user face image, selecting the user face image based on the effectiveness analysis result of the user face image, and feeding back the selected user face image to the recognition layer;
the camera module and the voice module are deployed on the sampling equipment, and participate in system operation through wireless data transmission, and the voice module is used for sending voice notification to inform a user to look at the camera module and do not move the head, a system end user inputs user face image acquisition frequency in the control terminal, and the camera module acquires the user face image acquisition frequency in the control terminal and applies operation;
the validity analysis logic of the analysis module operation stage for the user face image is expressed as follows:
；
wherein:the effective value of the face image is the user; />The distance from the left eye of the user to the camera module in the face image of the user is set; />The distance from the right eye of the user to the camera module in the face image of the user is provided; the distance from the left eye or the right eye of the user to the camera module in the face image of the user is expressed as:
；
wherein: the spatial coordinates of the camera module areThe spatial coordinates of the left eye or the right eye of the user in the user face image are +.>，/>Are known;
wherein,the closer the value of (2) is to 1, the more effective the user face image collected by the camera module is, and the user face image received by the identification layer is the calculated effective value of the user face image +.>Spatial coordinates of the left or right eye of the user applied closest to 1 +.>A face image of the user;
the coordinates of the user face image are known based on the positioning station of the sampling device, denoted (x, y), thenIn (I)>Is of known useFind +.>The logic of the calculation is expressed as:
；
wherein;is a scale factor; (/>，/>) For the corresponding +.>Coordinates of (c); />The ratio of the corresponding orthogonal rotation matrix to its translation vector in the user face image (x, y); />Is a perspective projection matrix;
wherein,when the method is used for solving, the plane defined by the camera end of the camera module and the camera angle and the plane where the face image (x, y) of the user is positioned are solved;
the processing module is used for outputting the user face image after the noise reduction processing of the user face image through the following formula:
；
wherein:the user face image is output after the noise reduction processing; />For neighborhood->Pixel sums within;pixel values for a point in the original user face image (x, y);
wherein,；
the weight isThe value is 0.5 or 1, and the weight is +.>When the value is 1 and the identification area is in a non-positive direction, the weight is +.>The value is 0.5;
the control layer comprises a setting module, a logic module and a control module, wherein the setting module is used for setting sampling equipment adjusting logic, the logic module is used for acquiring an identification area applied when analyzing the eye view angle distribution of a user in the identification layer, the sampling equipment adjusting logic is configured based on the identification area, the control module is used for receiving the sampling equipment adjusting logic configured in the logic module and the analysis result of the eye view angle distribution of the user, and the sampling equipment is controlled to operate based on the analysis result of the eye view angle distribution of the user and the sampling equipment adjusting logic, so that the adjustment operation of a sampling station is completed;
the angle of the sampling station is adjusted by the adjustment operation of the sampling station of the sampling equipment;
the sampling equipment adjusting logic set in the setting module is as follows:
；
wherein:to adjust the angle; />For adjusting the coefficient;
wherein, in the sampling device adjusting logicThe middle and middle molecules always apply the feature representation value obtained by the non-positive direction identification area to subtract the feature representation value obtained by the positive direction identification area, the denominator always applies the feature representation value obtained by the positive direction identification area to adjust the coefficient ∈ ->Is subject to the values->The greater the value of +.>The larger the value of +.>The smaller the value of +.>Setting logic with smaller value of +.>L in the drawing represents the arm span of the sampling station, and the angle is adjusted>After the acquisition, synchronously acquiring a positive direction identification area, and applying an adjusting angle to a sampling station of sampling equipment when the positive direction identification area is right or right downwards>When the upward adjustment is carried out and the positive direction identification area is right left or right upward, the sampling station of the sampling equipment applies an adjustment angle +.>Downward adjustment.
2. The intelligent throat swab sampling equipment control system based on machine vision according to claim 1, wherein the sampling equipment comprises a positioning station, a sampling station, a processing station and a control station, wherein a positioning vacancy is used for positioning the head placement posture of a user, the sampling station is used for collecting throat swab samples of the user, the processing station is used for recovering the collected throat swab samples of the user, and the control station is used for controlling the operation of the positioning station, the sampling station and the processing station;
the positioning station is provided with a gravity sensor, when the gravity sensor senses that the real-time bearing weight of a positioning vacancy changes, the gravity sensor triggers the acquisition layer to operate, the positioning station operates in a stage for supporting the chin of a user, the head of the user is arranged on the positioning station, the sampling station operates in a stage for automatic alignment, the sampling end of the throat swab is aligned to the mouth of the user, and after the sampling end of the throat swab is aligned to the mouth of the user, the throat swab sampling operation is further operated and executed.
3. The intelligent throat swab sampling device control system based on machine vision according to claim 1, wherein the control terminal is electrically connected with an analysis module selection module through a medium, the analysis module is connected with a camera module and a voice module through a local area network for data sharing, the camera module is electrically connected with the voice module through the medium, the selection module is electrically connected with a receiving module through the medium, the receiving module is electrically connected with a processing module and an identification module through the medium, the identification module is electrically connected with a setting module through the medium, and the setting module is electrically connected with a logic module and a control module through the medium.
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