CN114708632A - Digestive endoscopy visit robot face recognition system - Google Patents
Digestive endoscopy visit robot face recognition system Download PDFInfo
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- CN114708632A CN114708632A CN202210309463.0A CN202210309463A CN114708632A CN 114708632 A CN114708632 A CN 114708632A CN 202210309463 A CN202210309463 A CN 202210309463A CN 114708632 A CN114708632 A CN 114708632A
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Abstract
The invention discloses a digestive endoscopy visit robot face recognition system, which comprises: the system comprises a multimedia diagnosis robot, a multimedia patient end and a multimedia medical care end; the multi-media diagnosis robot comprises a diagnosis robot body, a storage module, a first recognition module, an appointment processing module, a face acquisition module, an image feature extraction module, a second recognition module and a result output module. According to the digestive endoscopy diagnosis robot face recognition system, the robot is used for checking the appointment code and the appointment information related to the appointment code, a face recognition database is established, the image feature extraction module and the second recognition module are used for comparing and recognizing the feature vector of the face through the multimedia medical end, the accuracy of the information of the patient to be diagnosed is improved, medical staff is effectively prevented from confusing and even mistaking the information of the patient, the working efficiency of a medical institution is improved, and the degree of satisfaction of the patient to be diagnosed is improved.
Description
Technical Field
The invention relates to the technical field of face recognition, in particular to a robot face recognition system for a digestive endoscopy diagnosis.
Background
A set of equipment for acquiring images directly from the digestive tract or acquiring ultrasonic or X-ray images of the digestive tract and digestive organs by equipment with ultrasonic and X-ray to diagnose and treat digestive system diseases. Can be divided into esophagoscope, gastroscope, duodenoscope, colonoscope, enteroscope, ultrasonic endoscope, capsule endoscope, choledochoscope (including primary and secondary endoscopes), pancreatoscope, laparoscope, laser confocal endoscope and the like according to the attributes of the endoscopes used for examination; the endoscope is divided into an upper gastrointestinal endoscope, a lower gastrointestinal endoscope, an Endoscopic Retrograde Cholangiopancreatography (ERCP), an ultrasonic endoscope and the like according to the examination part and the function; the clinical application of the digestive endoscope is divided into a diagnostic digestive endoscope and a therapeutic digestive endoscope.
In the digestive endoscopy process, when a nurse calls a patient to enter a preparation room and a doctor calls the patient to enter a diagnosis room to make a diagnosis and a treatment in each diagnosis room, if the condition that the same name and the same name are different in sex or are the same in tone among a plurality of patients occurs, not only is the medical care personnel confused and even the information of the patient is mistaken, the diagnosis result is influenced, but also the diagnosis efficiency is reduced, and the labor intensity of the medical care personnel is increased. Therefore, a digestive endoscopy diagnosis robot face recognition system is provided.
Disclosure of Invention
The invention mainly aims to provide a digestive endoscopy treatment robot face recognition system which can effectively solve the problems in the background technology.
In order to achieve the purpose, the invention adopts the technical scheme that:
a digestive endoscopy treatment robot face recognition system comprises a multimedia treatment robot, a multimedia patient end and a multimedia medical care end;
the multimedia diagnosis robot comprises a diagnosis robot body, a storage module, a first identification module, an appointment processing module, a face acquisition module, an image feature extraction module, a second identification module and a result output module;
the storage module is used for storing appointment codes generated by patients through appointment of patients in advance and appointment information related to the appointment codes, and establishing a face recognition database;
the first identification module is connected with the storage module and is used for identifying the appointment code displayed by the patient and retrieving the matched appointment information from the storage module according to the identification result;
the appointment processing module is connected with the first identification module and is used for sending the appointment information and the face identification database retrieved by the first identification module to a multimedia medical care end;
the face acquisition module is connected with the reservation processing module and is used for acquiring a face image of a patient and taking the face image of the patient as an input image of a face recognition system;
the image feature extraction module is connected with the face acquisition module and is used for extracting feature vectors of images input by the face acquisition module;
the second identification module is connected with the image feature extraction module and used for the multimedia medical care end to compare the feature vector of the input image with the face feature vector stored in the storage module to obtain an identification result;
and the result output module is connected with the second identification module and used for outputting the identification result.
Preferably, the establishing of the face recognition database includes: and acquiring reliable images of all people, extracting the face features of the reliable images and recording face feature information in a database.
Preferably, the acquiring the reliable images of all people specifically includes acquiring reliable image information of n people, and each person acquires m reliable images, where m and n are positive integers.
Preferably, the extracting of the face features of the reliable image specifically includes:
preprocessing the jth reliable face image of the ith person, wherein i is more than 0 and less than n +1, j is more than 0 and less than m +1, and m and n are positive integers;
and performing wavelet decomposition on the jth image of the ith person to obtain a low-frequency LL partial sub-image, performing Fourier transform on the low-frequency LL partial sub-image, and taking the amplitude of the low-frequency LL partial sub-image as the spectral feature Si, j of the reliable image.
Preferably, the preprocessing the jth reliable face image of the ith person is to perform dimension reduction processing on each reliable image through wavelet transformation.
Preferably, the image feature extraction module specifically includes:
preprocessing the input image;
and performing wavelet decomposition on the input image to obtain a low-frequency LL part sub-image, performing Fourier transform on the low-frequency LL part sub-image, and taking the amplitude of the low-frequency LL part sub-image as the spectral characteristic Y' of the input image.
Preferably, the second recognition module is configured to sequentially compare the feature vector Si, j of each face in the face database with the feature vector Y' of the input image, and specifically includes:
carrying out normalization processing on Si, j and Y';
measuring the similarity of the two vectors by using a cosine value of an included angle between the vectors, and enabling the similarity di, j to be cos (Si, j, Y');
feature determination is performed by di, j.
Preferably, the first identification module comprises an identity identification unit, a networking reading unit and an identity photo storage unit; the first identification module is used for inputting information through an identity card or a social security card, and the identity photo storage unit is used for storing the successfully input face information.
Preferably, the second identification module comprises a storage unit and an identification unit; the identification unit performs comparison identification through the internal storage information of the identity photo storage unit; the storage unit is used for storing the face image information without matching data.
Compared with the prior art, the invention has the following beneficial effects:
the invention uses the robot to check the appointment code and the appointment information related to the appointment code, automatically collects the face information of the patient, establishes the face recognition database, enables the image feature extraction module and the second recognition module to compare and recognize the feature vector of the face through the multimedia medical care end, improves the accuracy of the information of the patient to be diagnosed, effectively avoids medical care personnel from confusing and even mistaking the information of the patient, improves the working efficiency of a medical institution, improves the medical satisfaction degree of the patient, and effectively relieves the doctor-patient relationship.
Drawings
Fig. 1 is a structural diagram of a face recognition system of a robot for digestive endoscopy.
Detailed Description
In order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the invention is further described with the specific embodiments.
In the description of the present invention, it should be noted that the terms "upper", "lower", "inner", "outer", "front", "rear", "both ends", "one end", "the other end", and the like indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it is to be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "disposed," "connected," and the like are to be construed broadly, such as "connected," which may be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Examples
A digestive endoscopy treatment robot face recognition system comprises a multimedia treatment robot, a multimedia patient end and a multimedia medical care end;
the multimedia diagnosis robot comprises a diagnosis robot body, a storage module, a first identification module, an appointment processing module, a face acquisition module, an image feature extraction module, a second identification module and a result output module;
the system comprises a storage module, a face recognition module and a face recognition module, wherein the storage module is used for storing an appointment code generated by a patient through a diagnosis appointment in advance and appointment information related to the appointment code, and establishing a face recognition database; the establishment of the face recognition database comprises the following steps: acquiring reliable images of all people, extracting face characteristics of the reliable images and recording face characteristic information in a database; the method comprises the following steps that the reliable image acquisition of all people is specifically to acquire reliable image information of n people, each person acquires m reliable images, and m and n are positive integers; the face feature extraction of the reliable image specifically comprises the following steps:
preprocessing the jth reliable face image of the ith person, wherein i is more than 0 and less than n +1, j is more than 0 and less than m +1, and m and n are positive integers;
performing wavelet decomposition on the jth image of the ith person to obtain a low-frequency LL partial sub-image, performing Fourier transform on the low-frequency LL partial sub-image, and taking the amplitude of the low-frequency LL partial sub-image as the spectral feature Si, j of the reliable image; the preprocessing the jth reliable face image of the ith person is to perform dimension reduction processing on each reliable image through wavelet transformation;
the image feature extraction module specifically comprises:
preprocessing the input image;
performing wavelet decomposition on the input image to obtain a low-frequency LL part sub-image, performing Fourier transform on the low-frequency LL part sub-image, and taking the amplitude of the low-frequency LL part sub-image as the spectral characteristic Y' of the input image;
the first identification module is connected with the storage module and is used for identifying the appointment code displayed by the patient and retrieving the matched appointment information from the storage module according to the identification result; the first identification module comprises an identity identification unit, a networking reading unit and an identity photo storage unit; the first identification module is used for inputting information through an identity card or a social security card, and the identity photo storage unit is used for storing the successfully input face information;
the appointment processing module is connected with the first identification module and is used for sending the appointment information and the face identification database retrieved by the first identification module to a multimedia medical care end;
the face acquisition module is connected with the reservation processing module and is used for acquiring a face image of a patient and taking the face image of the patient as an input image of a face recognition system;
the image feature extraction module is connected with the face acquisition module and is used for extracting feature vectors of images input by the face acquisition module;
the second identification module is connected with the image feature extraction module and used for the multimedia medical care end to compare the feature vector of the input image with the face feature vector stored in the storage module to obtain an identification result; the second recognition module is used for comparing the feature vector Si, j of each face in the face database with the feature vector Y' of the input image in sequence, and specifically comprises:
carrying out normalization processing on Si, j and Y';
measuring the similarity of the two vectors by using a cosine value of an included angle between the vectors, and enabling the similarity di, j to be cos (Si, j, Y');
judging the characteristics through di, j; the second identification module comprises a storage unit and an identification unit; the identification unit performs comparison identification through the internal storage information of the identity photo storage unit; the storage unit is used for storing the face image information without matching data;
and the result output module is connected with the second identification module and used for outputting the identification result.
The invention uses the robot to check the appointment code and the appointment information related to the appointment code, automatically collects the face information of the patient, establishes the face recognition database, enables the image feature extraction module and the second recognition module to compare and recognize the feature vector of the face through the multimedia medical care end, improves the accuracy of the information of the patient to be diagnosed, effectively avoids medical care personnel from confusing and even mistaking the information of the patient, improves the working efficiency of a medical institution, improves the medical satisfaction degree of the patient, and effectively relieves the doctor-patient relationship.
The foregoing shows and describes the general principles and broad features of the present invention and advantages thereof. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (9)
1. The utility model provides a robot face identification system sees a doctor to digestion scope which characterized in that: the system comprises a multimedia diagnosis robot, a multimedia patient end and a multimedia medical care end;
the multimedia diagnosis robot comprises a diagnosis robot body, a storage module, a first identification module, an appointment processing module, a face acquisition module, an image feature extraction module, a second identification module and a result output module;
the system comprises a storage module, a face recognition module and a face recognition module, wherein the storage module is used for storing an appointment code generated by a patient through a diagnosis appointment in advance and appointment information related to the appointment code, and establishing a face recognition database;
the first identification module is connected with the storage module and is used for identifying the appointment code displayed by the patient and retrieving the matched appointment information from the storage module according to the identification result;
the appointment processing module is connected with the first identification module and is used for sending the appointment information and the face identification database retrieved by the first identification module to a multimedia medical care end;
the face acquisition module is connected with the reservation processing module and is used for acquiring a face image of a patient and taking the face image of the patient as an input image of a face recognition system;
the image feature extraction module is connected with the face acquisition module and is used for extracting a feature vector of an image input by the face acquisition module;
the second identification module is connected with the image feature extraction module and used for the multimedia medical care end to compare the feature vector of the input image with the face feature vector stored in the storage module to obtain an identification result;
and the result output module is connected with the second identification module and used for outputting the identification result.
2. The robot face recognition system for endoscope diagnosis according to claim 1, wherein: the establishment of the face recognition database comprises the following steps: and acquiring reliable images of all people, extracting the face features of the reliable images and recording face feature information in a database.
3. The robot face recognition system for endoscope diagnosis according to claim 1, wherein: the method comprises the steps of collecting reliable images of all people specifically collecting reliable image information of n people, wherein each person collects m reliable images, and m and n are positive integers.
4. The robot face recognition system for endoscope diagnosis according to claim 3, wherein: the face feature extraction of the reliable image specifically comprises the following steps:
preprocessing the jth reliable face image of the ith person, wherein i is more than 0 and less than n +1, j is more than 0 and less than m +1, and m and n are positive integers;
and performing wavelet decomposition on the jth image of the ith person to obtain a low-frequency LL partial sub-image, performing Fourier transform on the low-frequency LL partial sub-image, and taking the amplitude of the low-frequency LL partial sub-image as the spectral feature Si, j of the reliable image.
5. The robot face recognition system for endoscope diagnosis according to claim 4, wherein: the preprocessing of the jth reliable face image of the ith person is specifically to perform dimension reduction processing on each reliable image through wavelet transformation.
6. The robot face recognition system for endoscope diagnosis according to claim 1, wherein: the image feature extraction module specifically comprises:
preprocessing the input image;
and performing wavelet decomposition on the input image to obtain a low-frequency LL part sub-image, performing Fourier transform on the low-frequency LL part sub-image, and taking the amplitude of the low-frequency LL part sub-image as the spectral characteristic Y' of the input image.
7. The robot face recognition system for endoscope diagnosis according to claim 6, wherein: the second recognition module is used for comparing the feature vector Si, j of each face in the face database with the feature vector Y' of the input image in sequence, and specifically comprises:
carrying out normalization processing on Si, j and Y';
measuring the similarity of the two vectors by using a cosine value of an included angle between the vectors, and enabling the similarity di, j to be cos (Si, j, Y');
feature determination is performed by di, j.
8. The robot face recognition system for endoscope diagnosis according to claim 1, wherein: the first identification module comprises an identity identification unit, a networking reading unit and an identity photo storage unit; the first identification module is used for inputting information through an identity card or a social security card, and the identity photo storage unit is used for storing the successfully input face information.
9. The robot face recognition system for endoscope diagnosis according to claim 1, wherein: the second identification module comprises a storage unit and an identification unit; the identification unit performs comparison identification through the internal storage information of the identity photo storage unit; the storage unit is used for storing the face image information without matching data.
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| CN116719966A (en) * | 2023-05-25 | 2023-09-08 | 中国医学科学院皮肤病医院(中国医学科学院皮肤病研究所) | Hospital patient information management system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116719966A (en) * | 2023-05-25 | 2023-09-08 | 中国医学科学院皮肤病医院(中国医学科学院皮肤病研究所) | Hospital patient information management system |
| CN116719966B (en) * | 2023-05-25 | 2024-03-08 | 中国医学科学院皮肤病医院(中国医学科学院皮肤病研究所) | Hospital patient information management system |
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