WO2021261642A1 - Système de correction de température mesurée - Google Patents

Système de correction de température mesurée Download PDF

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Publication number
WO2021261642A1
WO2021261642A1 PCT/KR2020/008547 KR2020008547W WO2021261642A1 WO 2021261642 A1 WO2021261642 A1 WO 2021261642A1 KR 2020008547 W KR2020008547 W KR 2020008547W WO 2021261642 A1 WO2021261642 A1 WO 2021261642A1
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temperature
image
distance
unit
camera unit
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PCT/KR2020/008547
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English (en)
Korean (ko)
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조문석
홍성견
서인석
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쿨사인 주식회사
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Publication of WO2021261642A1 publication Critical patent/WO2021261642A1/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
    • G01J5/0022—Radiation pyrometry, e.g. infrared or optical thermometry for sensing the radiation of moving bodies
    • G01J5/0025—Living bodies
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
    • G01J5/02—Constructional details
    • G01J5/06—Arrangements for eliminating effects of disturbing radiation; Arrangements for compensating changes in sensitivity
    • G01J5/064—Ambient temperature sensor; Housing temperature sensor; Constructional details thereof
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
    • G01J5/02—Constructional details
    • G01J5/06—Arrangements for eliminating effects of disturbing radiation; Arrangements for compensating changes in sensitivity
    • G01J5/068—Arrangements for eliminating effects of disturbing radiation; Arrangements for compensating changes in sensitivity by controlling parameters other than temperature
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
    • G01J5/60—Radiation pyrometry, e.g. infrared or optical thermometry using determination of colour temperature
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
    • G01J5/80—Calibration
    • G01J5/804—Calibration using atmospheric correction
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/30—Determination of transform parameters for the alignment of images, i.e. image registration
    • G06T7/33—Determination of transform parameters for the alignment of images, i.e. image registration using feature-based methods
    • G06T7/337—Determination of transform parameters for the alignment of images, i.e. image registration using feature-based methods involving reference images or patches
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
    • G01J2005/0077—Imaging

Definitions

  • the present invention pertains to a technique of machine learning data collected from a plurality of object measuring devices and the like, and correcting the temperature of an object measured by a thermal imaging camera based on the learned data.
  • thermal imaging camera In order to quickly measure the fever of many people, a thermal imaging camera is being used.
  • a thermal imaging camera is a device that tracks and detects heat and displays it on the screen.
  • Thermal imaging cameras including Focal Plane Arrays (FPA) and uncooled microbolometers, accurately measure the temperature of objects within measurable distances.
  • FPA Focal Plane Arrays
  • microbolometers uncooled microbolometers
  • Such a thermal imaging camera detects the heat generated by an object and makes it possible to determine how much heat is generated in which part of the object.
  • the thermal imaging camera uses the size of the area that can accurately detect heat from the measurable distance as the standard range for measuring temperature.
  • the measurable distance of a conventional thermal imaging camera can be accurately determined according to a Spot Size Ratio (SSR) value according to an Instantaneous Filed Of View (IFOV).
  • SSR Spot Size Ratio
  • IFOV Instantaneous Filed Of View
  • a value of 1,000/1 means that the average temperature of an area of 1 square mm can be measured at a distance of 1,000 mm from the subject.
  • the size of the subject must be larger than the Instantaneous Filed Of View (IFOV) to measure the external radiation temperature except for the temperature of the subject.
  • IFOV Instantaneous Filed Of View
  • an error occurs when compared with the measured value using a temperature reference device such as a black body at both sides below the reference distance and above the reference distance. Also, when the subject is a human body, an error may occur in the measured temperature due to other heat sources possessed by the subject. That is, the temperature measurement result using the thermal imaging camera contains an error according to the distance between the inspection equipment and the object to be inspected.
  • An object of the present invention is to solve a problem in which the temperature of an object cannot be accurately measured due to environmental factors and limitations of a thermal imaging camera.
  • an optical camera unit for generating a first video image by photographing an object
  • thermal imaging camera unit for generating a second video image by photographing an object as a thermal image
  • a distance measuring unit for calculating a distance to a spaced black body and a distance to a spaced object
  • the correction temperature measured at different temperatures is set according to the distance between the thermal imaging camera unit and the object,
  • a measurement correction unit configured to generate a corrected temperature image by applying the corrected temperature to the mapped image.
  • the measurement correction unit calculates the measurement correction unit
  • a detection module for detecting a preset portion in the first image image and the second image image
  • mapping module for mapping the first detected image detected from the first video image through the detection module and the second detected image detected from the second video image
  • a temperature measurement module for measuring the average temperature of the detection site in the mapped image
  • a correction module configured to generate a corrected temperature image by applying the correction temperature to the mapped image.
  • the detection module may detect a face part of the human body.
  • the optical camera unit measures the temperature and humidity of the place where the object is photographed and transmits the measured temperature data and humidity data to the measurement correction unit to be utilized as machine-learning data It may further include an element measurement unit.
  • the measurement temperature correction system of the present invention identifies a specific part of the subject by determining whether the subject is a human body, and reflects the machine-learned average temperature of the specific part in the identified part to accurately measure the temperature of the subject.
  • the measurement temperature compensation system collects measurement results according to the performance of the thermal imaging camera, the performance of the lens and thermal imaging detector used, and the distance to the subject, and additionally substitutes variables for the surrounding environment to measure the exact temperature. let it be
  • FIG. 1 is a view showing a measurement temperature correction system according to an embodiment of the present invention.
  • FIG. 2 is a diagram specifically illustrating the measurement correction unit of FIG. 1 .
  • FIG 3 is a view showing a first image image taken by the optical camera unit and a detection image detected by the measurement correction unit.
  • FIG. 4 is a view showing a second image image taken by the thermal imaging camera unit and a detected image detected by the measurement correction unit.
  • 5 is a diagram illustrating a state in which the distance measurement unit measures the distance between the thermal imaging camera unit and the object and transmits the measured distance value to the measurement correction unit.
  • FIG. 6 is a diagram illustrating a state in which the distance measuring unit calculates the corrected temperature according to the distance of the object centered on the black body.
  • FIG. 7 is a diagram illustrating a mapped image by mapping a face detected by the optical camera unit of FIG. 3 and a face detected by the thermal imaging camera unit of FIG. 4 .
  • FIG. 9 is a diagram illustrating a state in which the measurement correction unit corrects the temperature of the mapped image to correspond to the measurement distance value.
  • FIG. 10 is a diagram illustrating a state in which the measurement correction unit performs machine learning of a distance value and a temperature correction value from a temperature-corrected image.
  • FIG. 11 is a view showing a measurement temperature correction system according to another embodiment of the present invention.
  • the measurement temperature compensation system will be described in general with reference to FIG. 1 .
  • the components of the measurement temperature correction system will be described with reference to FIGS. 1 and 2
  • the operation of the measurement temperature correction system will be described with reference to FIGS. 3 and 10 .
  • FIG. 1 is a view showing a measurement temperature correction system according to an embodiment of the present invention.
  • the measurement temperature correction system 1 of the present invention captures an object, that is, a subject, identifies a specific part of the subject, and reflects the machine-learned average temperature of the specific part to the identified part to accurately calculate the temperature of the subject.
  • the measurement temperature correction system of the present invention detects the face of a subject using the optical camera unit 10 and the thermal imaging camera unit 20, and the image captured by the optical camera unit 10 and the thermal imaging camera unit By mapping the image taken in (20), the average temperature of the subject's face is first measured, and the temperature measurement result according to the distance between the thermal imaging camera unit and the subject is measured as an example of the distance measuring unit, and the distance measuring sensor , Depth camera, 3D camera, etc., using a device capable of measuring the distance between the reference point and the target, calculates a correction value based on the distance measurement value of the subject and the thermal imaging camera unit. Then, the collected measurement result value and correction value are machine-learned, and a more accurate correction value is calculated and corrected.
  • the correction value becomes a correction temperature
  • the correction temperature is based on the reference temperature measured from the black body 60 in the thermal imaging camera unit 20 according to the distance between the thermal imaging camera unit 20 and the object M. The measured temperature becomes the other temperature.
  • the measurement temperature correction system 1 having such characteristics includes an optical camera unit 10 , a thermal image camera unit 20 , a distance measurement unit 30 , and a measurement correction unit 40 .
  • FIG. 1 is a diagram illustrating a measurement temperature correction system according to an embodiment of the present invention
  • FIG. 2 is a diagram specifically illustrating the measurement correction unit of FIG. 1 .
  • the optical camera unit 10 captures a signal reflecting sunlight to photograph an object and generates a first video image. That is, the optical camera unit 10 creates a video image by photographing the subject.
  • the thermal imaging camera unit 20 may be located adjacent to the optical camera unit 10 .
  • the thermal imaging camera unit 20 generates a second video image by photographing the object as a thermal image.
  • the thermal imaging camera unit 20 may measure thermal energy generated from the black body 60 and measure thermal energy emitted from the object.
  • a typical focal plane array assembly included in the thermal imaging camera unit 20 has about 60,000 to 1,000,000 or more individual detectors depending on the size and resolution, and is converted into a two-dimensional pixel matrix from 160 X 120 pixels to 1024 X 1024 pixels. You can create video images.
  • the thermal imaging camera unit using the microbolometer-type detector responds to a change in the state of the material (bolometer effect) by the incident radiation energy.
  • the field of view (FOV) of the thermal imaging camera unit 20 is different depending on the size of the lens and the focal plane.
  • the resolution (IFOV) is determined by the performance of the lens and detector FPA.
  • the effective minimum measurement area of the thermal imaging camera unit and the accurate temperature measurement distance can be calculated.
  • the distance measuring unit 30 is positioned on the same line as the optical camera unit 10 or the thermal imaging camera unit 20 to calculate the distance between the thermal imaging camera unit 20 and the optical camera unit 10 and the object. In addition, the distance measuring unit 30 measures a distance separated from the black body 60 . That is, the distance measuring unit 30 calculates the distance to the spaced black body 60 and the distance to the spaced object M.
  • the distance measuring unit 30 may calculate the distance between the objects photographed by the optical camera unit 10 or the thermal imaging camera unit 20 in any one of mm, cm, or m units. As an example, distance data calculated by photographing at intervals of 2 m may be calculated. Then, the calculated distance data is transmitted to the measurement correction unit 40 .
  • the black body 60 becomes a temperature reference module connected to the measurement correction unit 40 from the outside of the measurement correction unit 40 .
  • the measurement correction unit 40 calculates the distance between the thermal imaging camera unit 110 and the black body 60 and the distance between the thermal imaging camera unit 110 and the subject.
  • the measurement correction unit 40 is a distance between the thermal imaging camera unit 20 and the object M based on the reference temperature and the reference temperature measured from the black body 60 in the thermal imaging camera unit 20 at the distance from the subject. It includes a correction temperature table in which correction temperatures measured at different temperatures according to distance are set.
  • the horizontal axis is the distance between the distance measuring unit 30 and the object M
  • the vertical axis is the reference temperature, so that the temperature values of different objects are set in each relation instance.
  • the measurement correction unit 40 may extract a correction temperature according to a change value for each distance from the subject using the correction temperature table.
  • the measurement correction unit 40 detects a preset portion in the first image image (A1) and the second image image (A2) taken from the optical camera unit 10 and the thermal imaging camera unit 20, and The first detection image detected from the first video image and the second detection image detected from the second video image may be mapped.
  • the average temperature of the detection portion is measured in the mapped image F3 , and the correction temperature can be extracted from the above-described correction temperature table corresponding to the distance between the object and the thermal imaging camera unit 20 . And by giving the extracted correction temperature to the mapped image F3, it is possible to generate the corrected temperature image NT.
  • the temperature value set in each cell of the corrected temperature table may be a value calculated as a linear approximation value of the temperature change by distance by applying a linear regression method.
  • the linear equation obtained here can be applied to the measurement temperature correction of the subject.
  • the actual measured values for the reference temperature and the measured temperature may be calculated as a graph as shown in FIG. 8 .
  • the measurement correction unit 40 may perform machine learning with a multi-layered layer to compensate for the case in which the measured temperature is not linear according to the characteristics of the thermal imaging camera unit 20 .
  • the learning is carried out by configuring multi-layer layers such as convolution layer, ReLU layer, pooling layer, fully-connected layer, drop-out layer, and final layer through machine learning, correction of nonlinear values at a specific distance in the graph is performed. It is possible.
  • the measurement correction unit 40 that performs various functions may be a computer in which a plurality of components are combined.
  • the plurality of components are, as shown in FIG. 2 , a detection module 410 , a grid module 420 , a mapping module 430 , a temperature measurement module 440 , a calculation module 450 , and a correction module 460 . ) and so on.
  • the detection module 410 detects a preset portion in the first video image A1 and the second video image A2.
  • the preset part may be a face part of the human body.
  • the grid module 420 divides the first detection image F1 and the second detection image F2 into grids to form a plurality of regions so that different correction temperatures are reflected in each region.
  • the mapping module 430 maps the first detection image F1 detected from the first image image A1 through the detection module 410 and the second detection image F2 detected from the second image image A2. (Mapping).
  • the mapping refers to a process of generating one image by covering the first detection image F1 with the second detection image F2.
  • the temperature measurement module 440 is divided by the grid module 420 and the temperature is reflected in each area, and then measures the average temperature of the face part from the mapped image F3 generated by the mapping module 430 and extracts the average temperature value.
  • the calculation module 450 collects data from the optical camera unit 10 , the thermal imaging camera unit 20 , and the distance measurement unit 30 including the reference temperature to correspond to the distance between the object and the thermal imaging camera unit 20 . Then, the corrected temperature is calculated.
  • the correction module 460 generates a corrected temperature image NT by applying a correction temperature to the mapped image F3 .
  • FIG. 3 is a view showing a first image image taken by the optical camera unit and a detection image detected by the measurement correction unit
  • FIG. 4 is a second image image photographed by the thermal imaging camera unit and a detection image detected by the measurement correction unit
  • FIG. 5 is a diagram illustrating a state in which the distance measuring unit measures the distance between the thermal imaging camera unit and the object, and transmitting the measured distance value to the measurement correction unit.
  • FIG. 6 is a view showing a state in which the distance measuring unit calculates the correction temperature according to the distance of the object centered on the black body
  • FIG. 7 is the face detected by the optical camera unit of FIG. 3 and the thermal image camera unit of FIG. It is a diagram showing a mapped image by mapping a detected face
  • FIG 8 is a graph showing a temperature change state measured for each distance.
  • Figure 9 is a view showing a state in which the temperature of the image mapped to correspond to the measurement distance value in the measurement correction unit is corrected,
  • Figure 10 is the distance value and the temperature correction value from the temperature corrected image in the measurement correction unit It is a diagram showing the state of learning.
  • the measurement correction unit 40 photographs the object M with the optical camera unit 10 and the thermal imaging camera unit 20, as shown in FIGS. 3 and 4, and includes a first video image A1 and a second A video image A2 is created. Thereafter, the generated first video image A1 and the second video image A2 are transmitted to the measurement correction unit 40 .
  • the measurement correction unit 40 detects a face part in the first image image A1 and the second image image A2 as the first detection image F1 and the second detection image F2. Also, the measurement correction unit 40 may generate the mapped image F3 by mapping the detected first detection image F1 and the second detection image F2 as shown in FIG. 5 .
  • the distance measuring unit 30 may calculate the distance between the object M and the thermal imaging camera unit 20 or the optical camera unit 10 as shown in FIG. 5 . In addition, the distance from the black body 60 may be calculated and transmitted to the measurement correction unit 40 .
  • the distance measuring unit 30 calculates the separation distance (B_Distance) from the black body 60 as shown in FIG. 6, and the first separation distance (A1_Distance) of the object and the second separation distance of the object ( A2_Distance) can be calculated.
  • the distance measuring unit 30 only calculates the first separation distance and the second separation distance, but it is not limited to measuring the separation distance of only two objects, and N separation distances are sequentially measured. can do.
  • the measured values of the N separation distances may be transmitted to the measurement correction unit 40 .
  • the measurement correction unit 40 measures the average temperature of the mapped image F3 as shown in FIG. 7 , and the temperature change rate compared to the preset reference temperature corresponding to the distance between the object M and the optical camera unit 10 . can calculate the corrected temperature value by reflecting the machine learning value.
  • the measurement correction unit 40 may reflect the calculated correction temperature value to the mapped image F3 as shown in FIG. 8 and generate an image NT in which the correction temperature value is reflected.
  • the measurement correction unit 40 machine-learns the measurement result value and correction value from the image NT to which the correction temperature value is reflected, so that a more accurate correction temperature value can be reflected in the mapped image F3 to be newly created later. do.
  • the measurement correction unit 40 divides the second detection image F2 into nine grid regions through the above-described elements and adjusts the black body 60, that is, the temperature reference module to be maintained in each region,
  • the measured temperature can be recorded sequentially by distance while moving the object (the object whose temperature is measured to calculate the temperature value written in the initial calibration temperature table) from 50cm to 500cm.
  • the number of data in the measured ordered set to be learned that is, the value of the separation distance of the object measured according to the movement of the object is N
  • half of the data is used as the learning data.
  • the other half is used as data for machine learning verification.
  • the measurement correction unit 40 divides N/2 and N/2 first and second detection images among the calculated N data into 9 grids (C), and then divides the first detection images with the same distance. and the second detection image to generate N/2 mapped images F3. And after allocating the correction temperature for each distance to each grid area of the generated N/2 mapped images, the average temperature of N/2 pieces is calculated. Then, the calculated N/2 average temperatures are reflected and displayed in the N/2 corrected temperature images NT.
  • the measurement correction unit 40 includes the remaining N/2 first detected images and the second detected images that are not used for generating the corrected temperature image among the calculated N data are Convolution layer, ReLU Layer, Pooling layer, Fully-connected Creates an image (F4) mapped with multi-layer layers such as layer, drop-out layer, and final layer, reflects the correction temperature in each grid area of the generated mapped image (F4), and then assigns the image to each grid area again.
  • the corrected temperature value is extracted and machine-learned so that a more accurate correction temperature is reflected in the grid area of the image F3 mapped later.
  • the measurement correction unit 40 calculates each of the first lattice-divided first detection image and the first lattice-divided second detection image calculated as shown in FIG.
  • a correction temperature for each distance can be assigned to the grid area.
  • the average temperature of the correction temperature allocated to each grid region of the mapped image may be calculated, and the corrected temperature image NT to which the calculated value is allocated may be generated.
  • the calculated second grid-divided first detection image and the second grid-divided second detection image are mapped to generate a mapped image F4, and the generated mapped image F4 ) can be assigned a correction temperature for each distance in each grid area.
  • the correction temperature allocated to each grid region of the mapped image F4 may be different from the correction temperature allocated to each mustard region of the mapped image F3 described above.
  • the measurement correction unit 40 extracts the correction temperature assigned to each lattice of the mapped image F4 and machine-learns it so that a more accurate correction temperature is reflected in each lattice region of the mapped image F3 later.
  • the measurement temperature correction system according to another embodiment of the present invention is the same as that of the measurement temperature correction system according to an embodiment of the present invention, except that it further includes an external element measurement unit.
  • the external element measurement unit 50 included in the measurement temperature correction system 1-1 is a device for measuring the temperature and humidity of a place where the optical camera unit 10 captures an object. .
  • the external element measurement unit 50 transmits the measured temperature data and humidity data to the measurement correction unit 40 .
  • the measurement correction unit 40 uses the transmitted temperature data and humidity data as base data for more accurately calculating a corrected temperature value and performs machine learning.
  • the external element measuring unit 50 is installed at the place where the optical camera unit 10 and the thermal imaging camera unit 20 are installed to more accurately measure the external environment in which the object M is located.
  • the measurement temperature correction system (1, 1-1) of the present invention identifies the face of an object, calculates the primary temperature of the identified face, and reflects the average temperature of the identified part of the face part. to accurately display the temperature.
  • the measurement temperature compensation system (1, 1-1) collects the measurement results according to the performance of the thermal imaging camera, the performance of the used lens and thermal imaging detector, and the distance to the subject, and additionally substitutes variables for the surrounding environment Thus, it is possible to reflect and display a more accurate temperature on the face part.

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Abstract

La présente invention concerne un système de correction de température mesurée qui photographie un objet, c'est-à-dire un sujet, identifie une partie spécifique du sujet et reflète la température moyenne apprise par machine de la partie spécifique sur la partie identifiée de façon à calculer avec précision la température du sujet. Le système de correction de température mesurée de la présente invention comprend : une unité de caméra optique qui génère une première image vidéo en photographiant un objet; une unité de caméra d'imagerie thermique qui génère une seconde image vidéo en photographiant de l'objet sous la forme d'une image thermique; une unité de mesure de distance qui calcule une distance jusqu'à un corps noir espacé et une distance jusqu'à un objet espacé; et une unité de correction de mesure qui détecte une partie prédéfinie à partir de la première image vidéo et de la seconde image vidéo, cartographie une première image détectée à partir de la première image vidéo et une seconde image détectée à partir de la seconde image vidéo, mesure la température moyenne des parties détectées sur l'image cartographiée, définit une température corrigée mesurée à différentes températures en fonction de la distance entre l'unité de caméra d'imagerie thermique et l'objet, sur la base d'une température de référence mesurée à partir du corps noir par l'unité de caméra d'imagerie thermique, extrait une température corrigée prédéfinie à partir de la distance entre l'unité de caméra d'imagerie thermique et l'objet calculée par l'unité de mesure de distance, et applique la température corrigée à l'image cartographiée de façon à générer une image de température corrigée.
PCT/KR2020/008547 2020-06-22 2020-06-30 Système de correction de température mesurée WO2021261642A1 (fr)

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