CN115112248A - Infrared imaging temperature measurement method and device, server and readable storage medium - Google Patents
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Abstract
The application provides an infrared imaging temperature measurement method, an infrared imaging temperature measurement device, a server and a readable storage medium, wherein the infrared imaging temperature measurement method comprises the following steps: acquiring an infrared image P k And the lens temperature T for photographing the same m (ii) a From the infrared image P k Obtaining an infrared image P k Gray value Y of each pixel point m (ii) a Will T opitc ＝T m ，Y＝Y m Substituting the infrared image P into a response model, and solving to obtain an infrared image P k Black body temperature T corresponding to each pixel point b . The response model is obtained by respectively substituting a plurality of calibration arrays into a formula, solving unknown numbers and inversely substituting the solved unknown numbers into the formula; by the method, the gray value of each pixel point finally output is not limited by the working state of the thermal imagerThe output result is obtained through the self-adaptive response model, and the temperature measurement precision is further improved.
Description
Technical Field
The present disclosure relates generally to the field of infrared imaging technologies, and in particular, to an infrared imaging temperature measurement method, an infrared imaging temperature measurement device, a server, and a readable storage medium.
Background
All objects with a temperature above absolute zero continuously emit infrared radiant energy into the surrounding space. The distribution of the magnitude of the infrared radiation energy in terms of wavelength is quite closely related to its surface temperature. Therefore, by measuring the infrared energy emitted by the object itself, the surface temperature thereof can be accurately measured. According to the principle, the infrared thermal imager adopts a non-contact mode to quickly measure the surface temperature of an object, has the advantages of high response speed, high sensitivity, large single measurement area and visual measurement result, and is widely applied to the fields of electric power detection, security monitoring, epidemic prevention and control and the like.
However, due to the characteristics of the sensitive waveband and the limitation of the performance of the infrared detector, the working state of the thermal infrared imager is greatly influenced by the ambient temperature, and the response characteristics at high and low temperatures are greatly different from the response characteristics at normal temperature, so that the calibration of the thermal infrared imager data in the normal temperature environment cannot adapt to the working environment in a wide temperature range. In the aspect of data calibration, due to the nonlinear characteristic of imaging system response, a linear interpolation mode is adopted among multiple temperature calibration parameters, although the algorithm is simple, the actual response of the system cannot be accurately fitted, the optimal solution is not provided, and the temperature measurement precision cannot be further improved.
Disclosure of Invention
In view of the foregoing defects or shortcomings in the prior art, it is desirable to provide an infrared imaging temperature measurement method, an infrared imaging temperature measurement device, a server and a readable storage medium, which can solve the above technical problems.
The application provides an infrared imaging temperature measurement method in a first aspect, which comprises the following steps:
acquiring an infrared image P k And the lens temperature T for photographing the same m ；
According to the infrared image P k Obtaining the infrared image P k Gray value Y of each pixel point m ；
Will T opitc ＝T m ，Y＝Y m Substituting the infrared image P into the response model, and solving to obtain the infrared image P k Black body temperature T corresponding to each pixel point b ；
The response model is obtained by respectively substituting a plurality of calibration arrays into a formula (I), solving unknown numbers and substituting the solved unknown numbers into the formula (I); the calibration array comprises a blackbody temperature T b Corresponding to the black body temperature T b Gray value Y of the infrared image, and lens temperature T at the time of photographing the infrared image opitc (ii) a The formula (one) is as follows:
according to the technical scheme provided by the embodiment of the application, according to the infrared image P k Black body temperature T of each pixel point b And gray value Y m Generating the abscissa as the gray value Y m The ordinate is the black body temperature T b The inverse curve of (2).
According to the technical scheme provided by the embodiment of the application, according to the infrared image P k Obtaining the infrared image P k Gray value Y of each pixel point m Before, still include: for the infrared image P k And (6) filtering.
According to the technical scheme provided by the embodiment of the application, the infrared image P is corrected k The filtering method is realized by the following steps:
acquiring the infrared image P k Of successive frame pictures P k-1 、P k-2 、……、P 1 K is the current frame, and k is more than or equal to 4;
according to the continuous frame image P k-1 、P k-2 、……、P 1 Calculating the infrared image P k The steady state recording variable S of each pixel point (m, n) k (m, n); wherein m is the abscissa of the pixel point, n is the ordinate of the pixel point, and the stable state recording variable S k (m, n) is used for representing the stability degree of the pixel value change of the pixel point (m, n);
calculating the infrared image P according to the formula (II) k Of each pixel point (m, n) of (a) F (m,n,k)：
Wherein I (m, n, k) represents the infrared image P k Ts is a first set threshold.
According to the technical scheme provided by the embodiment of the application, the stable state record variable S k (m, n) is calculated by the following substeps:
judging the logic result T1 between the pixel value of the inter-frame difference and the second set threshold Thr according to the formula (III) k 、T2 k 、T3 k ：
Calculating the steady state recording variable S according to formula (IV) k (m,n)：
Wherein S is 3 (m,n)＝0。
According to the technical scheme provided by the embodiment of the application, the calibration array is obtained by the following substeps:
s 11: placing a black body and a thermal imager in an environmental test chamber, wherein the environmental test chamber is used for providing a test environment for the black body and the thermal imager; the thermal imager is used for shooting the infrared image of the black body
s 12: acquiring lens temperature T of thermal imager through sensor opitc (ii) a The sensor is installed on the thermal imager;
s 13: acquiring an infrared image shot by the thermal imager to obtain a gray value Y of the infrared image;
s 14: adjusting the environmental temperature of the environmental test chamber to adjust the lens temperature T of the thermal imager opitc (ii) a Adjusting a black body temperature T of the black body b (ii) a And repeating the steps s12-s13 to obtain a plurality of calibration arrays.
The second aspect of the present application provides an infrared imaging temperature measuring device, including:
an acquisition module for acquiring the infrared image P k And the lens temperature T for photographing the same m ；
A first processing module for processing the infrared image P k Obtaining the infrared image P k Gray value Y of each pixel point m ；
A computation module to convert T opitc ＝T m ，Y＝Y m Substituting the infrared image P into the response model, and solving to obtain the infrared image P k Black body temperature T corresponding to each pixel point b ；
Wherein the response model isRespectively substituting a plurality of calibration arrays into a formula (I), solving unknown numbers and substituting the solved numbers into the formula (I) to obtain the calibration data; the calibration array comprises a blackbody temperature T b Corresponding to the black body temperature T b Gray value Y of the infrared image and lens temperature T when the infrared image is taken opitc (ii) a The formula (one) is as follows:
according to the technical scheme provided by the embodiment of the application, the infrared imaging temperature measuring device further comprises: a second processing module for processing the infrared image P k Black body temperature T of each pixel point b And gray value Y m Generating the abscissa as the gray value Y m The ordinate is the black body temperature T b The inverse curve of (c).
According to the technical scheme provided by the embodiment of the application, a filtering module is arranged between the acquisition module and the first processing module and used for aligning the infrared image P k And (6) filtering.
According to the technical scheme provided by the embodiment of the application, the obtaining module is specifically configured to: acquiring the infrared image P k Of successive frame pictures P k-1 、P k-2 、……、P 1 K is the current frame, and k is more than or equal to 4; acquiring a lens temperature T for photographing the same m ；
The filtering module is specifically configured to:
according to the continuous frame image P k-1 、P k-2 、……、P 1 Calculating the infrared image P k The steady state recording variable S of each pixel point (m, n) k (m, n); wherein m is the abscissa of the pixel point, n is the ordinate of the pixel point, and the stable state recording variable S k (m, n) is used for representing the stability degree of the pixel value change of the pixel point (m, n);
calculating the infrared image P according to a formula (II) k Each pixel of (a)m, n) of the filtered value I F (m,n,k)：
Wherein I (m, n, k) represents the infrared image P k Ts is a first set threshold.
According to the technical scheme provided by the embodiment of the application, the stable state record variable S k (m, n) is calculated by the filtering module by the following substeps:
judging the logic result T1 between the pixel value of the inter-frame difference and the second set threshold Thr according to the formula (III) k 、T2 k 、T3 k ：
Calculating the steady state recording variable S according to formula (IV) k (m ,n )：
Wherein S is 3 (m,n)＝0。
According to the technical scheme provided by the embodiment of the application, the calibration array is obtained by the following substeps:
s 11: placing a black body and a thermal imager in an environmental test chamber, wherein the environmental test chamber is used for providing a test environment for the black body and the thermal imager; the thermal imager is used for shooting the infrared image of the black body
s 12: acquiring lens temperature T of thermal imager through sensor opitc (ii) a The sensor is installed on the thermal imager;
s 13: acquiring an infrared image shot by the thermal imager to obtain a gray value Y of the infrared image;
s 14: adjusting the ambient temperature of the environmental test chamber to adjust the temperatureLens temperature T of thermal imager opitc (ii) a Adjusting the black body temperature T of the black body b (ii) a And repeating the steps s12-s13 to obtain a plurality of calibration arrays.
A third aspect of the present application provides a server, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor executes the computer program to implement the steps of the infrared imaging thermometry method as described above.
A fourth aspect of the present application provides a computer-readable storage medium having a computer program which, when executed by a processor, performs the steps of the infrared imaging thermometry method as described above.
The beneficial effect of this application lies in: the application provides an infrared imaging temperature measurement method, which comprises the steps of obtaining known multiple groups of calibration arrays in a self-adaptive stage, substituting the known multiple groups of calibration arrays into a formula (I), and solving to obtain a self-adaptive response model; shooting an infrared image P of the black body in a detection stage k Acquiring and shooting the infrared image P k Temperature T of lens m According to said infrared image P k Obtaining the infrared image P k Gray value Y of each pixel point m (ii) a Further adjust the lens temperature T m Gray value Y m Substituting the independent variable into the response model, and outputting the gray value of each pixel point. By the method, the gray value of each pixel point finally output is not limited by the working state of the thermal imager, the output result is obtained through the self-adaptive response model, and the temperature measurement precision is further improved.
Drawings
Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
FIG. 1 is a flow chart of an infrared imaging temperature measurement method provided by the present application;
FIG. 2 is a graph of a record of pixels before and after filtering in scene 1;
FIG. 3 is a graph of a record of pixels before and after filtering for scene 2;
FIG. 4 is a diagram illustrating a comparison among an original map, a filtered map and a residual map in a target motion scene 1;
fig. 5 is a schematic diagram of comparison among an original map, a filtered map and a residual map in the target motion scene 2;
fig. 6 is a schematic diagram showing comparison among an original image, a filter image and a residual image in a square target NETD test scene;
FIG. 7 is a diagram illustrating a comparison between an original image, a filtered image and a residual image in an indoor low-contrast motion scene;
FIG. 8 is a schematic diagram showing a comparison of a calibration curve and an inversion curve at an ambient temperature of 14.5 ℃;
FIG. 9 is a schematic diagram of a comparison of a calibration curve and an inversion curve at an ambient temperature of 34.5 ℃;
FIG. 10 is a schematic diagram of a comparison of a calibration curve and an inversion curve at an ambient temperature of 54.5 ℃;
fig. 11 is a server provided in the present application;
FIG. 12 is a schematic diagram of an infrared imaging thermometry apparatus provided herein;
fig. 13 is a schematic diagram of the filtering module 5 disposed between the obtaining module 1 and the first processing module 2 in fig. 12.
Reference numbers in the figures:
1. an acquisition module; 2. a first processing module; 3. a calculation module; 4. a second processing module; 5. and a filtering module.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not to be construed as limiting the invention. It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
Example 1
Please refer to fig. 1, which is a flowchart of an infrared imaging temperature measurement method provided in the present application, including the following steps:
s 1: acquiring an infrared image P k And the lens temperature T for photographing the same m ；
s 2: according to the infrared image P k Obtaining the infrared image P k Gray value Y of each pixel point m ；
s 3: will T opitc ＝T m ，Y＝Y m Substituting the infrared image P into the response model, and solving to obtain the infrared image P k Black body temperature T corresponding to each pixel point b ；
The response model is obtained by respectively substituting a plurality of calibration arrays into a formula (I), solving unknown numbers and substituting the solved numbers into the formula (I); the calibration array comprises a blackbody temperature T b Corresponding to the black body temperature T b Gray value Y of the infrared image and lens temperature T when the infrared image is taken opitc (ii) a The formula (one) is as follows:
specifically, the method for solving the unknowns may adopt a least square method.
Specifically, the data of the calibration array is calibration data, and the calibration array corresponds to the blackbody temperature T b Gray values of all pixel points of the lower infrared image are equal;
specifically, in step s1, infrared image P is acquired k The method is that an infrared thermal imager shoots an infrared image P of the black body k (ii) a Furthermore, the thermal infrared imager and the black body are both arranged in an environment test chamber, and the environment test chamber is used for providing a test environment and a test temperature for the environment test chamber, so that the temperature T of the lens can be adjusted m ；
Specifically, the lens temperature T in step s1 m Can be transmitted by temperature measurementThe temperature sensor is arranged on the thermal infrared imager.
The infrared imaging temperature measurement method provided by the embodiment aims to solve the problem that in the prior art, as the working state of a thermal infrared imager is greatly influenced by the ambient temperature, the response characteristic at high and low temperatures is greatly different from the response characteristic at normal temperature, namely, the temperature measurement process cannot adapt to the working environment with a wide temperature range; meanwhile, in the data calibration process, the actual response of the system cannot be accurately fitted, and the temperature measurement precision is low;
based on this background, the present embodiment provides an infrared imaging temperature measurement method, which mainly includes:
actually shooting infrared image P of black body k Acquiring and shooting the infrared image P k Temperature T of lens m According to said infrared image P k Obtaining the infrared image P k Gray value Y of each pixel point m (ii) a Further adjust the lens temperature T m Gray value Y m Substituting the independent variable into the response model, and outputting the gray value of each pixel point.
The self-adaptive response model is obtained by acquiring a plurality of groups of calibration arrays, substituting the calibration arrays into a formula (I), and substituting the solved inverse into the formula (I).
According to the steps, the gray value of each pixel point which is finally output is not limited by the working state of the thermal imager, the output result is obtained through the self-adaptive response model, and the temperature measurement precision is further improved.
It should be further noted that the formula (I) is to calculate the lens temperature T m Gray value Y m Black body temperature T b An adaptive bridge is established between the two, and the evolution process is as follows:
a 1: a basic response model is established by the formula (1-1):
Y＝tGL(T b )+tL out +D dark (1-1)
wherein Y is a gray value of the response output; t is the integration time; l (T) b ) Radiant energy that is a black body; t is b Is the black body temperature; d dark Response shift due to dark current; l is out External stray light interference;
a 2: when no external light is incident directly without passing through the light system, the L is converted into the light out Regarded as the lens temperature T opitc As a function of (a) to obtain:
Y＝tGL(T b )+tL(T opitc )+D dark (1-2)；
a 3: mixing L (T) b ) Regarding the temperature range as a nonlinear model, we obtain:
Y＝tG(aT b 2 +bT b +c)+tL(T opitc )+D dark (1-3)；
a 4: integrating the coefficients, integrating the coefficient G into the coefficients a, b, c, yields:
Y＝t(aT b 2 +bT b +c)+tL(T opitc )+D dark (1-4)；
a 5: according to the model of the cover of the stray heat radiation pot in the engineering, L (T) opitc ) Regarded as the lens temperature T opitc In the form of a quadratic function, we obtain:
a 6: combining the coefficients in the formulas (1-5) to obtain:
wherein, K int Is an internal parameter that is integral time dependent;
a 7: let tK in the formula (1-6) int +D dark And D is combined, and other coefficients are further simplified, so that the formula (I) is obtained:
in some embodiments, the infrared imaging thermometry method further comprises:according to the black body temperature T of each pixel point of the infrared image b And gray value Y m Generating the abscissa as the gray value Y m The ordinate is the black body temperature T b The inverse curve of (2).
In some embodiments, the calibration array is obtained by the following sub-steps:
s 11: placing a black body and a thermal imager in an environmental test chamber, wherein the environmental test chamber is used for providing a test environment for the black body and the thermal imager; the thermal imager is used for shooting the infrared image of the black body
s 12: acquiring lens temperature T of thermal imager through sensor opitc (ii) a The sensor is installed on the thermal imager;
s 13: acquiring an infrared image shot by the thermal imager to obtain a gray value Y of the infrared image;
s 14: adjusting the environmental temperature of the environmental test chamber to adjust the lens temperature T of the thermal imager opitc (ii) a Adjusting a black body temperature T of the black body b (ii) a And repeating the steps s11-s13 to obtain a plurality of calibration arrays.
Further, in the step s14, the environmental temperature of the environmental test chamber is adjusted, the environmental temperature reaches a set temperature value, the set time is continued, and after the thermal imager is stabilized, the steps s11-s13 are performed, so that the accuracy of measurement is further improved.
Example 2
Based on embodiment 1, in some embodiments, the infrared image P is obtained k Obtaining the infrared image P k Gray value Y of each pixel point m Before, still include: for the infrared image P k And (6) filtering. Preferably, the filtering mode adopts adaptive time domain filtering.
In some embodiments, the infrared image P is processed k The filtering method is realized by the following steps:
acquiring the infrared image P k Of successive frame pictures P k-1 、P k-2 、……、P 1 K is the current frame, and k is more than or equal to 4;
according to the continuous frame image P k-1 、P k-2 、……、P 1 Calculating the infrared image P k The steady state recording variable S of each pixel point (m, n) k (m, n); wherein m is the abscissa of the pixel point, n is the ordinate of the pixel point, and the stable state recording variable S k (m, n) is used for representing the stability degree of the pixel value change of the pixel point (m, n);
calculating the infrared image P according to the formula (II) k Of each pixel point (m, n) of (a) F (m,n,k)：
Wherein I (m, n, k) represents the infrared image P k Ts is a first set threshold.
In the above steps, the infrared image P is filtered in a self-adaptive time domain filtering manner k And self-adaptive filtering is performed, so that time domain noise is reduced, and the accuracy of the measurement result is further improved.
It should be further noted that the infrared image P k Where k denotes the current frame and k ≧ 4, P k-1 Representing an infrared image P k The previous frame image of (2); for convenience of explaining the operation principle of the present embodiment, taking k as 5 as an example, the infrared image P is acquired 5 Of successive frame pictures P 4 、P 3 、P 2 、P 1 (ii) a Calculating the position of each pixel point (m, n) in P 5 、P 4 、P 3 、P 2 、P 1 The degree of stability of the pixel value change; when the stability of a certain pixel point (m, n) is greater than or equal to the first set threshold, then P is added 5 、P 4 、P 3 、P 2 Averaging and outputting the pixel values corresponding to the pixel points (m, n); when the stability degree of a certain pixel point (m, n) is less than the first set threshold, directly adding P 5 And (4) outputting the pixel value corresponding to the pixel point (m, n).
In some embodiments, the steady state recording variable S k (m, n) is calculated by the following substeps:
judging the logic result T1 between the pixel value of the inter-frame difference and the second set threshold Thr according to the formula (III) k 、T2 k 、T3 k ：
Calculating the steady state recording variable S according to formula (IV) k (m,n)：
Wherein S is 3 (m,n)＝0。
It should be further noted that the logic result T1 k 、T2 k 、T3 k The output result of (1) is 0 (logic false) or 1 (logic true);
it is further noted that the steady state recording variable S k The algorithm concept of (m, n) is as follows:
sequentially calculating the difference value of the pixel points of the frame image and the first three frames of images of the frame image from the 4 th frame of image, and logically comparing the difference value with the second set threshold Thr to obtain T1 4 、T2 4 、T3 4 Three logical results. Judgment T1 4 +T2 4 +T3 4 When the value of (2) is greater than or equal to 2, recording the stable state of the frame as a variable S 4 (m, n) is set to 0; judgment T1 4 +T2 4 +T3 4 When the value of (A) is less than 2, recording a steady state recording variable S of the frame 4 (m, n) is assigned as the steady state recording variable S for the previous frame image 3 (m, n) + 1; here, since k.gtoreq.4, S is 3 (m, n) as initial values and S 3 (m,n)＝0；
Repeating the above steps, calculating the stable state record variable S of the 5 th frame image 5 (m, n) when T1 5 +T2 5 +T3 5 When the value of (3) is greater than or equal to 2, recording a stable state recording variable S of the frame 5 (m, n) is set to 0; when T1 5 +T2 5 +T3 5 Is less than 2, the steady state of the frame is recorded as variable S 5 (m, n) is assigned as the steady state recording variable S for the 4 th frame image 4 (m,n)+1；
Until the current frame (infrared image P) is calculated k ) Steady state recording variable S k (m, n) is over; and then calculating a filter value to be output according to a formula (II).
In some embodiments, the first set threshold Ts in the formula (two) is 10 to 20; for example Ts 15;
in some embodiments, the value of the second set threshold Thr in the formula (three) is 8 to 20; for example Thr ═ 12.
Example 3
As shown in fig. 12, the present embodiment provides an infrared imaging temperature measuring device, which includes:
an acquisition module 1, wherein the acquisition module 1 is used for acquiring an infrared image P k And the lens temperature T for photographing the same m ；
A first processing module 2, wherein the first processing module 2 is used for processing the infrared image P k Obtaining the infrared image P k The gray value Y of each pixel point m ；
A calculation module 3, said calculation module 3 being adapted to assign T opitc ＝T m ，Y＝Y m Substituting the infrared image P into the response model, and solving to obtain the infrared image P k Black body temperature T corresponding to each pixel point b ；
The response model is obtained by respectively substituting a plurality of calibration arrays into a formula (I), solving unknown numbers and substituting the solved numbers into the formula (I); the calibration array comprises a blackbody temperature T b Corresponding to the black body temperature T b Gray value Y of the infrared image and lens temperature T when the infrared image is taken opitc (ii) a The formula (one) is as follows:
according to the infrared imaging temperature measuring device provided by the embodiment, the gray value of each pixel point finally output by the infrared imaging temperature measuring device is not limited by the working state of the thermal imager, and the output result is obtained through the self-adaptive response model, so that the temperature measuring precision is further improved.
In some embodiments, the infrared imaging thermometry device further comprises: a second processing module 4, said second processing module 4 being configured to process said infrared image P k Black body temperature T of each pixel point b And gray value Y m Generating the abscissa as the gray value Y m The ordinate is the black body temperature T b The inverse curve of (2).
Example 4
As shown in fig. 13, on the basis of embodiment 3, in this embodiment, a filtering module 5 is disposed between the obtaining module 1 and the first processing module 2, and the filtering module 5 is configured to filter the infrared image P k And (6) filtering.
In some embodiments, the obtaining module 1 is specifically configured to: acquiring the infrared image P k Of successive frame pictures P k-1 、P k-2 、……、P 1 K is the current frame, and k is more than or equal to 4; acquiring a lens temperature T for photographing the same m ；
The filtering module 5 is specifically configured to:
according to the continuous frame image P k-1 、P k-2 、……、P 1 Calculating the infrared image P k The steady state recording variable S of each pixel point (m, n) k (m, n); wherein m is the abscissa of the pixel point, n is the ordinate of the pixel point, and the stable state recording variable S k (m, n) is used for representing the stability of the pixel value change of the pixel point (m, n);
calculating the infrared image P according to the formula (II) k Of each pixel point (m, n) of (a) F (m,n,k)：
Wherein I (m, n, k) represents the infrared image P k Ts is a first set threshold.
In some embodiments, the steady state recording variable S k (m, n) is calculated by the filtering module 5 by the following substeps:
judging the logic result T1 between the pixel value of the frame difference and the second set threshold Thr according to the formula (III) k 、T2 k 、T3 k ：
Calculating the steady state recording variable S according to formula (IV) k (m,n)：
Wherein S is 3 (m,n)＝0。
In some embodiments, the calibration array is obtained by the following sub-steps:
s 11: placing a black body and a thermal imager in an environmental test chamber, wherein the environmental test chamber is used for providing a test environment for the black body and the thermal imager; the thermal imager is used for shooting an infrared image of the black body;
s 12: acquiring lens temperature T of thermal imager through sensor opitc (ii) a The sensor is installed on the thermal imager;
s 13: acquiring an infrared image shot by the thermal imager to obtain a gray value Y of the infrared image;
s 14: adjusting the environmental temperature of the environmental test chamber to adjust the lens temperature T of the thermal imager opitc (ii) a Adjusting a black body temperature T of the black body b (ii) a And repeating the steps s12-s13 to obtain a plurality of calibration arrays.
Example 5
On the basis of embodiment 2, in this embodiment, in order to further explain the technical effects of the technical solution of the present application, the following example test verification is performed:
1. the method for testing the filtering effect is used for testing the filtering effect in a self-adaptive time domain filtering mode, three different application scenes (namely shooting scenes) are selected, meanwhile, a first set threshold Ts is set to be 15, and a second set threshold Thr is set to be 12; the test results are shown in Table-1:
| serial number | Filtering front noise | |
| Scene | ||
| 1 | 3.46 | 2.04 |
| |
1.71 | 0.92 |
| |
1.84 | 0.88 |
TABLE-1
As can be seen from Table-1, by adopting the adaptive time domain filtering method, the noise reduction effect can reach more than 40%, and the filtering effect is good.
Meanwhile, fig. 2 and fig. 3 respectively list the recording curves of the pixels before filtering and the pixels after filtering of the scene 1 and the scene 2, and it can be known from the graphs that the fluctuation of the pixel values after filtering is weak, and the mode of adaptive temporal filtering in the present application has a better filtering effect.
2. To further explain the filtering effect, the present embodiment respectively performs the shooting and filtering of the infrared image in the target motion scene 1, the target motion scene 2, the square target NETD test scene, and the indoor low-contrast motion scene. The filtering effect is shown in fig. 4-7 in sequence;
taking fig. 4 as an example, the original map, the filtered map and the residual map in the target motion scene 1 are sequentially shown from left to right; it can be clearly observed from the residual map that the static background is filtered, the moving area is updated in real time, and the residual is weak.
3. In order to further illustrate the accuracy of the infrared imaging temperature measurement method in the application, the following tests are carried out:
obtaining a calibration curve from the calibration array under the same environment temperature (namely the same lens temperature), and obtaining an infrared image P k Gray value Y of each pixel point m And the final output black body temperature T b And obtaining an inversion curve. Wherein, the abscissa of the calibration curve and the inversion curve is a gray value, and the ordinate is black body temperature; and comparing the calibration curve with the black body temperature curve, and testing the accuracy of the output result.
As shown in FIGS. 8-10, this example illustrates the comparison of calibration curves and inversion curves at ambient temperatures of 14.5 deg.C, 34.5 deg.C, and 54.5 deg.C, respectively; as can be seen from the figure, after the environmental temperature changes in a large range, the temperature values under different environments are inverted by using a group of parameters, the maximum error of the inversion accuracy range does not exceed +/-2 ℃, and a good effect is achieved.
Example 6
Referring to fig. 11, a schematic block diagram of a computer system 800 of a server or a server provided in this embodiment includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the infrared imaging temperature measurement method as described above when executing the computer program.
As shown in fig. 11, the computer system 800 includes a Central Processing Unit (CPU)801 that can perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)802 or a program loaded from a storage section into a Random Access Memory (RAM) 803. In the RAM803, various programs and data necessary for system operation are also stored. The CPU801, ROM802, and RAM803 are connected to each other via a bus 804. An input/output (I/O) interface 805 is also connected to bus 804.
The following components are connected to the I/O interface 805: an input portion 806 including a keyboard, a mouse, and the like; an output section including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 808 including a hard disk and the like; and a communication section 809 including a network interface card such as a LAN card, a modem, or the like. The communication section 809 performs communication processing via a network such as the internet. Drives are also connected to the I/O interface 805 as needed. A removable medium 811 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 810 as necessary, so that the computer program read out therefrom is mounted on the storage section 808 as necessary.
In particular, according to an embodiment of the invention, the process described above with reference to the flowchart of fig. 1 may be implemented as a computer software program. For example, embodiment 1 of the invention comprises a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication section, and/or installed from a removable medium. The above-described functions defined in the system of the present application are executed when the computer program is executed by the Central Processing Unit (CPU) 501.
Example 5
The present embodiment provides a computer-readable storage medium having a computer program, which when executed by a processor implements the steps of the infrared imaging thermometry method as described above.
It should be noted that the computer readable medium shown in the present invention can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of the present invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present invention may be implemented by software, or may be implemented by hardware, and the described units may also be disposed in a processor. Wherein the names of the elements do not in some way constitute a limitation on the elements themselves. The described units or modules may also be provided in a processor, and may be described as: a processor comprises an acquisition module and a data processing module.
The names of these units or modules do not in some cases constitute a limitation on the units or modules themselves, for example, the acquisition module may also be described as "for acquiring the infrared image P k The acquisition module of (1).
As another aspect, the present embodiment also provides a computer-readable medium, which may be included in the electronic device described in the above embodiment; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs, which when executed by one of the electronic devices, cause the electronic device to implement the steps of the infrared imaging thermometry method in the above embodiment.
For example, the electronic device may implement the following as shown in fig. 1:
s 1: obtaining an Infrared image P k And the lens temperature T for photographing the same m ；
s 2: according to the infrared image P k Obtaining the infrared image P k Ash of upper pixel pointValue Y m ；
s 3: will T opitc ＝T m ，Y＝Y m Substituting the infrared image P into the response model, and solving to obtain the infrared image P k Black body temperature T corresponding to each pixel point b ；
The response model is obtained by respectively substituting a plurality of calibration arrays into a formula (I), solving unknown numbers and substituting the solved numbers into the formula (I); the calibration array comprises a blackbody temperature T b Corresponding to the black body temperature T b Gray value Y of the infrared image and lens temperature T when the infrared image is taken opitc (ii) a The formula (one) is as follows:
it should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functions of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
Moreover, although the steps of the methods of the present disclosure are depicted in the drawings in a particular order, this does not require or imply that the steps must be performed in this particular order, or that all of the depicted steps must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken into multiple step executions, etc.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware.
The above description is only a preferred embodiment of the application and is illustrative of the principles of the technology employed. It will be appreciated by a person skilled in the art that the scope of the invention as referred to in the present application is not limited to the embodiments with a specific combination of the above-mentioned features, but also covers other embodiments with any combination of the above-mentioned features or their equivalents without departing from the inventive concept. For example, the above features may be replaced with (but not limited to) features having similar functions disclosed in the present application.
Claims (14)
1. An infrared imaging temperature measurement method is characterized by comprising the following steps:
acquiring an infrared image P k And the lens temperature T for photographing the same m ；
According to the infrared image P k Obtaining the infrared image P k Gray value Y of each pixel point m ；
Will T opitc ＝T m ，Y＝Y m Substituting the infrared image P into the response model, and solving to obtain the infrared image P k Black body temperature T corresponding to each pixel point b ；
The response model is obtained by respectively substituting a plurality of calibration arrays into a formula (I), solving unknown numbers and substituting the solved numbers into the formula (I); the calibration array comprises a blackbody temperature T b Corresponding to the black body temperature T b Gray value Y of the infrared image and lens temperature T when the infrared image is taken opitc (ii) a The formula (one) is as follows:
2. the infrared imaging temperature measurement method of claim 1, further comprising: according to the infrared image P k Black body temperature T of each pixel point b And gray value Y m Generating the abscissaIs a gray value Y m The ordinate is the black body temperature T b The inverse curve of (2).
3. The infrared imaging thermometry method of claim 1, wherein the infrared image P is based on k Obtaining the infrared image P k Gray value Y of each pixel point m Before, still include: for the infrared image P k And (6) filtering.
4. The infrared imaging thermometry method of claim 3, wherein the infrared image P is measured k The filtering method is realized by the following steps:
acquiring the infrared image P k Of successive frame pictures P k-1 、P k-2 、……、P 1 K is the current frame, and k is more than or equal to 4;
according to the continuous frame image P k-1 、P k-2 、……、P 1 Calculating the infrared image P k The steady state recording variable S of each pixel point (m, n) k (m, n); wherein m is the abscissa of the pixel point, n is the ordinate of the pixel point, and the stable state recording variable S k (m, n) is used for representing the stability of the pixel value change of the pixel point (m, n);
calculating the infrared image P according to the formula (II) k Of each pixel point (m, n) of (a) F (m,n,k)：
Wherein I (m, n, k) represents the infrared image P k Ts is a first set threshold.
5. The infrared imaging thermometry method of claim 4, wherein the steady state recording variable S k (m, n) is calculated by the following substeps:
according to the formula (III)Logic result T1 between pixel value of inter-frame difference and second set threshold Thr k 、T2 k 、T3 k ：
Calculating the steady state recording variable S according to formula (IV) k (m,n)：
Wherein S is 3 (m,n)＝0。
6. The infrared imaging temperature measurement method according to any one of claims 1 to 5, wherein the calibration array is obtained by the following substeps:
s 11: placing a black body and a thermal imager in an environmental test chamber, wherein the environmental test chamber is used for providing a test environment for the black body and the thermal imager; the thermal imager is used for shooting the infrared image of the black body
s 12: acquiring lens temperature T of thermal imager through sensor opitc (ii) a The sensor is installed on the thermal imager;
s 13: acquiring an infrared image shot by the thermal imager to obtain a gray value Y of the infrared image;
s 14: adjusting the environmental temperature of the environmental test chamber to adjust the lens temperature T of the thermal imager opitc (ii) a Adjusting a black body temperature T of the black body b (ii) a And repeating the steps s12-s13 to obtain a plurality of calibration arrays.
7. An infrared imaging temperature measuring device, comprising:
an acquisition module (1), the acquisition module (1) being used for acquiring an infrared image P k And the lens temperature T for photographing the same m ；
A first processing module (2), aThe first processing module (2) is used for processing the infrared image P according to the infrared image k Obtaining the infrared image P k Gray value Y of each pixel point m ；
A calculation module (3), the calculation module (3) being configured to assign T opitc ＝T m ，Y＝Y m Substituting the infrared image P into the response model, and solving to obtain the infrared image P k Black body temperature T corresponding to each pixel point b ；
The response model is obtained by respectively substituting a plurality of calibration arrays into a formula (I), solving unknown numbers and substituting the solved unknown numbers into the formula (I); the calibration array comprises a blackbody temperature T b Corresponding to the black body temperature T b Gray value Y of the infrared image and lens temperature T when the infrared image is taken opitc (ii) a The formula (one) is as follows:
8. the infrared imaging temperature measuring device of claim 7, further comprising: a second processing module (4), said second processing module (4) being configured to process said infrared image P k Black body temperature T of each pixel point b And the gray value Y m Generating the abscissa as the gray value Y m The ordinate is the black body temperature T b The inverse curve of (c).
9. The infrared imaging temperature measuring device of claim 7, wherein a filtering module (5) is disposed between the obtaining module (1) and the first processing module (2), and the filtering module (5) is used for filtering the infrared image P k And (6) filtering.
10. The infrared imaging temperature measuring device of claim 9,
the acquisition module (1) is specifically configured to: acquiring the infrared image P k Of successive frame pictures P k-1 、P k-2 、……、P 1 K is the current frame, and k is more than or equal to 4; acquiring a lens temperature T for photographing the same m ；
The filtering module (5) is specifically configured to:
according to the continuous frame image P k-1 、P k-2 、……、P 1 Calculating the infrared image P k The steady state recording variable S of each pixel point (m, n) k (m, n); wherein m is the abscissa of the pixel point, n is the ordinate of the pixel point, and the stable state recording variable S k (m, n) is used for representing the stability degree of the pixel value change of the pixel point (m, n);
calculating the infrared image P according to the formula (II) k Of each pixel point (m, n) of (a) F (m,n,k)：
Wherein I (m, n, k) represents the infrared image P k Ts is a first set threshold.
11. The infrared imaging thermometry device of claim 10 wherein the steady state recording variable S k (m, n) is calculated by the filtering module (5) by the following substeps:
judging the logic result T1 between the pixel value of the inter-frame difference and the second set threshold Thr according to the formula (III) k 、T2 k 、T3 k ：
Calculating the steady state recording variable S according to the formula (IV) k (m,n)：
Wherein S is 3 (m,n)＝0。
12. The infrared imaging temperature measurement device of claim 10, wherein the calibration array is obtained by the following substeps:
s 11: placing a black body and a thermal imager in an environmental test chamber, wherein the environmental test chamber is used for providing a test environment for the black body and the thermal imager; the thermal imager is used for shooting an infrared image of the black body;
s 12: acquiring lens temperature T of thermal imager through sensor opitc (ii) a The sensor is arranged on the thermal imager;
s 13: acquiring an infrared image shot by the thermal imager to obtain a gray value Y of the infrared image;
s 14: adjusting the environmental temperature of the environmental test chamber to adjust the lens temperature T of the thermal imager opitc (ii) a Adjusting a black body temperature T of the black body b (ii) a And repeating the steps s12-s13 to obtain a plurality of calibration arrays.
13. A server comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the infrared imaging thermometry method according to any one of claims 1 to 6.
14. A computer-readable storage medium, having a computer program, wherein the computer program is adapted to carry out the steps of the infrared imaging thermometry method of any one of claims 1-6 when executed by a processor.
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