CN115018812A - Material type determination method, device, equipment and readable storage medium - Google Patents
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Abstract
The invention relates to the technical field of material detection, in particular to a material type determining method, a device, equipment and a readable storage medium, wherein the method comprises the steps of sending material image information acquired by an infrared detector to an image preprocessing module for image reconstruction, and carrying out non-uniformity correction and image enhancement on the basis of a reconstructed material image to obtain a preprocessed material image; then, calculating a temperature value to obtain a temperature value of each pixel point in the preprocessed material image; calculating the temperature change rate of each pixel point; the method comprises the steps of analyzing and identifying the temperature value of each pixel point in the preprocessed material image and the temperature change rate of each pixel point in the preprocessed material image to obtain material type information in the first information.
Description
Technical Field
The invention relates to the technical field of material detection, in particular to a method, a device and equipment for determining a material type and a readable storage medium.
Background
At present, a plurality of common material identification methods exist, wherein the material is identified according to the inherent characteristics of the target under the observation condition of infrared equipment, which is a very useful method, but the common infrared radiation characteristic measuring equipment has the disadvantages of huge volume, high precision, high price, more than ten million yuan, and inconvenience for teaching and cultivating corresponding talents, so that an identification method and an identification device with material identification function are needed for teaching.
Disclosure of Invention
It is an object of the present invention to provide a method, apparatus, device and readable storage medium for determining a material type to improve the above problems. In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
in one aspect, the present application provides a material type determination method, the method comprising:
acquiring first information and second information, wherein the first information is material image information acquired by an infrared detector, and the second information comprises historical material temperature values and gray values of historical preprocessed material images;
sending the first information to an image preprocessing module for image reconstruction, and performing image enhancement based on a reconstructed material image to obtain a preprocessed material image;
calculating based on the preprocessed material image and the second information to obtain a temperature value of each pixel point in the preprocessed material image;
inputting the temperature value of each pixel point in the preprocessed material image into a temperature change rate calculation module for calculation to obtain the temperature change rate of each pixel point in the preprocessed material image;
analyzing and identifying the temperature value of each pixel point in the preprocessed material image and the temperature change rate of each pixel point in the preprocessed material image to obtain the material type information in the first information.
In a second aspect, an embodiment of the present application provides a material type determination apparatus, including:
the device comprises a first acquisition unit, a second acquisition unit and a control unit, wherein the first acquisition unit is used for acquiring first information and second information, the first information is material image information acquired by an infrared detector, and the second information comprises historical material temperature values and gray values of a material image subjected to historical preprocessing;
the first sending unit is used for sending the first information to an image preprocessing module for image reconstruction and carrying out image enhancement on the basis of a reconstructed material image to obtain a preprocessed material image;
the first calculation unit is used for calculating based on the preprocessed material image and the second information to obtain a temperature value of each pixel point in the preprocessed material image;
the second calculation unit is used for inputting the temperature value of each pixel point in the preprocessed material image into the temperature change rate calculation module for calculation to obtain the temperature change rate of each pixel point in the preprocessed material image;
and the first analysis unit is used for analyzing and identifying the temperature value of each pixel point in the preprocessed material image and the temperature change rate of each pixel point in the preprocessed material image to obtain the material type information in the first information.
In a third aspect, embodiments of the present application provide a material type determination device, which includes a memory and a processor. The memory is used for storing a computer program; the processor is adapted to carry out the steps of the above-described material type determination method when executing said computer program.
In a fourth aspect, the present application provides a readable storage medium, on which a computer program is stored, and the computer program, when executed by a processor, implements the steps of the material type determination method described above.
The invention has the beneficial effects that:
the device for determining the type of the material is simple in structure and low in cost, can be used for school teaching and is convenient for students to understand in an enhancing mode, the image is enhanced, errors generated by the device are reduced, the temperature change characteristics of the material at different time are calculated through the temperature change rate calculating module, and then the type of the material is determined conveniently and quickly.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the embodiments of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
Fig. 1 is a schematic flow chart of a material type determination method according to an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of a material type determining apparatus according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a material type determination apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present invention, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
Example 1
As shown in fig. 1, the present embodiment provides a material type determination method, which includes step S1, step S2, step S3, step S4, and step S5.
Step S1, acquiring first information and second information, wherein the first information is material image information acquired by an infrared detector, and the second information comprises historical material temperature values and gray values of a material image subjected to historical preprocessing;
step S2, sending the first information to an image preprocessing module for image reconstruction, and performing image enhancement based on the reconstructed material image to obtain a preprocessed material image;
step S3, calculating based on the preprocessed material image and the second information to obtain a temperature value of each pixel point in the preprocessed material image;
step S4, inputting the temperature value of each pixel point in the preprocessed material image into a temperature change rate calculation module for calculation to obtain the temperature change rate of each pixel point in the preprocessed material image;
step S5, analyzing and identifying the temperature value of each pixel point in the preprocessed material image and the temperature change rate of each pixel point in the preprocessed material image, to obtain the material type information in the first information.
The device for determining the type of the material is simple in structure and low in cost, can be used for school teaching and facilitates students to understand the material in an enhanced mode, reduces errors generated by the device by enhancing the image, and determines the type of the material by calculating the temperature change characteristics of the material at different time through the temperature change rate calculating module, so that the device is convenient and rapid to use.
The invention can be understood as preprocessing the image, calculating the temperature value and the temperature change rate of the material image, and then reversely calculating which material is in the image.
In a specific embodiment of the present disclosure, the step S2 includes steps S21, S22 and S23.
Step S21, performing fourier transform processing on the material image information in the first information, and converting the spatial threshold information of the material image information in the first information into frequency domain information;
step S22, decomposing the frequency domain information according to a preset threshold, wherein the frequency domain information larger than the preset threshold is recorded as high-frequency image information, and the frequency domain information smaller than the preset threshold is recorded as low-frequency image information;
step S23, performing sharpening processing on the high-frequency image information and performing smoothing processing on the low-frequency image information, and performing image reconstruction on the processed high-frequency image information and the processed low-frequency image information based on linear characteristics of fourier transform and inverse transform to obtain a reconstructed material image.
It can be understood that the above steps are to enhance the material image, increase the accuracy of image recognition, and improve the recognition effect, and the invention is to enhance the image details, fade the image background, enhance the target information, and help to improve the efficiency of the following processing steps.
In a specific embodiment of the present disclosure, the step S2 includes steps S24 and S25.
Step S24, carrying out gray level transformation on the reconstructed material image information to obtain a gray level histogram of the reconstructed material image information;
and step S25, performing histogram equalization processing on the gray level histogram based on the material image information, wherein the histogram equalization processing is to call the gray level histogram of the reconstructed material image information, and perform nonlinear stretching on the gray level histogram to redistribute image pixel values to obtain a preprocessed material image.
It can be understood that in the above steps, the material image is subjected to gray level transformation through the gray level histogram, so that the details of the image are optimized, and the recognition error is reduced.
In a specific embodiment of the present disclosure, the step S3 includes a step S31, a step S32, a step S33, and a step S34.
Step S31, calling the second information and the radiation response sensitivity of the infrared detector;
step S32, sending the second information and the radiation response sensitivity of the infrared detector to a neural network model to calculate the gray level offset value of the infrared detector;
step S33, calling each pixel gray value of the preprocessed material image;
step S34, sending the gray value of each pixel point of the preprocessed material image, the gray offset value of the infrared detector and the radiation response sensitivity of the infrared detector to a temperature calculation module for processing to obtain the temperature value of each pixel point in the preprocessed material image.
It will be appreciated that the principle of the above steps is to take a series of different blackbody radiation temperatures as the infrared radiation calibration points within the dynamic range of operation of the system. By directly changing the blackbody radiation temperature, a series of measured values can be obtained from the radiation response signal output of the system to be measured, and the response values are expressed by gray values after analog-to-digital conversion. And by the formula:
H＝kT+B
the temperature value of any pixel point can be calculated, wherein H is a gray value, k is the radiation response sensitivity of the infrared detector, B is a gray offset value of the infrared detector, and T is the temperature value of the pixel point.
In a specific embodiment of the present disclosure, the step S4 includes steps S41 and S42.
Step S41, calling a temperature value of each pixel point in the preprocessed material image, preset third information and preset fourth information, wherein the third information comprises a set of at least two continuous frames of the preprocessed material image and the fourth information is time interval information between frames of images in the third information;
step S42, the temperature value, the third information and the fourth information of each pixel point in the preprocessed material image are sent to a temperature change rate calculation model, the temperature change rate of each pixel point in the preprocessed material image is calculated, and the temperature change rate calculation model is a model for calculating the temperature change rate of each pixel point in the preprocessed material image based on a temperature change rate formula.
It is understood that the above steps are calculated by the temperature change rate calculation formula:
to calculate the temperature change rate of each pixel point, wherein delta T The temperature change rate of the pixel points is represented by P, the total frame number of the images is represented by k, k represents the kth frame of the images, k is more than or equal to 1 and less than or equal to P, delta t is the time interval between every two frames of the images, Tk is the temperature of the pixel points in the kth frame, and Tk +1 is the temperature of the same pixel points in the kth frame and the kth frame.
In a specific embodiment of the present disclosure, the step S5 includes a step S51, a step S52, a step S53, and a step S54.
Step S51, calling pixel points with the same temperature value in the preprocessed material image and pixel points with the same temperature change rate in the preprocessed material image;
step S52, connecting the pixel points with the same temperature value to obtain pixel point images with the same temperature value, marking colors of the pixel point images with the same temperature value according to different temperatures, and obtaining a temperature image of the material in the first information;
step S53, connecting the pixel points with the same temperature change rate to obtain pixel point images with the same temperature change rate, and comparing the pixel point images with the same temperature change rate with the temperature image of the material in the first information to obtain an image with a smaller image range;
step S54 is to take the image with the smaller image range as the material characteristic image in the first information, and compare the material characteristic image in the first information with the material characteristic image in the database to obtain the type information of the material in the first information.
It can be understood that the invention obtains a contour image by connecting pixel points with the same temperature value, then obtains a contour image with a temperature change rate by the same method, and then performs comparison to remove the influence of possible impurities to obtain a larger contour image, thereby increasing the comparison precision.
Example 2
As shown in fig. 2, the present embodiment provides a material type determination apparatus, which includes a first acquisition unit 701, a first transmission unit 702, a first calculation unit 703, a second calculation unit 704, and a first analysis unit 705.
The first obtaining unit 701 is configured to obtain first information and second information, where the first information is material image information acquired by an infrared detector, and the second information includes a historical material temperature value and a gray value of a material image after historical preprocessing;
a first sending unit 702, configured to send the first information to an image preprocessing module for image reconstruction, and perform image enhancement based on a reconstructed material image to obtain a preprocessed material image;
a first calculating unit 703, configured to perform calculation based on the preprocessed material image and the second information to obtain a temperature value of each pixel point in the preprocessed material image;
a second calculating unit 704, configured to input the temperature value of each pixel point in the preprocessed material image into a temperature change rate calculating module to calculate, so as to obtain a temperature change rate of each pixel point in the preprocessed material image;
a first analyzing unit 705, configured to analyze and identify a temperature value of each pixel point in the preprocessed material image and a temperature change rate of each pixel point in the preprocessed material image, so as to obtain material type information in the first information.
In a specific embodiment of the present disclosure, the first sending unit 702 includes a first processing subunit 7021, a second processing subunit 7022, and a third processing subunit 7023.
A first processing subunit 7021, configured to perform fourier transform processing on the material image information in the first information, and convert spatial threshold information of the material image information in the first information into frequency domain information;
a second processing subunit 7022, configured to decompose the frequency domain information according to a preset threshold, where the frequency domain information greater than the preset threshold is recorded as high-frequency image information, and the frequency domain information smaller than the preset threshold is recorded as low-frequency image information;
a third processing subunit 7023, configured to perform sharpening on the high-frequency image information and perform smoothing on the low-frequency image information, and perform image reconstruction on the processed high-frequency image information and the processed low-frequency image information based on linear characteristics of fourier transform and inverse transform, to obtain a reconstructed material image.
In a specific embodiment of the present disclosure, the first sending unit 702 includes a fourth processing subunit 7024 and a fifth processing subunit 7025.
A fourth processing subunit 7024, configured to perform gray scale transformation on the reconstructed material image information to obtain a gray scale histogram of the reconstructed material image information;
a fifth processing subunit 7025, configured to perform histogram equalization processing on the basis of the grayscale histogram of the material image information, where the histogram equalization processing is to call the grayscale histogram of the reconstructed material image information, and perform nonlinear stretching on the grayscale histogram to reallocate image pixel values, so as to obtain a preprocessed material image.
In a specific embodiment of the present disclosure, the first calculating unit 703 includes a first invoking subunit 7031, a first sending subunit 7032, a second invoking subunit 7033, and a sixth processing subunit 7034.
A first calling subunit 7031, configured to call the second information and the radiation response sensitivity of the infrared detector;
the first sending subunit 7032 is configured to send the second information and the radiation response sensitivity of the infrared detector to a neural network model to calculate a grayscale offset value of the infrared detector;
a second calling subunit 7033, configured to call the gray value of each pixel point of the preprocessed material image;
a sixth processing subunit 7034, configured to send the gray scale value of each pixel point of the preprocessed material image, the gray scale offset value of the infrared detector, and the radiation response sensitivity of the infrared detector to a temperature calculation module for processing, so as to obtain a temperature value of each pixel point in the preprocessed material image.
In a specific embodiment of the present disclosure, the second calculating unit 704 includes a third invoking sub-unit 7041 and a seventh processing sub-unit 7042.
A third calling subunit 7041, configured to call a temperature value of each pixel point in the preprocessed material image, preset third information, and preset fourth information, where the third information includes a set of at least two consecutive frames of the preprocessed material image, and the fourth information is time interval information between frames of images in the third information;
a seventh processing subunit 7042, configured to send the temperature value, the third information, and the fourth information of each pixel point in the preprocessed material image to a temperature change rate calculation model, and calculate a temperature change rate of each pixel point in the preprocessed material image, where the temperature change rate calculation model is a model that calculates a temperature change rate of each pixel point in the preprocessed material image based on a temperature change rate formula.
In a specific embodiment of the present disclosure, the first analysis unit 705 includes a fourth invoking subunit 7051, an eighth processing subunit 7052, a ninth processing subunit 7053, and a tenth processing subunit 7054.
A fourth calling subunit 7051, configured to call a pixel point with the same temperature value in the preprocessed material image and a pixel point with the same temperature change rate in the preprocessed material image;
an eighth processing subunit 7052, configured to connect the pixel points with the same temperature value to obtain pixel point images with the same temperature value, and mark colors of the pixel point images with the same temperature value according to different temperatures to obtain a temperature image of the material in the first information;
a ninth processing subunit 7053, configured to connect the pixel points with the same temperature change rate to obtain pixel point images with the same temperature change rate, and compare the pixel point images with the same temperature change rate with the temperature image of the material in the first information to obtain an image with a smaller image range;
a tenth processing subunit 7054 is configured to use the image with the smaller image range as the material characteristic image in the first information, and compare the material characteristic image in the first information with the material characteristic image in the database to obtain the type information of the material in the first information.
It should be noted that, regarding the apparatus in the above embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated herein.
Example 3
Corresponding to the above method embodiments, the embodiments of the present disclosure also provide a material type determining apparatus, and a material type determining apparatus described below and a material type determining method described above may be referred to in correspondence with each other.
Fig. 3 is a block diagram illustrating a material type determination device 800 in accordance with an exemplary embodiment. As shown in fig. 3, the material type determination apparatus 800 may include: a processor 801, a memory 802. The material type determination device 800 may also include one or more of a multimedia component 803, an input/output (I/O) interface 804, and a communication component 805.
The processor 801 is configured to control the overall operation of the material type determination apparatus 800, so as to complete all or part of the steps of the material type determination method. The memory 802 is used to store various types of data to support operation at the material type determination device 800, such data may include, for example, instructions for any application or method operating on the material type determination device 800, as well as application-related data, such as contact data, transceived messages, pictures, audio, video, and so forth. The Memory 802 may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk or optical disk. The multimedia components 803 may include screen and audio components. Wherein the screen may be, for example, a touch screen and the audio component is used for outputting and/or inputting audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may further be stored in the memory 802 or transmitted through the communication component 805. The audio assembly also includes at least one speaker for outputting audio signals. The I/O interface 804 provides an interface between the processor 801 and other interface modules, such as a keyboard, mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 805 is used for wired or wireless communication between the material type determination device 800 and other devices. Wireless communication, such as Wi-Fi, bluetooth, Near field communication (NFC for short), 2G, 3G, or 4G, or a combination of one or more of them, so the corresponding communication component 805 may include: Wi-Fi module, bluetooth module, NFC module.
In an exemplary embodiment, material type determining Device 800 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components for performing one of the material type determining methods described above.
In another exemplary embodiment, there is also provided a computer readable storage medium comprising program instructions which, when executed by a processor, implement the steps of the material type determination method described above. For example, the computer readable storage medium may be the memory 802 described above including program instructions that are executable by the processor 801 of the material type determination device 800 to perform the material type determination method described above.
Example 4
Corresponding to the above method embodiment, the embodiment of the present disclosure further provides a readable storage medium, and a readable storage medium described below and a material type determination method described above may be correspondingly referred to each other.
A readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the material type determination method of the above-mentioned method embodiment.
The readable storage medium may be a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and various other readable storage media capable of storing program codes.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily think of the changes or substitutions within the technical scope of the present invention, and shall cover the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A material type determination method, comprising:
acquiring first information and second information, wherein the first information is material image information acquired by an infrared detector, and the second information comprises a historical material temperature value and a grey value of a material image subjected to historical preprocessing;
sending the first information to an image preprocessing module for image reconstruction, and performing image enhancement based on a reconstructed material image to obtain a preprocessed material image;
calculating based on the preprocessed material image and the second information to obtain a temperature value of each pixel point in the preprocessed material image;
inputting the temperature value of each pixel point in the preprocessed material image into a temperature change rate calculation module for calculation to obtain the temperature change rate of each pixel point in the preprocessed material image;
analyzing and identifying the temperature value of each pixel point in the preprocessed material image and the temperature change rate of each pixel point in the preprocessed material image to obtain the material type information in the first information.
2. The method according to claim 1, wherein sending the first information to an image preprocessing module for image reconstruction comprises:
performing Fourier transform processing on the material image information in the first information, and converting the spatial threshold information of the material image information in the first information into frequency domain information;
decomposing the frequency domain information according to a preset threshold, wherein the frequency domain information larger than the preset threshold is recorded as high-frequency image information, and the frequency domain information smaller than the preset threshold is recorded as low-frequency image information;
and respectively carrying out sharpening processing on the high-frequency image information and smoothing processing on the low-frequency image information, and carrying out image reconstruction on the processed high-frequency image information and the processed low-frequency image information based on linear characteristics of Fourier transform and inverse transform to obtain a reconstructed material image.
3. The material type determination method according to claim 1, wherein the image enhancement based on the reconstructed material image comprises
Carrying out gray level transformation on the reconstructed material image information to obtain a gray level histogram of the reconstructed material image information;
and performing histogram equalization processing on the gray level histogram of the material image information, wherein the histogram equalization processing is to call the gray level histogram of the reconstructed material image information, and perform nonlinear stretching on the gray level histogram to redistribute image pixel values to obtain a preprocessed material image.
4. The method for determining the material type according to claim 1, wherein the calculating based on the preprocessed material image and the second information to obtain the temperature value of each pixel point in the preprocessed material image comprises:
calling the second information and the radiation response sensitivity of the infrared detector;
sending second information and the radiation response sensitivity of the infrared detector to a neural network model to calculate the gray level offset value of the infrared detector;
calling the gray value of each pixel point of the preprocessed material image;
and sending the gray value of each pixel point of the preprocessed material image, the gray offset value of the infrared detector and the radiation response sensitivity of the infrared detector to a temperature calculation module for processing to obtain a temperature value of each pixel point in the preprocessed material image.
5. A material type determining apparatus, comprising:
the device comprises a first acquisition unit, a second acquisition unit and a control unit, wherein the first acquisition unit is used for acquiring first information and second information, the first information is material image information acquired by an infrared detector, and the second information comprises historical material temperature values and gray values of a material image subjected to historical preprocessing;
the first sending unit is used for sending the first information to an image preprocessing module for image reconstruction and carrying out image enhancement on the basis of a reconstructed material image to obtain a preprocessed material image;
the first calculation unit is used for calculating based on the preprocessed material image and the second information to obtain a temperature value of each pixel point in the preprocessed material image;
the second calculation unit is used for inputting the temperature value of each pixel point in the preprocessed material image into the temperature change rate calculation module for calculation to obtain the temperature change rate of each pixel point in the preprocessed material image;
and the first analysis unit is used for analyzing and identifying the temperature value of each pixel point in the preprocessed material image and the temperature change rate of each pixel point in the preprocessed material image to obtain the material type information in the first information.
6. The material type determination apparatus according to claim 5, characterized in that the apparatus comprises:
the first processing subunit is configured to perform fourier transform processing on the material image information in the first information, and convert spatial threshold information of the material image information in the first information into frequency domain information;
the second processing subunit is configured to decompose the frequency domain information according to a preset threshold, where frequency domain information larger than the preset threshold is recorded as high-frequency image information, and frequency domain information smaller than the preset threshold is recorded as low-frequency image information;
and the third processing subunit is used for respectively carrying out sharpening processing on the high-frequency image information and smoothing processing on the low-frequency image information, and carrying out image reconstruction on the processed high-frequency image information and the processed low-frequency image information based on linear characteristics of Fourier transform and inverse transform to obtain a reconstructed material image.
7. The material type determination apparatus according to claim 5, characterized in that the apparatus comprises
The fourth processing subunit is configured to perform gray scale transformation on the reconstructed material image information to obtain a gray scale histogram of the reconstructed material image information;
and the fifth processing subunit is used for performing histogram equalization processing on the basis of the gray histogram of the material image information, wherein the histogram equalization processing is to call the gray histogram of the reconstructed material image information and perform nonlinear stretching on the gray histogram to redistribute image pixel values to obtain a preprocessed material image.
8. The material type determination apparatus according to claim 5, characterized in that the apparatus comprises:
the first calling subunit is used for calling the second information and the radiation response sensitivity of the infrared detector;
the first sending subunit is used for sending second information and the radiation response sensitivity of the infrared detector to a neural network model to calculate the gray level offset value of the infrared detector;
the second calling subunit is used for calling the gray value of each pixel point of the preprocessed material image;
and the sixth processing subunit is used for sending the gray value of each pixel point of the preprocessed material image, the gray offset value of the infrared detector and the radiation response sensitivity of the infrared detector to the temperature calculation module for processing to obtain the temperature value of each pixel point in the preprocessed material image.
9. A material type determining apparatus, comprising:
a memory for storing a computer program;
a processor for implementing the steps of the method of determining a type of material as claimed in any one of claims 1 to 4 when executing the computer program.
10. A readable storage medium, characterized by: the readable storage medium has stored thereon a computer program which, when being executed by a processor, carries out the steps of the material type determination method according to any one of claims 1 to 4.
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