Image Processing Method, Apparatus, Electronic Device, and Storage Medium

Abstract

The present application provides an image processing method, apparatus, electronic device, and storage medium. The image processing method of the present application includes: obtaining imaging data of a target object; determining a solute region and a target object region in the imaging data, and taking the center point of the target object region as the center, sequentially dividing the solute region into a plurality of solute rings radially outward; analyzing the imaging data to obtain pixel information of each solute ring; determining concentration information of each solute ring according to the light incident intensity for generating the imaging data, the size information of the target object, and the pixel information of each solute ring. Therefore, the present application can analyze the concentration information of the solute in the target object through the imaging data of the target object, and the present application divides the solute region into a plurality of solute rings and determines the concentration information of each solute ring, thereby improving the accuracy of the data to truly reflect the change of the solute in the melt blocked by structures such as dendrites.

Description

Technical Field

[0001] The present application relates to the technical field of physical state research. Specifically, it relates to an image processing method, device, electronic device, and storage medium. Background Art

[0002] When liquid metal solidifies, solid crystal nuclei grow faster along certain crystal directions, resulting in the formation of dendritic crystals, simply referred to as dendrites. In recent years, X-ray imaging has been widely used in the in-situ observation and research of the metal solidification process. Using it, the crystal nucleation and growth during the metal solidification process, as well as the dynamic tissue evolution process, can be studied intuitively and accurately.

[0003] X-ray imaging data Figure 1 Generally, it is a grayscale image that records the light intensity information of each pixel point of the detector. For synchrotron radiation X-ray imaging data, some solutions directly use the grayscale of the region of interest to characterize the information of metal solutes. There are also some solutions that use the Beer-Lambert law (the X-ray light intensity after passing through the sample is related to the density of the substance) combined with standard samples to obtain semi-quantitative information of metal solutes.

[0004] However, most of the existing solute reconstruction methods assume structures such as dendrites, which are actually three-dimensional structures, as two-dimensional graphics, without considering the information in the thickness direction. Even if the thickness of the dendrite is obtained by dendrite segmentation combined with solute interpolation, it is carried out under the assumption that the dendrite in the sample thickness direction is an integral body with uniform composition.

[0005] In the actual scenario, dendrites present a three-dimensional dendritic shape, and the liquid solutes along the sample thickness direction outside the dendrites are not uniform. Considering the dendrite in the sample thickness direction as an integral body with uniform composition in the prior art cannot truly reflect the change of solutes in the melt blocked by structures such as dendrites. Summary of the Invention

[0006] The purpose of the embodiments of the present application is to provide an image processing method, device, electronic device, and computer-readable storage medium, which can analyze the concentration information of solutes in a target object through the imaging data of the target object.

[0007] In a first aspect, the present application provides an image processing method, including: obtaining imaging data of a target object; determining the solute region and the target object region of the imaging data, and successively dividing the solute region into a plurality of solute rings along the radial direction outward with the center point of the target object region as the center; analyzing the imaging data to obtain the pixel information of each solute ring; and determining the concentration information of each solute ring according to the light incident intensity for generating the imaging data, the size information of the target object, and the pixel information of each solute ring.

[0008] In one embodiment, the image processing method further includes: generating visualization information according to the concentration information of each solute ring.

[0009] In one embodiment, the generating visualization information according to the concentration information of each solute ring includes: establishing a three-dimensional model of the target object according to the concentration information of each solute ring and the size information of the target object.

[0010] In one embodiment, the target object is spherical, the imaging data includes a two-dimensional schematic diagram of the target object along the direction perpendicular to the light ray generating the imaging data; the target object area is circular, and the solute area is an annular shape centered on the center point of the target object area.

[0011] In one embodiment, determining the solute area and the target object area of the imaging data, and taking the center point of the target object area as the center, and sequentially dividing the solute area into a plurality of solute rings along the radial direction outward, includes: dividing the imaging data into a solute area and a target object area according to the gray value, the first threshold and the second threshold in the imaging data; taking the center point of the target object area as the center, and sequentially dividing the solute area into a plurality of solute rings along the radial direction outward.

[0012] In one embodiment, taking the center point of the target object area as the center, and sequentially dividing the solute area into a plurality of solute rings along the radial direction outward; includes: analyzing the imaging data to obtain the minimum resolution of the imaging data; taking the center point of the target object area as the center, and sequentially dividing the solute area into a plurality of solute rings along the radial direction outward according to the minimum resolution.

[0013] In one embodiment, the image processing method further includes: determining the concentration information of each solute ring by using the following formula:

[0014]

[0015]

[0016] where n is the total number of layers of solute rings; c n is the concentration of the outermost solute ring; c n-1 is the concentration of the second outermost solute ring; L is the width of the solute ring; r is the radius of the target object area; δ is the total diameter of the target object; I 0 is the light incident intensity for generating the imaging data; is the average gray value of the target object area; is the average gray value of the outermost solute ring; is the average gray value of the second outermost solute ring; μ a is the absorption coefficient of the solute element at the photon energy; μ bis the absorption coefficient of the solvent element at the photon energy.

[0017] In a second aspect, the present application provides an image processing device, including: an image acquisition module, a region determination module, an imaging analysis module, and an information processing module. The image acquisition module is used to acquire imaging data of a target object; the region determination module is used to determine a solute region and a target object region of the imaging data, and taking the center point of the target object region as the center, sequentially divide the solute region into a plurality of solute rings radially outward; the imaging analysis module is used to analyze the imaging data to obtain pixel information of each solute ring; the information processing module is used to determine the concentration information of each solute ring according to the light incident intensity for generating the imaging data, the size information of the target object, and the pixel information of each solute ring.

[0018] Wherein, the target object is spherical, and the imaging data includes a two-dimensional schematic diagram of the target object along the direction perpendicular to the light for generating the imaging data; the target object region is circular, and the solute region is an annular shape centered on the center point of the target object region.

[0019] In one embodiment, the image processing device further includes: a generation module, and the generation module is used to generate visualization information according to the concentration information of each solute ring.

[0020] In one embodiment, the generation module is further used to establish a three-dimensional model of the target object according to the concentration information of each solute ring and the size information of the target object.

[0021] In one embodiment, the region determination module is further used to divide the imaging data into a solute region and a target object region according to the gray value, a first threshold, and a second threshold in the imaging data; taking the center point of the target object region as the center, sequentially divide the solute region into a plurality of solute rings radially outward.

[0022] In one embodiment, the region determination module is further used to analyze the imaging data to obtain the minimum resolution of the imaging data; taking the center point of the target object region as the center, sequentially divide the solute region into a plurality of solute rings according to the minimum resolution radially outward.

[0023] In one embodiment, the information processing module is further used to determine the concentration information of each solute ring by using the following formula:

[0024]

[0025]

[0026] Wherein, n is the total number of layers of the solute rings; c n is the concentration of the outermost solute ring; c n-1is the concentration of the second outermost solute ring; L is the width of the solute ring; r is the radius of the target area; δ is the total diameter of the target; I 0 is the light incident intensity for generating the imaging data; is the average gray value of the target area; is the average gray value of the outermost solute ring; is the average gray value of the second outermost solute ring; μ a is the absorption coefficient of the solute element at the photon energy; μ b is the absorption coefficient of the solvent element at the photon energy.

[0027] In a third aspect, the present application provides an electronic device, including: a memory and a processor, the memory is used to store a computer program; the processor is used to execute the method described in any one of the foregoing embodiments to automatically calibrate the sensor to be measured.

[0028] In a fourth aspect, the present application provides a computer-readable storage medium, including: a program, when it runs through an electronic device, enables the electronic device to execute the method described in any one of the foregoing embodiments.

[0029] The image processing method, device, electronic device and computer-readable storage medium provided by the present application first analyze the imaging data of the target, determine the solute area and the target area of the imaging data, and take the center point of the target area as the center, and radially outward divide the solute area into multiple solute rings in sequence, then obtain the pixel information of each solute ring, and finally process the light incident intensity for generating the imaging data, the size information of the target and the pixel information of each solute ring, so as to determine the concentration information of the solute ring.

[0030] Therefore, the present application can analyze the concentration information of the solute in the target through the imaging data of the target, and the present application divides the solute area into multiple solute rings and determines the concentration information of each solute ring, so as to improve the accuracy of the data and truly reflect the change of the solute in the melt blocked by structures such as dendrites. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required to be used in the embodiments of the present application. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can be obtained according to these drawings without creative efforts.

[0032] Figure 1 is a schematic structural diagram of an electronic device shown in an embodiment of the present application.

[0033] Figure 2 Schematic diagram of an application scenario shown in an embodiment of the present application.

[0034] Figure 3 Schematic flowchart of an image processing method according to an embodiment of the present application.

[0035] Figure 4 Schematic diagram of steps of an image processing method according to an embodiment of the present application.

[0036] Figure 5 Schematic diagram of steps of an image processing method according to an embodiment of the present application.

[0037] Figure 6 Schematic flowchart of an image processing method according to an embodiment of the present application.

[0038] Figure 7 Schematic diagram of steps of an image processing method according to an embodiment of the present application.

[0039] Figure 8 Schematic diagram of the structure of an image processing apparatus shown in an embodiment of the present application.

[0040] Icons: 100 - electronic device; 101 - bus; 102 - memory; 103 - processor; 200 - image processing apparatus; 210 - image acquisition module; 220 - region determination module; 230 - imaging analysis module; 240 - information processing module; 300 - imaging device; 310 - encapsulation sheet; 320 - target object; 330 - light source; 340 - imager; B - subject region; D - solute region. Detailed implementation manners

[0041] In the description of the present application, terms such as "first", "second", etc. are only used for distinguishing descriptions, and do not represent an arrangement sequence, nor can they be understood as indicating or implying relative importance.

[0042] In the description of the present application, terms such as "include", "comprise", etc. indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, elements, components, and / or their combinations.

[0043] Next, the technical solutions in the embodiments of the present application will be described with reference to the accompanying drawings in the embodiments of the present application.

[0044] Please refer to Figure 1 , which is a schematic diagram of the structure of the electronic device 100 shown in an embodiment of the present application. The electronic device 100 includes: at least one processor 103 and a memory 102, Figure 1Take a processor 103 as an example. The processor 103 and the memory 102 are connected through a bus 101. The memory 102 stores instructions executable by the processor 103. The instructions are executed by the processor 103 so that the electronic device 100 can execute all or part of the processes of the methods in the following embodiments, and can analyze the concentration information of the solute in the target object 320 through the imaging data of the target object 320.

[0045] In one embodiment, the processor 103 may be a general-purpose processor 103, including but not limited to a central processing unit 103 (CPU), a network processor 103 (NP), etc. It may also be a digital signal processor 103 (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor 103 may be a microprocessor 103, or the processor 103 may also be any conventional processor 103, etc. The processor 103 is the control center of the electronic device 100 and connects various parts of the entire electronic device 100 through various interfaces and lines. The processor 103 may implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present application.

[0046] In one embodiment, the memory 102 may be implemented by any type of volatile or non-volatile storage device or a combination thereof, including but not limited to a random access memory 102 (RAM), a read-only memory 102 (ROM), a static random access memory 102 (SRAM), a programmable read-only memory 102 (PROM), an erasable programmable read-only memory 102 (EPROM), and an electrically erasable programmable read-only memory 102 (EEPROM).

[0047] The electronic device 100 can be a device such as a mobile phone, a laptop computer, a desktop computer, or an operating system composed of multiple computers. The electronic device 100 may also include more or fewer components than those shown in Figure 1 or have a different configuration from that shown in Figure 1 . For example, the electronic device 100 further includes input and output devices for human-computer interaction.

[0048] Please refer to Figure 2 , which is a schematic diagram of an application scenario shown in an embodiment of the present application. The application scenario may be an image processing system, and the image processing system includes an imaging device 300 and an image processing device 200. The imaging device 300 is used for imaging the target object 320; the image processing device 200 is used for processing the imaging data acquired by the imaging device to obtain the concentration information of the solute in the target object 320.

[0049] The imaging device 300 includes a packaging sheet 310 for placing the target object 320, a light source 330 for emitting X-rays, γ-rays, α-rays or β-rays, and an imager 340 for taking images. Among them, the emission direction of the X-rays is perpendicular to the shooting direction of the imager 340, and the image taken by the imager 340 is a two-dimensional schematic diagram of the target object 320 along the direction perpendicular to the light rays generating the imaging data, that is, a two-dimensional top view of the target object 320.

[0050] Among them, the emission direction of the X-rays can be used as the Y direction, and the shooting direction of the imager 340 can be used as the Z direction to establish a rectangular coordinate system. Then the target object 320 is a spherical shape that is relatively uniform along the X direction, Y direction and Z direction. Among them, δ is the thickness of the target object 320 along the Y direction, which can represent the total diameter of the target object 320.

[0051] The image processing system can be applied to the in-situ study of metal solidification of the synchrotron radiation light source 330. Then the light source 330 can be used to emit synchrotron radiation X-rays, and the imager 340 can be a ccd camera, a cmos camera or an X-ray detector. The packaging sheet 310 can be a double-sided lens that can transmit synchrotron radiation X-rays, that is, a polished alumina ceramic substrate. The imaging device 300 may further include components such as a housing, a water-cooling circulation pump, a hot stage, a heating sheet, a K-type thermocouple, a PC terminal, a vacuum chamber, and a vacuum pump.

[0052] In a specific operation process, the composition of the alloy sample sheet is Al-15wt.%Bi, which means that the mass ratio of bismuth in the aluminum alloy is 15%, and the size of the alloy sample sheet is 10×15×0.5mm 3 . First, two double-sided lenses with dimensions of 20×25×0.1mm 3 are used to clamp the alloy sample sheet in the form of a sandwich, and the double-sided lenses and the alloy sample sheet are adhered with a mixture of alumina powder and silica sol.

[0053] After it is completely dried, place the fixed double-sided lens and the alloy sample piece between two heating plates on the hot stage in the imaging device 300, and paste and fix two K-type thermocouples between the heating plates and the sample respectively. Then open the hatch of the outer shell in the imaging device 300, place the hot stage with the alloy sample piece on the micro-stage in the imaging device 300 and fix it with bolts. Connect the two heating plates fixed at the upper and lower ends of the alloy sample piece to the corresponding power controllers in the imaging device 300, and then connect the two K-type thermocouples and the power controllers to a dual-channel PID temperature controller.

[0054] Turn on the vacuum pump to evacuate the inside of the outer shell, then introduce Ar gas into the inside as a protective atmosphere, and then control the micro-stage through the PC terminal (computer) in the imaging device 300 to adjust the position of the alloy sample piece.

[0055] Open the shutter of the synchrotron X-ray in the imaging device 300 to make it in the light-passing state, and adjust the X-ray energy to 20 keV (kilo-electron volts). Open the temperature controller program on the PC terminal to set the temperature control program, so that the temperatures at both ends of the alloy sample piece rise to 720 °C within 30 min (minutes) and keep warm for 30 min. During this period, fine-tune the position of the alloy sample piece through the micro-stage to find a suitable field of view position. If the imaging device 300 includes other detectors in addition to the X-ray detector, correct the fields of view of the various detectors in the imaging device 300 through the program so that the data spaces of the various detectors are correlated with each other.

[0056] Control the data acquisition rate in the X-ray detector through the PC terminal to be 10 fps (frames per second), and 2 min before the end of the heat preservation program, control the X-ray detector to start collecting data. The PC terminal simultaneously controls components such as the water-cooled circulation pump to make the alloy sample piece cool gradually at a rate of 10 °C / min, so that the alloy sample piece solidifies isothermally. After the solidification process ends, turn off the X-ray detector, stop the temperature control program and let the hot stage, that is, the alloy sample piece, cool with the furnace.

[0057] Close the synchrotron X-ray shutter, then release the vacuum, tidy up the alloy sample piece and the imaging device 300, and finally obtain the imaging data. After that, the imaging data can be analyzed by the image processing device 200.

[0058] It should be noted that the alloy sample piece can be a immiscible alloy, the imaging data can include the entire alloy sample piece, and the target 320 refers to the immiscible droplets in the alloy sample piece. Moreover, since the alloy sample piece in the imaging device 300 is in a vacuum environment or under microgravity conditions where there is no convection or very little convection under gravity conditions, that is, a pure diffusion condition, at this time the immiscible droplets are spherical or approximately spherical, eliminating the deformation of the immiscible droplets caused by convection.

[0059] The imaging data consists of images captured by the imager 340 and is an image set formed according to time rules based on different acquisition times of the images. The imaging device 300 controls the isothermal solidification of the entire alloy sample sheet through components such as a water-cooling circulation pump and a heating sheet. If the acquisition process of the imaging data is during the isothermal solidification of the entire alloy sample sheet, the imaging data can be used to reveal the changes in solutes, the interaction between droplets and the solid-liquid interface, the movement of droplets, and the wettability between droplets and the solid phase during the isothermal solidification process of the entire alloy sample sheet.

[0060] Please refer to Figure 3 , which is a schematic flowchart of the image processing method according to an embodiment of the present application. Please refer to Figure 4 and Figure 5 , which is a schematic diagram of the steps of the image processing method according to an embodiment of the present application. This method can be executed by the electronic device 100 shown in Figure 1 , or applied to the application scenario shown in Figure 2 to analyze the concentration information of solutes in the target object 320 through the imaging data of the target object 320. This method includes the following steps:

[0061] Step S110: Obtain the imaging data of the target object 320.

[0062] In this step, the computer can directly obtain the imaging data of the target object 320 from the local area, or obtain the imaging data of the target object 320 from other devices such as the imaging device 300.

[0063] The target object 320 in this step can include bubbles, pores, spherical particles, or spherical droplets. When the target object 320 is a bubble in any liquid substance, the present application can help understand the segregation of solutes near the bubble; when the target object 320 is a pore in any metal material, the present application can reconstruct the true solute boundary layer of the pore, which helps to reveal the influence of pores on the nucleation and segregation of metal particles; when the target object 320 is a spherical solid-phase particle in any metal material, the present application can reconstruct the true solute boundary layer of the spherical solid-phase particle, which helps to reveal the true compositional supercooling distribution of the spherical solid-phase particle nucleation and reveal the nucleation mechanism; when the target object 320 is a spherical droplet in any metal material, the present application can reconstruct the true solute boundary layer of the spherical droplet, which helps to reveal the interaction between the droplet and the solid-liquid interface, the movement of the droplet, and the wettability between the droplet and the solid phase, etc.

[0064] Furthermore, the immiscible alloy is a heterogeneous system, which can be a copper-cobalt alloy (Cu-Co), a copper-iron alloy (Cu-Fe), a copper-chromium alloy (Cu-Cr), or an aluminum-bismuth alloy (Al-Bi). Among them, the target object 320 is a spherical droplet of the second phase in any immiscible alloy, for example, it can be a spherical droplet of the less abundant component, i.e., the minor phase.

[0065] Specifically, when the composition of the immiscible alloy is Al-15wt.%Bi (the mass ratio of bismuth is 15%) or Al-3.4wt.%B (the mass ratio of bismuth is 3.4%), the target 320 is a Bi-rich droplet therein. When the composition of the immiscible alloy is Al-90wt.%Bi (the mass ratio of bismuth is 90%) or Al-50wt.%Bi (the mass ratio of bismuth is 50%), the target 320 is an Al-rich droplet therein. When the composition of the immiscible alloy is Al-50wt.%Bi (the mass ratio of bismuth is 50%), the target 320 is an Al-rich droplet or a Bi-rich droplet therein. When the composition of the immiscible alloy is Cu-20wt.%Co (the mass ratio of cobalt is 20%), the target 320 is a Co-rich droplet therein. When the composition of the immiscible alloy is Cu-10wt.%Fe (the mass ratio of iron is 10%), the target 320 is an Fe-rich droplet therein. When the composition of the immiscible alloy is Cr-45wt.%Cu (the mass ratio of copper is 15%), the target 320 is a Cu-rich droplet therein. When the composition of the immiscible alloy is Cr-45wt.%Cu (the mass ratio of copper is 45%), the target 320 is a Cr-rich droplet therein.

[0066] The imaging data of the target object 320 in this step may be a two-dimensional top view of the target object 320 , or may be an image set composed of multiple two-dimensional top views of the target object 320 and formed according to a time rule according to different image acquisition times.

[0067] The imaging data of the target object 320 in this embodiment is based on Figure 2 The X-ray imaging grayscale image obtained by the imaging device 300 shown in the figure needs to be pre-processed by using an image processing system such as de-noising and manual area selection to prepare for the subsequent analysis of the component concentration of the target object 320.

[0068] The X-ray imaging grayscale image may include only the spherical droplet as the target object 320, or may include the entire alloy sample piece containing the target object 320. When the X-ray imaging grayscale image includes the entire alloy sample piece containing the target object 320, the location of the target object 320 may be extracted by manual frame selection, key point recognition, or grayscale recognition.

[0069] Step S120: determining the solute region D and the target region B of the imaging data, and dividing the solute region D into a plurality of solute rings in sequence along the radial direction outwards with the center point of the target region B as the center.

[0070] like Figure 4As shown, the target object 320 is a spherical droplet, which is equivalent to a solid solution and includes a first substance b as the solvent and a second substance a as the solute. The center of the sphere mainly contains substance b, which is called the target object area B, and the periphery of the sphere mainly contains substance a, which is called the solute area D. For example, when the target object 320 is a Bi-rich droplet of Al-15wt.%Bi, the target object area B is the spherical particle Bi (or droplet) therein, and the solute area D is the solute shell layer outside the spherical particle Bi, which can be used to represent the mixing situation of solute Al in solvent Bi.

[0071] As Figure 5 shown, the imaging data is a top view of a spherical droplet. The target object 320 on the imaging data is shown as a circle. Since the materials of the target object area B and the solute area D are different, the degree of X-ray absorption is different, resulting in a gray-scale change on the imaging data. The target object area B on the imaging data is shown as a circular structure with a larger gray-scale value, and the solute area D on the imaging data is shown as an annular structure with a gradually changing gray-scale value centered on the center point of the target object area B.

[0072] In this embodiment, the imaging data can be divided into the solute area D and the target object area B according to the gray-scale value in the imaging data and the first threshold and the second threshold input manually. The area with a gray-scale value between 0 and the first threshold is divided into the solute area D, and the area with a gray-scale value between the first threshold and the second threshold is divided into the target object area B. Among them, the first threshold is less than the second threshold.

[0073] In a specific embodiment, the divided solute area D and target object area B can be verified to determine whether the difference between the gray-scale values of two adjacent pixel points on the outer edge line of the solute area D is less than the third threshold input manually. If so, the division of the outer edge line of the solute area D is relatively reasonable; if not, a warning message is issued and the second threshold is adjusted manually.

[0074] Among them, the first threshold, the second threshold, and the third threshold can be input manually in advance and are known constant parameters, or can be input in real time by the operator according to the gray-scale value in the current imaging data. In another embodiment, the determination of the solute area D and the target object area B of the imaging data can be determined manually.

[0075] In this embodiment, after determining the solute area D of the imaging data, with the center point of the target object area B as the center, the solute area D is sequentially divided into multiple, i.e., n, solute rings along the radial direction outward, and each solute ring is named solute ring D1, solute ring D2, solute ring D3, solute ring D4,... solute ring Dn-1, solute ring Dn from the inside to the outside in turn.

[0076] In this embodiment, the step of sequentially dividing the solute region D into n solute rings radially outward with the center point of the target region B as the center includes: first, analyzing the imaging data to obtain the minimum resolution of the imaging data; then, with the center point of the target region B as the center, dividing the solute region D into multiple solute rings sequentially according to the minimum resolution radially outward. By dividing in this way, the size of the solute rings can be divided into the smallest unit, making the solute rings tend to be infinitely thin, thereby improving the reference value and accuracy of the solute ring concentration obtained subsequently, and improving the solute reconstruction accuracy subsequently.

[0077] Wherein, if the pixel is rectangular and its size includes Ly and Lx, the width L of the solute ring is L = max(Ly, Lx), which is the maximum value of Ly and Lx, that is, the minimum resolution is the length of the pixel. The width L of the solute ring can be 0.325 μm - 13 μm.

[0078] As Figure 5 shown, the final division result is: the diameter of the target region B is d, the radius is r, the inner circle radius of the solute region D is R1 = r, the outer circle radius of the solute region D is R1 = r + nL, the inner circle radius of any solute ring Di is R1 = r + (i - 1)L, and the outer circle radius is R2 = r + iL. Where i is an integer representing the number of solute ring layers, and 1 ≤ i ≤ n.

[0079] In another embodiment, the step of sequentially dividing the solute region D into n solute rings radially outward with the center point of the target region B as the center includes: first, receiving the value n input by the user; then dividing the solute region D into n equal solute rings according to the value n.

[0080] In another embodiment, the step of sequentially dividing the solute region D into n solute rings radially outward with the center point of the target region B as the center includes: first, receiving the width of the solute ring input by the user; then dividing the solute region D into n solute rings according to the width of the solute ring input by the user.

[0081] Step S130: Analyze the imaging data to obtain the pixel information of each solute ring.

[0082] The pixel information in this step can be the gray average value, gray maximum value, gray minimum value, color information, brightness information, etc. of each solute ring.

[0083] In this embodiment, the pixel information in this step is the gray average value of each solute ring for the calculation in step S140. This step may include: first, obtaining the gray value (I a , I b , I c , ……) of each pixel in each solute ring, and then calculating the gray average value of each solute ring

[0084] As shown Figure 5 in the figure, the pixel points at the intersection of the horizontal (X-axis) radii of each solute ring are named Ai, and Ai are A1, A2, A3... An-1 and An in sequence from the inside to the outside. The average gray value of each solute ring obtained in this step can be used to represent the gray value of the corresponding pixel point Ai, that is, the intensity of the outgoing light. Where i is an integer representing the number of solute ring layers, and 1 ≤ i ≤ n.

[0085] In addition, this step may also include obtaining the pixel information of the target area B. First, obtain the gray value of each pixel in the target area B, and then calculate the average gray value of each solute ring used to represent the outgoing light intensity of the A 0 pixel point at the center of the solute ring.

[0086] Step S140: Determine the concentration information of each solute ring according to the incident light intensity for generating the imaging data, the size information of the target 320, and the pixel information of each solute ring.

[0087] The incident light intensity for generating the imaging data in this step is a known parameter, which can be Figure 2 the X-ray intensity emitted by the light source 330 in the imaging device 300 as shown, which is input by the user in advance, directly obtained from the local database, or obtained from other devices such as the imaging device 300. The size information of the target 320 is a known parameter, which can be input by the user in advance or obtained by analyzing the imaging data of the target 320.

[0088] In this step, according to the incident light intensity for generating the imaging data, the size information of the target 320, and the pixel information of each solute ring, using the Lambert-Beer law, the concentration information of each solute ring is determined. Therefore, in this embodiment, the concentration information of the solute in the target 320 can be analyzed through the imaging data of the target 320. And in this embodiment, the solute area D is divided into multiple solute rings, and the concentration information of each solute ring is determined, so as to improve the accuracy of the data and truly reflect the change of the solute in the melt blocked by structures such as dendrites.

[0089] In the Lambert-Beer law, A = lg(1 / T) = Kbc; where A is the absorbance, T is the transmittance (transparency), which is the ratio of the outgoing light intensity to the incident light intensity, K is the molar absorptivity. It is related to the properties of the absorbing substance and the wavelength λ of the incident light. c is the concentration of the absorbing substance, with the unit of mol / L, and b is the thickness of the absorption layer, with the unit of cm.

[0090] According to the derivation based on the Lambert-Beer law, the formula for the relationship between the emitted light intensity of each solute ring in the target area B or the solute area D and the solute concentration can be obtained.

[0091] As Figure 5 shown, since the X-ray is incident along the positive Y-axis direction, before reaching the A0 pixel point, the X-ray passes through the first half of all solute rings. Then, for the absorbance A of the A0 pixel point in the target area B A0 The calculation formula is:

[0092]

[0093] where c B represents the concentration of the target area B, and c B = 1; n is the total number of solute ring layers; i is an integer representing the solute ring layer number, and 1 ≤ i < n; c n is the concentration of the outermost solute ring; c i is the concentration of the i-th solute ring; c j is the concentration of the j-th pixel point; μ a is the absorption coefficient of the solute element at the photon energy; μ b is the absorption coefficient of the solvent element at the photon energy. L is the width of the solute ring; r is the radius of the target area B; δ is the total diameter of the target 320; I 0 is the incident intensity of the light generating the imaging data; is the average gray value of the target area B.

[0094] It should be noted that μ a is the absorption coefficient of the solute element a at the photon energy; μ b is the absorption coefficient of the solvent element b at the photon energy, both of which are known constant parameters and can be input by the user or retrieved from the local database.

[0095] As Figure 5 shown, since the X-ray is incident along the positive Y-axis direction, before reaching the Ai pixel point, the X-ray passes through the first half of the solute ring located outside the i-th layer. Then, for the absorbance A of the Ai pixel point in the i-th solute ring Ai The calculation formula is:

[0096]

[0097] where n is the total number of solute ring layers; i is an integer representing the solute ring layer number, and 1 ≤ i < n; c n is the concentration of the outermost solute ring; c i is the concentration of the i-th solute ring; c j is the concentration of the j-th pixel point; μa is the absorption coefficient of the solute element at the photon energy; μ b is the absorption coefficient of the solvent element at the photon energy. L is the width of the solute ring; r is the radius of the target area B; δ is the total diameter of the target 320; I 0 is the incident intensity of the light ray for generating the imaging data; is the average gray value of the target area B; is the average gray value of the outermost solute ring; is the average gray value of the i-th solute ring.

[0098] As Figure 5 shown, the pixel point An at the intersection of the lateral (X-axis) radius of the outermost solute ring. Since the X-ray is incident along the positive Y-axis direction, before reaching the pixel point An, the X-ray does not pass through other solute rings. Then, for the absorbance A of the pixel point An in the n-th solute ring An The calculation formula is:

[0099]

[0100] where n is the total number of solute rings; c n is the concentration of the outermost solute ring; μ a is the absorption coefficient of the solute element at the photon energy; μ b is the absorption coefficient of the solvent element at the photon energy; δ is the total diameter of the target 320; I 0 is the incident intensity of the light ray for generating the imaging data.

[0101] According to the above formula for conversion, the calculation formula for the concentration (average concentration) of each solute ring is:

[0102]

[0103]

[0104] where n is the total number of solute rings; c n is the concentration of the outermost solute ring; c n-1 is the concentration of the second outermost solute ring; L is the width of the solute ring; r is the radius of the target area; δ is the total diameter of the target; I 0 is the incident intensity of the light ray for generating the imaging data; is the average gray value of the target area; is the average gray value of the outermost solute ring; is the average gray value of the second outermost solute ring; μ a is the absorption coefficient of the solute element at the photon energy; μ b is the absorption coefficient of the solvent element at the photon energy.

[0105] During an operation process, first, substitute the average gray value of the nth solute ring obtained in step S130 into formula (1) to obtain the solute concentration c of the nth solute ring n .

[0106] Then, substitute the gray values of the (n - 1)th to nth solute rings obtained in step S130 and into formula (2) in sequence to obtain the solute value c of the (n - 1)th solute shell n-1 ;

[0107] Next, based on the gray values of the (n - 2)th, (n - 1)th, and nth solute rings obtained in step S130 and calculate the solute value c of the (n - 1)th solute shell n-2 .

[0108] And so on. Finally, based on the gray values of the 1st to nth solute rings obtained in step S130 calculate the solute value c of the 1st solute shell in three - dimensional space 1 .

[0109] In addition, the concentration c of the target area B B is 1.

[0110] It should be noted that formula (1) and formula (2) can calculate the solute values of the outermost and the second outermost solute shells respectively. When n = 2, formula (1) and formula (2) can calculate the solute values of the first layer and the second layer of solute shells respectively.

[0111] Please refer to Figure 6 , which is a schematic flowchart of an image - processing method according to an embodiment of the present application. Please refer to Figure 7 , which is a schematic diagram of the steps of an image - processing method according to an embodiment of the present application. This method can be executed by the electronic device 100 shown in Figure 1 , or applied to the application scenario shown in Figure 2 to analyze the concentration information of the solute in the target object 320 through the imaging data of the target object 320. This method includes the following steps:

[0112] Step S210: Obtain the imaging data of the target object 320. For details, refer to the description of step S110 in the above - mentioned embodiment.

[0113] Step S220: Determine the solute area D and the target area B of the imaging data, and with the center point of the target area B as the center, radially divide the solute area D into multiple solute rings in sequence. For details, refer to the description of step S120 in the above - mentioned embodiment.

[0114] Step S230: Analyze the imaging data to obtain pixel information of each solute ring. For details, refer to the description of step S130 in the above embodiment.

[0115] Step S240: Determine the concentration information of each solute ring according to the incident light intensity for generating imaging data, the size information of the target 320 and the pixel information of each solute ring. For details, refer to the description of step S140 in the above embodiment.

[0116] Step S250: Generate visualization information according to the concentration information of each solute ring.

[0117] The visualization information in this step is the concentration information c of the n solute rings calculated in step S240. 1 、c i ……c n The processed bar graph, curve graph, color graph, grayscale graph or three-dimensional model is obtained.

[0118] In this embodiment, step S250 is to establish a three-dimensional model of the target object 320 according to the concentration information of each solute ring and the size information of the target object 320. Specifically, it includes: firstly, according to the size information of the target object 320, an initial three-dimensional model of the target object 320 is established, wherein the size information of the target object 320 includes the overall size of the target object 320, the size of the solute region D, the size of the central region, and the size of each solute ring; then, according to the concentration information of each solute ring, the color information corresponding to each solute ring is determined; finally, according to the color information corresponding to each solute ring, the color of each solute ring in the initial three-dimensional model is converted to obtain the final three-dimensional model of the target object 320, such as Figure 7 shown.

[0119] In the above steps, the color information corresponding to each solute ring is determined according to the concentration information of each solute ring, which can be obtained according to the instructions input by the user or by querying the pre-stored charts, models, etc. in the local database to obtain each concentration value c i The corresponding grayscale value, RGB color value, hexadecimal color code, etc. are used to determine the color information corresponding to each solute ring and perform pseudo-colorization. For example, the solute ring with the highest concentration value is red, and it changes to orange, yellow, green or purple as the concentration value decreases to form a color three-dimensional map; for example, the solute ring with the highest concentration value has the highest grayscale value, and the grayscale value decreases as the concentration value decreases.

[0120] It should be noted that, if the concentration value of the target area B is known to be 1, the color of the target area B can be the default color, can be customized by the user, or can be left uncolored.

[0121] Therefore, in this embodiment, through visual processing such as rendering and false coloring of the concentration information, a three-dimensional model of the target object 320 is obtained, so that more realistic boundary layer information around the immiscible solution droplet sphere can be obtained, and the four-dimensional solute field around the spherical particles is visualized, which can vividly represent the changes of the solute of the target object 320 (immiscible solution droplet) in the X-axis direction, Y-axis direction, Z-axis direction, and over time. Compared with the prior art that only directly represents the changes of the solute of the immiscible solution droplet in the X-axis direction, Y-axis direction, and over time through X-ray two-dimensional imaging, it is more intuitive, three-dimensional, and the result is more accurate.

[0122] In addition, in this embodiment, by processing the X-ray two-dimensional imaging and then obtaining the three-dimensional model of the target object 320, compared with directly using three-dimensional imaging technologies such as three-dimensional CT in the prior art, this embodiment does not require rotating the imaging sample, and the required scanning or imaging time is less, which improves the work efficiency; in addition, this embodiment also reduces the steps of aligning the center of the imaging sample, avoiding the reconstruction error caused by misaligning the center of the sample, and improving the result accuracy.

[0123] Please refer to Figure 8 , which is a schematic structural diagram of the image processing device 200 shown in an embodiment of the present application. This device can be applied to Figure 1 the electronic device 100 shown in the figure, including: an image acquisition module 210, a region determination module 220, an imaging analysis module 230, and an information processing module 240. The principle relationships of each module are as follows:

[0124] The image acquisition module 210 is used to acquire the imaging data of the target object 320.

[0125] The region determination module 220 is used to determine the solute region D and the target object region B of the imaging data, and with the center point of the target object region B as the center, the solute region D is sequentially divided into a plurality of solute rings radially outward.

[0126] The imaging analysis module 230 is used to analyze the imaging data to obtain the pixel information of each solute ring.

[0127] The information processing module 240 is used to determine the concentration information of each solute ring according to the light incident intensity for generating the imaging data, the size information of the target object 320, and the pixel information of each solute ring.

[0128] Among them, the target object 320 is spherical, the imaging data includes a two-dimensional schematic diagram of the target object 320 along the direction perpendicular to the light direction for generating the imaging data; the target object region B is circular, and the solute region D is an annular shape centered on the center point of the target object region B.

[0129] In one embodiment, the image processing apparatus 200 further includes: a generation module, configured to generate visualization information for each solute ring according to the concentration information of each solute ring.

[0130] In one embodiment, the generation module is further configured to establish a three-dimensional model of the target object 320 according to the concentration information of each solute ring and the dimension information of the target object 320.

[0131] In one embodiment, the region determination module 220 is further configured to divide the imaging data into a solute region D and a target object region B according to the gray value, a first threshold, and a second threshold in the imaging data; and sequentially divide the solute region D into a plurality of solute rings radially outward with the center point of the target object region B as the center.

[0132] In one embodiment, the region determination module 220 is further configured to analyze the imaging data to obtain the minimum resolution of the imaging data; and sequentially divide the solute region D into a plurality of solute rings according to the minimum resolution radially outward with the center point of the target object region B as the center.

[0133] In one embodiment, the information processing module 240 is further configured to determine the concentration information of each solute ring by using the following formula:

[0134]

[0135]

[0136] where n is the total number of layers of the solute rings; c n is the concentration of the outermost solute ring; c n-1 is the concentration of the second outermost solute ring; L is the width of the solute ring; r is the radius of the target object region; δ is the total diameter of the target object; I 0 is the incident light intensity for generating the imaging data; is the average gray value of the target object region; is the average gray value of the outermost solute ring; is the average gray value of the second outermost solute ring; μ a is the absorption coefficient of the solute element at the photon energy; μ b is the absorption coefficient of the solvent element at the photon energy.

[0137] For a detailed description of the above image processing apparatus 200, please refer to the description of the relevant method steps in the above embodiments.

[0138] An embodiment of the present application also provides a computer-readable storage medium, including: a program, which when running on the electronic device 100 enables the electronic device 100 to execute all or part of the processes of the methods in the above embodiments. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory 102, a hard disk drive (abbreviation: HDD), or a solid-state drive (SSD), etc. The storage medium can also include a combination of the above types of memories 102.

[0139] In several embodiments provided by the present application, the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions, and operations of devices, methods, and computer program products according to multiple embodiments of the present application. In this regard, each block in the flowchart or block diagram can represent a module, a program segment, or a part of code, and a module, a program segment, or a part of code contains one or more executable instructions for implementing the specified logical function.

[0140] In some alternative implementations, the functions marked in the blocks can also occur in a different order from that marked in the accompanying drawings. For example, two consecutive blocks can actually be executed substantially in parallel, and they can sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, as well as the combination of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0141] In addition, in each embodiment of the present application, the functional modules can be integrated together to form an independent part, or each module can exist alone, or two or more modules can be integrated to form an independent part.

[0142] Each embodiment in this specification is described in a progressive manner. The same or similar parts among the embodiments can be referred to each other, and the key points of each embodiment are the differences from other embodiments. The above are only the preferred embodiments of the present application, which are only used to illustrate the technical solutions of the present application and are not used to limit the present application. For those of ordinary skill in the art in this technical field, any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

[0143] It should be noted that, without conflict, the features in the embodiments of the present application may be combined with each other. The above are only the embodiments of the present application and are not used to limit the protection scope of the present application. For those skilled in the art, the present application may have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the protection scope of the present application.

Claims

1. An image processing method, characterized in that, comprising: acquiring imaging data of a target object; determining a solute region and a target region of the imaging data, and taking the center point of the target region as the center, and sequentially dividing the solute region into a plurality of solute rings radially outward; analyzing the imaging data to obtain pixel information of each solute ring; determining concentration information of each solute ring according to the light incident intensity for generating the imaging data, the size information of the target object, and the pixel information of each solute ring by using Lambert-Beer's law; wherein, the determining the solute region and the target region of the imaging data, and taking the center point of the target region as the center, and sequentially dividing the solute region into a plurality of solute rings radially outward includes: dividing the imaging data into a solute region and a target region according to the gray value, a first threshold, and a second threshold in the imaging data; dividing the region with a gray value between 0 and the first threshold into the solute region, and dividing the region with a gray value between the first threshold and the second threshold into the target region; wherein, the first threshold is less than the second threshold; wherein, the following formula is used to determine the concentration information of each solute ring: Among them, n is the total number of layers of the solute rings; c n is the concentration of the outermost solute ring; c n-1 is the concentration of the second outermost solute ring; L is the width of the solute ring; r is the radius of the target area; δ is the total diameter of the target; I 0 is the incident intensity of the light rays generating the imaging data; is the average gray value of the target area; is the average gray value of the outermost solute ring; is the average gray value of the second outermost solute ring; μ a is the absorption coefficient of the solute element at the photon energy; μ b is the absorption coefficient of the solvent element at the photon energy.

2. The image processing method according to claim 1, characterized in that, further comprising: generating visualization information according to the concentration information of each solute ring.

3. The image processing method according to claim 2, characterized in that, the generating visualization information according to the concentration information of each solute ring includes: establishing a three-dimensional model of the target object according to the concentration information of each solute ring and the size information of the target object.

4. The image processing method according to any one of claims 1 to 3, characterized in that, the target object is spherical, and the imaging data includes a two-dimensional schematic diagram of the target object along the direction perpendicular to the light for generating the imaging data; the target region is circular, and the solute region is an annular shape centered on the center point of the target region.

5. The image processing method according to claim 4, characterized in that, the sequentially dividing the solute region into a plurality of solute rings radially outward with the center point of the target region as the center; includes: analyzing the imaging data to obtain the minimum resolution of the imaging data; sequentially dividing the solute region into a plurality of solute rings according to the minimum resolution radially outward with the center point of the target region as the center.

6. An image processing apparatus, characterized in that, comprising: an image acquisition module for acquiring imaging data of a target object; a region determination module for determining a solute region and a target region of the imaging data, and taking the center point of the target region as the center, and sequentially dividing the solute region into a plurality of solute rings radially outward; Among them, determining the solute region and the target region of the imaging data, and taking the center point of the target region as the center, and successively dividing the solute region into a plurality of solute rings radially outward, includes: dividing the imaging data into a solute region and a target region according to the gray value, the first threshold, and the second threshold in the imaging data; dividing the region with a gray value between 0 and the first threshold into a solute region, and dividing the region with a gray value between the first threshold and the second threshold into a target region; wherein, the first threshold is less than the second threshold; An imaging analysis module, configured to analyze the imaging data to obtain pixel information of each of the solute rings; An information processing module, configured to determine the concentration information of each of the solute rings according to the light incident intensity for generating the imaging data, the size information of the target object, and the pixel information of each of the solute rings; Among them, the following formula is used to determine the concentration information of each of the solute rings: where n is the total number of solute rings; c n is the concentration of the outermost solute ring; c n-1 is the concentration of the second outermost solute ring; L is the width of the solute ring; r is the radius of the target area; δ is the total diameter of the target; I 0 is the light incident intensity for generating the imaging data; is the average gray value of the target area; is the average gray value of the outermost solute ring; is the average gray value of the second outermost solute ring; μ a is the absorption coefficient of the solute element at the photon energy; μ b is the absorption coefficient of the solvent element at the photon energy.

7. An electronic device, characterized in that, it includes: a memory for storing a computer program; a processor for executing the method according to any one of claims 1 to 5 to automatically calibrate a sensor to be measured.

8. A computer-readable storage medium, characterized in that, it includes: a program, when it runs by means of an electronic device, causes the electronic device to execute the method according to any one of claims 1 to 5.

Images