Object detection method, device and equipment

Abstract

The invention provides an object detection method, device and equipment. The method comprises the following steps: acquiring a target X-ray intensity value of a to-be-detected object collected by an X-ray detector; inquiring the obtained information table through the target X-ray intensity value to obtain a first mass thickness value of the first base material and a second mass thickness value of the second base material; determining second attribute information of a second unknown object based on the first mass thickness value, the second mass thickness value and the first attribute information of the first unknown object; or, on the basis of the first mass thickness value, the second mass thickness value, the third attribute information of the first unknown object and the fourth attribute information of the second unknown object, the fifth attribute information of the first unknown object and the sixth attribute information of the second unknown object are determined. According to the technical scheme, the detection accuracy can be improved.

Description

Technical Field

[0001] The present application relates to the field of non-invasive detection, and in particular to an object detection method, device and equipment. Background Art

[0002] With the growing demand for security inspections, security inspection equipment is becoming increasingly common, and these devices often utilize X-ray technology to perform security inspections. For example, security inspection equipment may include an X-ray generator and an X-ray detector, with an object to be inspected placed on a conveyor. While the conveyor is in motion, the X-ray generator emits X-rays toward the object, while the X-ray detector receives the X-rays that pass through it and forms an image of the object based on the X-rays. Specifically, the X-ray detector captures an X-ray image of the object. Based on this X-ray image, the detector analyzes the object's internal structure to determine the object's type, also known as its category.

[0003] However, when two objects are superimposed together, that is, when the object to be detected is the superposition of a first unknown object and a second unknown object, it is impossible to analyze the internal structure of the object to be detected based on the X-ray image, that is, the detection of the object to be detected cannot be achieved, and there are problems such as detection errors. Summary of the Invention

[0004] The present application provides an object detection method, the method comprising:

[0005] Obtaining a target X-ray intensity value of an object to be detected collected by an X-ray detector; wherein the object to be detected is an object formed by superimposing a first unknown object and a second unknown object;

[0006] querying the acquired information table using the target X-ray intensity value to obtain a first mass thickness value of the first base material and a second mass thickness value of the second base material; wherein the mass thickness value is a product value of thickness and density; wherein the information table includes a correspondence between the sample X-ray intensity value, the mass thickness value of the first base material, and the mass thickness value of the second base material; wherein the first base material and the second base material are materials with known effective atomic numbers, and the effective atomic numbers of the first unknown object and the second unknown object are within the effective atomic number range of the first base material and the second base material;

[0007] determining second attribute information of the second unknown object based on the first mass thickness value and the second mass thickness value, and the first attribute information of the first unknown object;

[0008] Alternatively, based on the first mass thickness value and the second mass thickness value, as well as the third attribute information of the first unknown object and the fourth attribute information of the second unknown object, the fifth attribute information of the first unknown object and the sixth attribute information of the second unknown object are determined.

[0009] The present application provides an object detection device, comprising:

[0010] an acquisition module, configured to acquire a target X-ray intensity value of an object to be detected collected by the X-ray detector; wherein the object to be detected is an object formed by superimposing a first unknown object and a second unknown object;

[0011] a query module, configured to query the acquired information table using the target X-ray intensity value to obtain a first mass thickness value of the first base material and a second mass thickness value of the second base material; wherein the mass thickness value is a product value of thickness and density; wherein the information table includes a correspondence between the sample X-ray intensity value, the mass thickness value of the first base material, and the mass thickness value of the second base material; wherein the first base material and the second base material are materials with known effective atomic numbers, and the effective atomic numbers of the first unknown object and the second unknown object are within a range of the effective atomic numbers of the first base material and the second base material;

[0012] a determining module, configured to determine second attribute information of the second unknown object based on the first mass thickness value and the second mass thickness value, and the first attribute information of the first unknown object;

[0013] Alternatively, based on the first mass thickness value and the second mass thickness value, as well as the third attribute information of the first unknown object and the fourth attribute information of the second unknown object, the fifth attribute information of the first unknown object and the sixth attribute information of the second unknown object are determined.

[0014] The present application provides an electronic device, comprising: a processor and a machine-readable storage medium, wherein the machine-readable storage medium stores machine-executable instructions that can be executed by the processor; the processor is used to execute the machine-executable instructions to implement the object detection method of the above example of the present application.

[0015] The present application provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements the object detection method of the above example of the present application.

[0016] The present application provides a machine-readable storage medium, which stores machine-executable instructions that can be executed by a processor; wherein the processor is used to execute the machine-executable instructions, and when the machine-executable instructions are executed, the object detection method of the above example of the present application is implemented.

[0017] As can be seen from the above technical solutions, in the embodiment of the present application, the information table can be queried based on the target X-ray intensity value of the object to be detected to obtain the first mass thickness value of the first base material and the second mass thickness value of the second base material, and then the attribute information of the first unknown object and the attribute information of the second unknown object can be determined based on the first mass thickness value and the second mass thickness value. In this way, the detection of the object to be detected can be achieved based on the first mass thickness value of the first base material and the second mass thickness value of the second base material, thereby improving the detection accuracy and avoiding problems such as detection errors. When two objects are superimposed together, the identification and non-invasive detection of the superimposed objects can also be achieved based on X-rays, and the identification of the material type (for example, determining the type of the unknown object) and the quantitative analysis of the material composition (for example, determining the mass thickness value of the unknown object) can be achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a flow chart of an object detection method in one embodiment of the present application;

[0019] Figure 2 is a flow chart of an object detection method in one embodiment of the present application;

[0020] Figure 3 is a flow chart of an object detection method in one embodiment of the present application;

[0021] Figure 4 is a flow chart of an object detection method in one embodiment of the present application;

[0022] Figure 5 is a schematic structural diagram of an object detection device in one embodiment of the present application;

[0023] Figure 6 It is a hardware structure diagram of an electronic device in one embodiment of the present application. DETAILED DESCRIPTION

[0024] In the embodiment of the present application, an object detection method is proposed, which can be applied to electronic devices. Figure 1 FIG. 1 is a flow chart of the object detection method, which may include:

[0025] Step 101: Acquire a target X-ray intensity value of an object to be detected collected by an X-ray detector; wherein the object to be detected is an object formed by superimposing a first unknown object and a second unknown object.

[0026] Step 102: query the acquired information table through the target X-ray intensity value to obtain a first mass thickness value of the first base material and a second mass thickness value of the second base material; wherein the mass thickness value is the product of thickness and density; wherein the information table includes a correspondence between the sample X-ray intensity value, the mass thickness value of the first base material, and the mass thickness value of the second base material; wherein the first base material and the second base material are materials with known effective atomic numbers, and the effective atomic numbers of the first unknown object and the second unknown object are within the effective atomic number range of the first base material and the second base material.

[0027] Step 103: Determine the second attribute information of the second unknown object based on the first mass thickness value and the second mass thickness value, and the first attribute information of the first unknown object; or, determine the fifth attribute information of the first unknown object and the sixth attribute information of the second unknown object based on the first mass thickness value and the second mass thickness value, and the third attribute information of the first unknown object and the fourth attribute information of the second unknown object.

[0028] Exemplarily, the first attribute information may include but is not limited to the first type parameter of the first unknown object and the mass thickness value of the first unknown object, and the second attribute information may include but is not limited to the second type parameter of the second unknown object, or the second attribute information may include but is not limited to the second type parameter of the second unknown object and the mass thickness value of the second unknown object; wherein the first type parameter is used to identify the type of the first unknown object; wherein the second type parameter is used to identify the type of the second unknown object.

[0029] Exemplarily, there are overlapping areas and non-overlapping areas between the first unknown object and the second unknown object, and the target X-ray intensity value is the X-ray intensity value of the overlapping area; based on the first mass thickness value and the second mass thickness value, and the first attribute information of the first unknown object, before determining the second attribute information of the second unknown object, the X-ray intensity value of the non-overlapping area collected by the X-ray detector is obtained; wherein the non-overlapping area is the area where the first unknown object itself is located; based on the X-ray intensity value of the non-overlapping area, the obtained first mass attenuation coefficient of the first base material and the obtained second mass attenuation coefficient of the second base material, the first type parameter of the first unknown object and the mass thickness value of the first unknown object are determined.

[0030] Exemplarily, the third attribute information may include a mass thickness value of the first unknown object, the fourth attribute information may include a mass thickness value of the second unknown object, the fifth attribute information may include a first type parameter of the first unknown object, and the sixth attribute information may include a second type parameter of the second unknown object;

[0031] Alternatively, the third attribute information may include a first type parameter of the first unknown object, the fourth attribute information may include a second type parameter of the second unknown object, the fifth attribute information may include a mass thickness value of the first unknown object, and the sixth attribute information may include a mass thickness value of the second unknown object;

[0032] Alternatively, the third attribute information may include a first type parameter of the first unknown object, the fourth attribute information may include a mass thickness value of the second unknown object, the fifth attribute information may include a mass thickness value of the first unknown object, and the sixth attribute information may include a second type parameter of the second unknown object. In this embodiment of the present application, the mass thickness value refers to the product of the thickness and the density.

[0033] It will be understood that in the embodiments of the present application, attribute information is used to describe and distinguish different objects. Attribute information may include one or more of an object's type parameters, mass, thickness, and other information. In the above example, the third attribute information of the first unknown object and the fifth attribute information of the first unknown object are respectively used to indicate different attribute information of the first unknown object. Similarly, the fourth attribute information of the second unknown object and the sixth attribute information of the second unknown object are respectively used to indicate different attribute information of the second unknown object.

[0034] Exemplarily, an effective atomic number of the first unknown object may be determined based on the determined type of the first unknown object; a first type parameter of the first unknown object may be determined based on the effective atomic number of the first unknown object, the first effective atomic number of the first base material, and the second effective atomic number of the second base material;

[0035] The effective atomic number of the second unknown object can also be determined based on the determined type of the second unknown object; and the second type parameter of the second unknown object can be determined based on the effective atomic number of the second unknown object, the first effective atomic number of the first base material, and the second effective atomic number of the second base material.

[0036] Exemplarily, based on the first effective atomic number of the first base material, the second effective atomic number of the second base material, and the first type parameter, the effective atomic number of the first unknown object is determined, and the type of the first unknown object is determined based on the effective atomic number of the first unknown object; based on the first effective atomic number of the first base material, the second effective atomic number of the second base material, and the second type parameter, the effective atomic number of the second unknown object is determined, and the type of the second unknown object is determined based on the effective atomic number of the second unknown object.

[0037] Exemplarily, the effective atomic number of the first unknown object and the first type parameter satisfy the following expression relationship: X1=a1Z1+(1-a1)Z2; the effective atomic number of the second unknown object and the second type parameter satisfy the following expression relationship: Z X2 =b1Z1+(1-b1)Z2; where Z X1 represents the effective atomic number of the first unknown object, Z X2 represents the effective atomic number of the second unknown object, a1 represents the first type parameter, b1 represents the second type parameter, Z1 represents the first effective atomic number, and Z2 represents the second effective atomic number.

[0038] For example, the first mass thickness value, the second mass thickness value, the first type parameter of the first unknown object, the second type parameter of the second unknown object, the mass thickness value of the first unknown object and the mass thickness value of the second unknown object satisfy the following expression relationship: t1=a1t X +b1t Y , t2=(1-a1)t X +(1-b1)t Y ; Wherein, t1 represents the first mass thickness value, t2 represents the second mass thickness value; a1 represents the first type parameter of the first unknown object, b1 represents the second type parameter of the second unknown object; t X Indicates the mass and thickness of the first unknown object, t Y Indicates the mass and thickness of the second unknown object.

[0039] As can be seen from the above technical solutions, in the embodiment of the present application, the information table can be queried based on the target X-ray intensity value of the object to be detected to obtain the first mass thickness value of the first base material and the second mass thickness value of the second base material, and then the attribute information of the first unknown object and the attribute information of the second unknown object can be determined based on the first mass thickness value and the second mass thickness value. In this way, the detection of the object to be detected can be achieved based on the first mass thickness value of the first base material and the second mass thickness value of the second base material, thereby improving the detection accuracy and avoiding problems such as detection errors. When two objects are superimposed together, the identification and non-invasive detection of the superimposed objects can also be achieved based on X-rays, and the identification of the material type (for example, determining the type of the unknown object) and the quantitative analysis of the material composition (for example, determining the mass thickness value of the unknown object) can be achieved.

[0040] The above technical solutions of the embodiments of the present application are described below in conjunction with specific application scenarios.

[0041] An X-ray machine is a device that generates X-rays (X-rays), which can also be called an X-ray generator. The X-ray generator emits X-rays toward the object to be detected. The X-ray detector receives the X-rays that pass through the object to be detected, and images the object to be detected based on the X-rays to obtain an X-ray image of the object to be detected.

[0042] X-ray machines include single-energy X-ray machines and multi-energy X-ray machines (such as dual-energy X-ray machines). Single-energy X-ray machines use X-rays of a single energy to acquire X-ray images of the object being inspected. For example, an X-ray generator emits X-rays of a single energy toward the object being inspected, while an X-ray detector receives the X-rays of a single energy. The X-rays are then used to form an image of the object, resulting in an X-ray image of the object.

[0043] Furthermore, dual-energy X-ray machines use two energies of X-rays to acquire X-ray images of the object being inspected, enabling more accurate differentiation between different substances. For example, an X-ray generator emits two energies of X-rays toward the object being inspected, while an X-ray detector receives the two energies of X-rays. These two energies are then used to create an image of the object being inspected, resulting in an X-ray image of the object.

[0044] For a single-energy X-ray machine, when the X-ray generator emits X-rays toward the object to be detected, the intensity change of the X-rays passing through the single object to be detected follows the Beer-Lambert law, as shown in formula (1).

[0045] I(E)=I0(E)exp(-μ(E)t) Formula (1)

[0046] E represents the incident X-ray energy, i.e., the energy of the X-rays emitted by the X-ray generator. I0(E) is the initial X-ray intensity, i.e., the X-ray intensity value when the X-ray generator emits X-rays. This initial X-ray intensity corresponds to the incident X-ray energy E and is a known value. I(E) is the target X-ray intensity observed by the X-ray detector, i.e., the X-ray intensity value when the X-ray detector receives X-rays that have passed through the object to be inspected. This target X-ray intensity corresponds to the incident X-ray energy E and is a known value.

[0047] μ(E) represents the mass attenuation coefficient of the object to be detected. This mass attenuation coefficient corresponds to the incident X-ray energy E and is an unknown value. That is, the mass attenuation coefficient corresponding to the incident X-ray energy E needs to be determined.

[0048] t represents the mass thickness of the object to be tested. The mass thickness value is an unknown value and needs to be determined. For example, the mass thickness value can be the thickness of the object to be tested multiplied by the density.

[0049] The exp function is used to represent an exponential function with the natural constant e as the base.

[0050] In formula (1), the mass attenuation coefficient and mass thickness values ​​are related to the type of object to be detected, and the type of the object to be detected can be determined based on the mass attenuation coefficient and mass thickness values. However, the mass attenuation coefficient and mass thickness values ​​are both unknown values, and it is impossible to determine the mass attenuation coefficient and mass thickness values ​​based on formula (1), and thus the type of the object to be detected. In summary, single-energy X-ray machines do not have the ability to distinguish types, and the information observed by the X-ray detector cannot be used to simultaneously solve for the mass attenuation coefficient and mass thickness values.

[0051] In a dual-energy X-ray machine, the X-ray generator emits X-rays of two energies toward the object to be inspected. For example, two X-ray generators generate X-rays of two different energies, or a single X-ray generator operates at two different voltages to generate X-rays of two different energies. Due to the differences in absorption rates of different materials for X-rays of different energies, the X-ray detector is able to receive X-rays of two different energies and convert them into X-ray images. Based on this, when two X-rays of different energies pass through a single object to be inspected, the following equations can be used:

[0052] I(E1)=I0(E1)exp(-μ(E1)t) Formula (2)

[0053] I(E2)=I0(E2)exp(-μ(E2)t) Formula (3)

[0054] E1 represents the first incident X-ray energy, E2 represents the second incident X-ray energy, I0(E1) represents the initial X-ray intensity value of the first incident X-ray energy, I0(E2) represents the initial X-ray intensity value of the second incident X-ray energy, I(E1) represents the target X-ray intensity value corresponding to the first incident X-ray energy observed by the X-ray detector, and I(E2) represents the target X-ray intensity value corresponding to the second incident X-ray energy observed by the X-ray detector. In addition, μ(E) and t represent the mass attenuation coefficient and mass thickness value of the object to be detected. Obviously, when the mass attenuation coefficient and mass thickness value are unknown, the mass attenuation coefficient and mass thickness value can be determined by formula (2) and formula (3). Considering that the mass attenuation coefficient and mass thickness value are related to the effective atomic number and electron density of the material, they can be used to distinguish different materials. Therefore, the type of the object to be detected can be determined based on the mass attenuation coefficient and mass thickness value.

[0055] In summary, the dual-energy X-ray machine has the ability to distinguish types, and the information observed by the X-ray detector can simultaneously solve the mass attenuation coefficient and mass thickness value, thereby being able to distinguish different substances more accurately.

[0056] However, when two objects are superimposed together, that is, the object to be detected is the superposition of the first unknown object and the second unknown object, there are four unknown parameters, namely the mass attenuation coefficient and mass thickness value of the first unknown object, and the mass attenuation coefficient and mass thickness value of the second unknown object. It is impossible to determine the mass attenuation coefficient and mass thickness value of the first unknown object and the mass attenuation coefficient and mass thickness value of the second unknown object through formula (2) and formula (3), and it is also impossible to determine the type of the first unknown object and the type of the second unknown object.

[0057] In response to the above findings, this embodiment proposes an object detection method that, when two objects are superimposed on each other, can realize the identification and non-invasive detection of the superimposed objects based on X-rays, and realize material type identification (determining the type of unknown objects) and quantitative analysis of material composition (determining the mass and thickness values ​​of unknown objects).

[0058] In order to achieve the recognition and detection of superimposed objects, in this embodiment, two materials with known effective atomic numbers can be selected and referred to as the first base material and the second base material. For example, the effective atomic number of a single substance is consistent with the nuclear charge number of its nucleus, and the effective atomic number of a compound can be estimated by the following empirical formula: c i is the number of atoms of the element in the compound, Z i is the effective atomic number of the element, n can be an empirical value, generally between 2-4.

[0059] Assuming that the effective atomic number of all unknown objects is no greater than A, and the effective atomic number of all unknown objects is no less than B, and B is less than A, then when selecting the first base material and the second base material, the effective atomic number of the first base material needs to be less than B, and the effective atomic number of the second base material needs to be greater than A. In this way, the effective atomic number of the unknown object is within the effective atomic number range of the first base material and the second base material, that is, the effective atomic number of the unknown object can be within the effective atomic number range from A to B.

[0060] For example, if the unknown object is a substance near organic matter, the first base material can be acrylic (PMMA) and the second base material can be aluminum (Al). Of course, acrylic is only an example of the first base material, and aluminum is only an example of the second base material, and there is no limitation on this.

[0061] For example, after selecting the first and second base materials, since the two materials are selected with known effective atomic numbers, the effective atomic number of the first base material (hereinafter referred to as the first effective atomic number) and the effective atomic number of the second base material (hereinafter referred to as the second effective atomic number) can be obtained. Furthermore, the mass attenuation curve of the first and second base materials can be obtained theoretically or experimentally. The method for obtaining these mass attenuation curves is not limited, as long as the mass attenuation curves can be obtained.

[0062] Based on the mass attenuation curve of the first base material, the mass attenuation curve can be queried through the incident X-ray energy E to obtain the mass attenuation coefficient μ(E) corresponding to the incident X-ray energy E. This mass attenuation coefficient is the mass attenuation coefficient of the first base material, which will be referred to as the first mass attenuation coefficient later.

[0063] Based on the mass attenuation curve of the second base material, the mass attenuation curve can be queried through the incident X-ray energy E to obtain the mass attenuation coefficient μ(E) corresponding to the incident X-ray energy E. This mass attenuation coefficient is the mass attenuation coefficient of the second base material, which will be subsequently recorded as the second mass attenuation coefficient.

[0064] In summary, the first effective atomic number of the first base material, the second effective atomic number of the second base material, the first mass attenuation coefficient of the first base material, and the second mass attenuation coefficient of the second base material are obtained.

[0065] For example, after selecting the first base material and the second base material, an information table may be maintained, which may include a correspondence between the sample X-ray intensity value, the mass thickness value of the first base material, and the mass thickness value of the second base material. For example, the process of obtaining the information table may include:

[0066] An X-ray generator emits X-rays toward a sample material, and an X-ray detector acquires a sample X-ray intensity value for the sample material. The sample material may be a stack of a first base material and a second base material, and the mass and thickness values ​​of the first base material and the second base material are both known. Based on this, a corresponding relationship between the sample X-ray intensity value, the mass and thickness values ​​of the first base material, and the mass and thickness values ​​of the second base material may be recorded in an information table.

[0067] Table 1 shows an example of this information table. For example, a sample material is obtained by superimposing a first base material having a mass thickness of d11 with a second base material having a mass thickness of d21. The sample X-ray intensity value c1 of this sample material is recorded in the information table. A sample material is obtained by superimposing a first base material having a mass thickness of d12 with a second base material having a mass thickness of d22. The sample X-ray intensity value c2 of this sample material is recorded in the information table. This information is then maintained in this manner.

[0068] Table 1

[0069] Sample X-ray intensity value Mass thickness value of the first base material Mass thickness value of the second base material Sample X-ray intensity value c1 Mass thickness value d11 Mass thickness value d21 Sample X-ray intensity value c2 Mass thickness value d12 Mass thickness value d22 Sample X-ray intensity value c3 Mass thickness value d13 Mass thickness value d23 Sample X-ray intensity value c4 Mass thickness value d14 Mass thickness value d24 … … …

[0070] In one possible embodiment, the sample X-ray intensity value may include K sample sub-intensity values, where K may be a positive integer. For example, for a single-energy X-ray machine, the X-ray generator emits X-rays of one energy to the sample material, and the sample X-ray intensity value includes one sample sub-intensity value. For a dual-energy X-ray machine, the X-ray generator emits X-rays of two energies to the sample material, and the sample X-ray intensity value includes two sample sub-intensity values, as shown in Table 2, which is an example of an information table. For a triple-energy X-ray machine, the X-ray generator emits X-rays of three energies to the sample material, and the sample X-ray intensity value includes three sample sub-intensity values, and so on. For the convenience of description, the information table shown in Table 2 is used as an example.

[0071] Table 2

[0072] Sample X-ray intensity value Mass thickness value of the first base material Mass thickness value of the second base material Sample sub-intensity values ​​c11, c12 Mass thickness value d11 Mass thickness value d21 Sample sub-intensity values ​​c21, c22 Mass thickness value d12 Mass thickness value d22 Sample sub-intensity values ​​c31, c32 Mass thickness value d13 Mass thickness value d23 Sample sub-intensity values ​​c41, c42 Mass thickness value d14 Mass thickness value d24 … … …

[0073] For example, after selecting the first base material and the second base material, for a dual-energy X-ray machine, when two X-rays of different energies pass through a single object to be detected, the object to be detected is called an unknown object X, and the mass attenuation coefficient of the unknown object X is μ X Then, the effective atomic number of the unknown object X is within the effective atomic number range of the first and second base materials. The linear combination of the first mass attenuation coefficient μ1 of the first base material and the second mass attenuation coefficient μ2 of the second base material can be used to approximate the mass attenuation coefficient of the unknown object X as μ X , that is, μ X =a1μ1+a2μ2. In the above formula, the first mass attenuation coefficient μ1, the second mass attenuation coefficient μ2 and the mass attenuation coefficient μ X Both correspond to the incident X-ray energy E.

[0074] In the above formula, the sum of a1 and a2 can be a fixed value, such as 1. Therefore, the above formula can also be equivalent to: μ X=a1μ1+(1-a1)μ2. a1 represents the base material decomposition coefficient, that is, the base material decomposition coefficient when the unknown object X is decomposed into the first base material and the second base material. The base material decomposition coefficient a1 can also be called the type parameter of the unknown object X, which is used to determine the type of the unknown object X.

[0075] On this basis, when two X-rays of different energies pass through a single object to be detected, formulas (2) and (3) can be further modified, that is, the mass attenuation coefficient μ of the unknown object X is replaced by X Substitute into the above formula, that is, μ X =a1μ1+(1-a1)μ2, as shown in formula (4) and formula (5).

[0076] I(E1)=I0(E1)exp[-(a1μ1(E1)+(1-a1)μ2(E1))t] Formula (4)

[0077] I(E2)=I0(E2)exp[-(a1μ1(E2)+(1-a1)μ2(E2))t] Formula (5)

[0078] E1 represents the first incident X-ray energy, E2 represents the second incident X-ray energy, I0(E1) represents the initial X-ray intensity value for the first incident X-ray energy, I0(E2) represents the initial X-ray intensity value for the second incident X-ray energy, I(E1) represents the target X-ray intensity value corresponding to the first incident X-ray energy, and I(E2) represents the target X-ray intensity value corresponding to the second incident X-ray energy. μ1(E1) represents the first mass attenuation coefficient μ1 of the first base material corresponding to the first incident X-ray energy, μ1(E2) represents the first mass attenuation coefficient μ1 of the first base material corresponding to the second incident X-ray energy, μ2(E1) represents the second mass attenuation coefficient μ2 of the second base material corresponding to the first incident X-ray energy, and μ2(E2) represents the second mass attenuation coefficient μ2 of the second base material corresponding to the second incident X-ray energy. Obviously, the first mass attenuation coefficient μ1 and the second mass attenuation coefficient μ2 can both be known values.

[0079] The type parameter a1 of the unknown object X represents the base material decomposition coefficient, and t represents the mass thickness value of the unknown object X. When the type parameter a1 and the mass thickness value are unknown values, the type parameter a1 and the mass thickness value can be determined by formula (4) and formula (5), and the type parameter a1 can be used to distinguish different substances.

[0080] In a possible implementation, formula (4) may be transformed to obtain formula (6) in integral form, and formula (5) may be transformed to obtain formula (7) in integral form.

[0081]

[0082] For example, when two unknown objects are superimposed together, the two unknown objects are referred to as a first unknown object X and a second unknown object Y, and the superimposed object is referred to as an object to be detected. That is, the object to be detected is the object formed by superimposing the first unknown object X and the second unknown object Y. The effective atomic number of the first unknown object X is unknown, but falls within the effective atomic number range of the first base material and the second base material. The effective atomic number of the second unknown object Y is unknown, but falls within the effective atomic number range of the first base material and the second base material. In subsequent embodiments, the effective atomic number of the first unknown object X and the second unknown object Y can be determined, and then the type of the unknown object can be analyzed.

[0083] For a single-energy X-ray machine, a multi-energy X-ray machine (such as a dual-energy X-ray machine), etc., when the X-ray generator emits X-rays toward the object to be detected, the intensity change of the X-rays passing through the object to be detected (i.e., the first unknown object X and the second unknown object Y) follows the Beer-Lambert law, as shown in formula (8).

[0084]

[0085] In the above formula, E k Indicates the kth incident X-ray energy. For a single-energy X-ray machine, the value range of k is 1. For a dual-energy X-ray machine, the value range of k is 1 and 2, and so on. I0(E) represents the initial X-ray intensity value of the kth incident X-ray energy. I(E k ) represents the target X-ray intensity value corresponding to the kth incident X-ray energy observed by the X-ray detector. X (E) represents the mass attenuation coefficient of the first unknown object X corresponding to the kth incident X-ray energy, which is subsequently denoted as μ X , t X Represents the mass and thickness of the first unknown object X. μ Y (E) represents the mass attenuation coefficient of the second unknown object Y corresponding to the kth incident X-ray energy, which is subsequently denoted as μ Y , t Y Indicates the mass and thickness of the second unknown object Y.

[0086] For mass attenuation coefficient μ X , can be approximated using the first mass attenuation coefficient μ1 of the first base material and the second mass attenuation coefficient μ2 of the second base material, as μ X =a1μ1+a2μ2, a1 represents the first type parameter of the first unknown object X, a2=1-a1. For the mass attenuation coefficient μ Y, can be approximated using the first mass attenuation coefficient μ1 of the first base material and the second mass attenuation coefficient μ2 of the second base material, as μ Y =b1μ1+b2μ2, b1 represents the second type parameter of the second unknown object Y, b2=1-b1.

[0087] On this basis, formula (8) can also be transformed to replace the mass attenuation coefficient μ of the first unknown object X X Substitute into the above formula, that is, μ X =a1μ1+a2μ2, the mass attenuation coefficient μ of the second unknown object Y Y Substitute into the above formula, that is, μ Y =b1μ1+b2μ2, thus we can get formula (9). Based on formula (9), we can also transform formula (9) to get formula (10).

[0088]

[0089] For example, for a single-energy X-ray machine, a multi-energy X-ray machine (such as a dual-energy X-ray machine), etc., when the X-ray generator emits X-rays to a sample material (composed of a first base material and a second base material stacked together), when the X-rays pass through the sample material, referring to formula (8), the following formula (11) can be obtained.

[0090]

[0091] In formula (11), μ1 represents the first mass attenuation coefficient of the first base material, t1 represents the mass thickness value of the first base material (recorded as the first mass thickness value), μ2 represents the second mass attenuation coefficient of the second base material, and t2 represents the mass thickness value of the second base material (recorded as the second mass thickness value).

[0092] Combining formula (10) and formula (11), we can derive the following formula (12). In addition, considering that a2=1-a1, b2=1-b1, formula (12) can also be transformed into formula (13).

[0093] t1=a1t X +b1t Y , t2=a2t X +b2t Y Formula (12)

[0094] t1=a1t X +b1t Y , t2=(1-a1)t X +(1-b1)t Y Formula (13)

[0095] From formula (13), it can be seen that when the first mass thickness value t1 and the second mass thickness value t2 are known, there are four variables (a1, b1, t X ,t Y ), a1 represents the first type parameter of the first unknown object X, t X represents the mass thickness value of the first unknown object X, b1 represents the second type parameter of the second unknown object Y, t Y Represents the mass thickness value of the second unknown object Y. Based on the two known variables, the remaining two variables can be solved by combining the first mass thickness value t1 and the second mass thickness value t2, thereby completing object detection.

[0096] Under the above technical concept, an object detection method is proposed in an embodiment of the present application. Based on the first mass thickness value and the second mass thickness value, if the first attribute information of the first unknown object is known, the second attribute information of the second unknown object can be determined. In this example, the first attribute information may include the first type parameter of the first unknown object and the mass thickness value of the first unknown object, and the second attribute information may include the second type parameter of the second unknown object, or the second attribute information may include the second type parameter of the second unknown object and the mass thickness value of the second unknown object. Based on this, if the first type parameter a1 of the first unknown object X and the mass thickness value t of the first unknown object X are known X Then the second type parameter b1 of the second unknown object Y and the mass thickness value t of the second unknown object Y can be solved. Y Alternatively, if the first type parameter a1 of the first unknown object X and the mass thickness value t of the first unknown object X are known X , we can solve the second type parameter b1 of the second unknown object Y. In this example, we can solve the second type parameter b1 of the second unknown object Y and the mass thickness value t of the second unknown object Y. Y For example. On this basis, see Figure 2 FIG. 1 is a flow chart of the object detection method, which may include:

[0097] Step 201: Obtain a target X-ray intensity value of an object to be detected collected by an X-ray detector. The object to be detected is an object formed by superimposing a first unknown object X and a second unknown object Y.

[0098] For example, an X-ray generator emits X-rays toward an object to be detected, and an X-ray detector collects X-ray intensity values ​​of the X-rays passing through the object to be detected, that is, target X-ray intensity values.

[0099] Step 202: Query the acquired information table using the target X-ray intensity value to obtain a first mass thickness value of the first base material and a second mass thickness value of the second base material. The mass thickness value may be a product of thickness and density. For example, the first mass thickness value may be a product of the thickness and density of the first base material, and the second mass thickness value may be a product of the thickness and density of the second base material.

[0100] Exemplarily, for a single-energy X-ray machine, when acquiring the information table, the sample X-ray intensity value includes a sample sub-intensity value, and the target X-ray intensity value includes a target sub-intensity value.

[0101] On this basis, for each sample X-ray intensity value in the information table, a target loss value for that sample X-ray intensity value is calculated based on the difference between the target X-ray intensity value and the sample X-ray intensity value. As shown in Table 1, the target loss value for sample X-ray intensity value c1 is the absolute value of the difference between the target X-ray intensity value and the sample X-ray intensity value c1. Based on the sample X-ray intensity value corresponding to the minimum target loss value, the first mass thickness value of the first base material and the second mass thickness value of the second base material are queried from the information table.

[0102] For example, if the minimum target loss value corresponds to the sample X-ray intensity value c3, the mass thickness value d13 corresponding to the sample X-ray intensity value c3 is used as the first mass thickness value of the first base material, and the mass thickness value d23 corresponding to the sample X-ray intensity value c3 is used as the second mass thickness value of the second base material.

[0103] For example, in the case of a multi-energy X-ray machine, when obtaining the information table, the sample X-ray intensity value may include K sample sub-intensity values, and the target X-ray intensity value may include K target sub-intensity values ​​corresponding one-to-one to the K sample sub-intensity values, where K may be a positive integer greater than 1. For example, taking a dual-energy X-ray machine as an example, the sample X-ray intensity value may include two sample sub-intensity values, and the target X-ray intensity value may include two target sub-intensity values ​​corresponding one-to-one to the two sample sub-intensity values.

[0104] On this basis, for each sample X-ray intensity value in the information table, the target loss value of the sample X-ray intensity value is calculated based on the K target sub-intensity values ​​of the target X-ray intensity value and the K sample sub-intensity values ​​of the sample X-ray intensity value. For example, the target loss value Loss of the sample X-ray intensity value can be expressed as: Loss(f1(t1,t2),f2(t1,t2)…,f k (t1,t2);I 1,obs ,I 2,obs ,…,I k,obs), f1(t1, t2) represents the first sample sub-intensity value, f2(t1, t2) represents the second sample sub-intensity value, ..., f k (t1, t2) represents the Kth sample sub-intensity value, I 1,obs Indicates the first target sub-intensity value corresponding to f1(t1,t2), I 2,obs Indicates the second target sub-intensity value, ..., I k,obs Represents the K-th target sub-intensity value.

[0105] When calculating the target loss value, the absolute value of the difference between the target sub-intensity value and the sample sub-intensity value can be calculated, and then the average of the absolute values ​​of all the differences is used as the target loss value. For example, to calculate I 1,obs The absolute value of the difference with f1(t1,t2), I 2,obs The absolute value of the difference from f2(t1,t2), ..., I k,obs With f k The absolute value of the difference between (t1, t2) is calculated, and then the average of the absolute values ​​of all differences is used as the target loss value.

[0106] Alternatively, when calculating the target loss value, the least squares method can be used to determine the target loss value, that is, Loss = ∑ i [f i (t1,t2)-I i,obs ] 2 In the above formula, the value of i is 1 to k.

[0107] Of course, the above are just two examples, and there is no limitation on the method for determining the target loss value. The target loss value can be determined based on the difference between the target sub-intensity value and the corresponding sample sub-intensity value.

[0108] Based on the sample X-ray intensity value corresponding to the minimum target loss value, the first mass thickness value of the first base material and the second mass thickness value of the second base material can be queried from the information table. For example, as shown in Table 2, if the minimum target loss value corresponds to sample sub-intensity values ​​c31 and c32, the mass thickness value d13 corresponding to the sample sub-intensity values ​​c31 and c32 is used as the first mass thickness value of the first base material, and the mass thickness value d23 corresponding to the sample sub-intensity values ​​c31 and c32 is used as the second mass thickness value of the second base material.

[0109] Step 203: Obtain the first type parameter and mass thickness value of the first unknown object.

[0110] In a possible implementation, the first type parameter a1 of the first unknown object X and the mass thickness value t of the first unknown object X can be obtained by direct measurement. X .

[0111] For example, the first unknown object can be a bottle, pallet, container, etc. of a fixed shape, and the second unknown object can be a liquid in a bottle (the type of liquid that needs to be detected), an object on a pallet (the type of object that needs to be detected), or an object in a container (the type of object that needs to be detected).

[0112] For a first unknown object with a fixed shape, such as a bottle, pallet, or container, the material of the first unknown object is single (i.e., the type of the first unknown object can be known), the thickness of the first unknown object is fixed (i.e., the mass and thickness value t of the first unknown object can be known), and the thickness of the first unknown object is fixed. X ), therefore, the type, thickness and density of the first unknown object can be measured by a prior measurement method. There is no restriction on the measurement method, as long as the type, thickness and density information can be obtained, thereby obtaining the first type parameter a1 and the mass thickness value t X .

[0113] For example, based on the thickness and density of the first unknown object, the mass thickness value t of the first unknown object can be determined. X , mass thickness value t X It can be thickness multiplied by density. Based on the type of the first unknown object, since the type (i.e., material type) corresponds to the effective atomic number, the effective atomic number of the first unknown object can be determined. Based on the effective atomic number of the first unknown object, the first type parameter a1 can be determined using the following formula: Z X1 =a1Z1+(1-a1)Z2. Z X1 Used to represent the effective atomic number of the first unknown object, Z1 can represent the first effective atomic number of the first base material, and Z2 can represent the second effective atomic number of the second base material.

[0114] In a possible implementation, the first type parameter a1 of the first unknown object X and the mass thickness value t of the first unknown object X can be obtained by indirect measurement. X .

[0115] For example, when a first unknown object and a second unknown object are superimposed, the first unknown object and the second unknown object have an overlapping region and a non-overlapping region. The non-overlapping region is the region of the first unknown object. The range of the first unknown object is larger than the range of the second unknown object. The second unknown object is within the range of the first unknown object, but the second unknown object does not exist in part of the first unknown object (i.e., the non-overlapping region).

[0116] For example, when an unknown liquid is superimposed on object A (object A is a flat-sized and single-type object, such as a notebook), there is a large difference between the effective atomic number of the liquid in the superimposed area and the actual effective atomic number of the liquid. Directly using the effective atomic number of the liquid in the superimposed area to determine the liquid type will lead to an increase in the false alarm rate.

[0117] In this scenario, object A can be larger than the liquid area. Therefore, object A can be considered the first unknown object, and the unknown liquid can be considered the second unknown object. Object A and the unknown liquid have overlapping and non-overlapping regions. The non-overlapping region is where only object A exists, and the overlapping region is where both object A and the unknown liquid exist. Determining the overlapping and non-overlapping regions can be done through separate measurements, manual selection, or intelligent selection based on machine learning or deep learning.

[0118] In the above application scenario, since the first unknown object and the second unknown object have overlapping areas and non-overlapping areas, the X-ray intensity value of the overlapping area collected by the X-ray detector can be obtained, and the X-ray intensity value of the non-overlapping area collected by the X-ray detector can be obtained. In step 201, the target X-ray intensity value is the X-ray intensity value of the overlapping area. Based on the X-ray intensity value of the non-overlapping area, the first type parameter a1 of the first unknown object X and the mass thickness value t of the first unknown object X can be obtained. X .

[0119] First, the first mass attenuation coefficient μ1 of the first base material and the second mass attenuation coefficient μ2 of the second base material are known, and thus the first mass attenuation coefficient μ1 and the second mass attenuation coefficient μ2 can be obtained.

[0120] Then, based on the X-ray intensity value of the non-overlapping area (i.e., the X-ray intensity value for the first unknown object, which is independent of the second unknown object), the first mass attenuation coefficient μ1 and the second mass attenuation coefficient μ2, the first type parameter a1 and the mass thickness value t of the first unknown object X can be determined. X .

[0121] For example, as shown in formulas (4) and (5), or as shown in formulas (6) and (7), I0(E1) and I0(E2) can represent the initial X-ray intensity values, and I(E1) and I(E2) can represent the X-ray intensity values ​​in the non-overlapping region (i.e., the X-ray intensity values ​​corresponding to the first incident X-ray energy and the second incident X-ray energy), and the above parameters are all known values. In addition, μ1(E1) and μ1(E2) can represent the first mass attenuation coefficient corresponding to the incident X-ray energy, and μ2(E1) and μ2(E2) can represent the second mass attenuation coefficient corresponding to the incident X-ray energy, and both mass attenuation coefficients are known values.

[0122] From the above, we can see that only the first type parameter a1 and the mass thickness value t X are two unknown values, so the first type parameter a1 and mass thickness value t can be solved by formula (4) and formula (5) X Alternatively, the first type parameter a1 and mass thickness value t can be solved by formula (6) and formula (7) X .

[0123] Step 204: Determine the second type parameter of the second unknown object and the mass thickness value of the second unknown object based on the first mass thickness value of the first base material, the second mass thickness value of the second base material, the first type parameter of the first unknown object, and the mass thickness value of the first unknown object. Alternatively, determine the second type parameter of the second unknown object based on the first mass thickness value of the first base material, the second mass thickness value of the second base material, the first type parameter of the first unknown object, and the mass thickness value of the first unknown object.

[0124] For example, based on the first mass thickness value of the first base material, the second mass thickness value of the second base material, the first type parameter of the first unknown object and the mass thickness value of the first unknown object, formula (13) can be used to determine the second type parameter of the second unknown object and the mass thickness value of the second unknown object.

[0125] In formula (13), t1 represents the first mass thickness value, t2 represents the second mass thickness value, a1 represents the first type parameter of the first unknown object, t X represents the mass and thickness of the first unknown object. Obviously, the above four parameters are known parameters. In addition, b1 represents the second type parameter of the second unknown object, t Y Represents the mass thickness value of the second unknown object, and the above two parameters are unknown parameters. Based on the above four known parameters, the two unknown parameters are solved by formula (13), thereby obtaining the second type parameter b1 and the mass thickness value t Y .

[0126] Step 205: Determine the effective atomic number of the first unknown object based on the first effective atomic number of the first base material, the second effective atomic number of the second base material, and the first type parameter of the first unknown object. Determine the type of the first unknown object based on the effective atomic number of the first unknown object, thereby completing the detection of the first unknown object. Step 205 is optional. If the type of the first unknown object is known (see step 203, where the type of the first unknown object is pre-measured), the type of the first unknown object is not determined based on step 205. If the type of the first unknown object is unknown, the type of the first unknown object is determined based on step 205.

[0127] Step 206: Determine the effective atomic number of the second unknown object based on the first effective atomic number of the first base material, the second effective atomic number of the second base material, and the second type parameter of the second unknown object, and determine the type of the second unknown object based on the effective atomic number of the second unknown object to complete the detection of the second unknown object.

[0128] Exemplarily, the first effective atomic number Z1 of the first base material and the second effective atomic number Z2 of the second base material are known, and therefore, the first effective atomic number Z1 and the second effective atomic number Z2 can be obtained.

[0129] Based on the first effective atomic number Z1, the second effective atomic number Z2 and the first type parameter a1, the effective atomic number Z of the first unknown object X can be determined using the following formula: X1 :Z X1 =a1Z1+(1-a1)Z2. After obtaining the effective atomic number Z of the first unknown object X X1 Afterwards, since the effective atomic number has a corresponding relationship with the material type, the effective atomic number Z of the first unknown object X can be used to determine the material type. X1 The type of the first unknown object is determined.

[0130] Based on the first effective atomic number Z1, the second effective atomic number Z2 and the second type parameter b1, the effective atomic number Z of the second unknown object Y can be determined using the following formula: X2 :Z X2 =b1Z1+(1-b1)Z2. X2 Afterwards, since the effective atomic number has a corresponding relationship with the material type, the effective atomic number Z of the second unknown object Y can be used to determine the X2 Determine the type of the second unknown object.

[0131] For example, in a security inspection scenario, the object detection method can be applied to security detection equipment, and the object detection method is used to detect the type of unknown object (i.e., the type of unknown object). The types of unknown objects here can be carbon, iron, hydrogen, nitrogen, oxygen, etc., and can also be electronic products, liquids, corrosive items, metals, batteries, radioactive objects, ceramics, cosmetics, etc. Of course, the above are only examples of the types of unknown objects and are not limited to them.

[0132] Under the above technical concept, an object detection method is proposed in an embodiment of the present application. Based on the first mass thickness value and the second mass thickness value, if the third attribute information of the first unknown object and the fourth attribute information of the second unknown object are known, the fifth attribute information of the first unknown object and the sixth attribute information of the second unknown object are determined. In this example, the third attribute information includes the mass thickness value of the first unknown object, the fourth attribute information includes the mass thickness value of the second unknown object, the fifth attribute information includes the first type parameter of the first unknown object, and the sixth attribute information includes the second type parameter of the second unknown object. Based on this, if the mass thickness value t of the first unknown object X is known X and the mass and thickness value t of the second unknown object Y Y , we can solve the first type parameter a1 of the first unknown object X and the second type parameter b1 of the second unknown object Y. On this basis, see Figure 3 FIG. 1 is a flow chart of the object detection method, which may include:

[0133] Step 301: Acquire a target X-ray intensity value of an object to be detected collected by an X-ray detector. The object to be detected is a superposition of a first unknown object X and a second unknown object Y.

[0134] Step 302: Query the acquired information table through the target X-ray intensity value to obtain the first mass thickness value of the first base material and the second mass thickness value of the second base material.

[0135] Step 303: Obtain the mass and thickness value of the first unknown object and the mass and thickness value of the second unknown object.

[0136] In a possible implementation, the mass thickness value t of the first unknown object X can be obtained by direct measurement. X and the mass and thickness value t of the second unknown object Y Y For example, the first unknown object is an object of fixed shape. Through the method of prior measurement, the thickness and density of the first unknown object are measured. The density can be obtained based on weight / volume. There is no restriction on this measurement method. As long as the thickness and density can be obtained, the mass thickness value t of the first unknown object is determined based on the thickness and density of the first unknown object. X , mass thickness value t X The second unknown object is an object of fixed shape. The thickness and density of the second unknown object are measured by a method of prior measurement. Based on the thickness and density of the second unknown object, the mass thickness value t of the second unknown object is determined. Y , mass thickness value t Y It can be thickness times density.

[0137] In a possible implementation, the mass thickness value t of the first unknown object X can be obtained by indirect measurement. X and the mass and thickness value t of the second unknown object Y Y For example, an image of the object to be detected can be collected, and the mass thickness value t of the first unknown object X can be analyzed based on the image. X and the mass and thickness value t of the second unknown object Y Y Alternatively, an image of the object to be detected can be collected and input into a machine learning model to obtain the mass thickness value t of the first unknown object X. X and the mass and thickness value t of the second unknown object Y Y Of course, the above is just an example, and there is no limitation on this indirect measurement method. As long as the mass thickness value t of the first unknown object X can be obtained, X and the mass and thickness value t of the second unknown object Y Y That's it.

[0138] In a possible implementation, the mass thickness value t of the first unknown object X can be obtained by indirect measurement. X and the mass and thickness value t of the second unknown object Y Y For example, when testing fat percentage, it's difficult to obtain pure lean or fat meat. Instead, a flattened, uniform piece of lean meat (which may contain fat) and a flattened, uniform piece of fat meat (which may contain lean meat) are superimposed. The superimposed object to be tested is as square as possible. During the superposition process, a constrained phantom can be used, but the phantom should be as thin as possible to be negligible. Based on this process, the object to be tested, which includes both lean and fat meat, is obtained.

[0139] First, the total weight of the object to be detected (i.e., the superposition of lean meat and fat) can be obtained by weighing or other methods. The bottom area of ​​the object to be detected can be obtained by measurement or other methods. Based on the total weight of the object to be detected and the bottom area of ​​the object to be detected, the mass thickness of the object to be detected can be calculated. The mass thickness of the object to be detected is the mass thickness value t of the first unknown object X (e.g., lean meat). X The mass and thickness value t of the second unknown object Y (such as fat) Y For example, mass thickness * base area = thickness * base area * density, mass thickness * base area = volume * density = weight, so mass thickness = weight / base area. Obviously, the total weight of the object to be tested divided by the base area of ​​the object to be tested is the mass thickness of the object to be tested.

[0140] Then, during the fat rate test, for the object after the lean meat and fat meat are superimposed (i.e., the object to be tested), the fat rate of the object to be tested can be obtained. For example, the fat rate of the object to be tested can be obtained by using methods such as Soxhlet extraction and near-infrared measurement. There is no limitation on this, as long as the fat rate can be obtained. Since the fat rate represents the ratio between the mass of fat meat and the total mass of the object to be tested, when the second unknown object Y represents fat meat, the fat rate can be t Y / (t X +t Y ).

[0141] In summary, we can get t X +t Y The value of (i.e. the mass thickness of the object to be detected) and t Y / (t X +t Y ) value (i.e. the fat rate of the object to be detected), so the mass thickness value t of the first unknown object X can be solved X and the mass and thickness value t of the second unknown object Y Y .

[0142] Step 304: Determine first type parameters of the first unknown object and second type parameters of the second unknown object based on the first mass thickness value of the first base material, the second mass thickness value of the second base material, the mass thickness value of the first unknown object and the mass thickness value of the second unknown object.

[0143] For example, the first type parameter of the first unknown object and the second type parameter of the second unknown object can be determined by using formula (13). In formula (13), t1 represents the first mass thickness value, t2 represents the second mass thickness value, and t X Indicates the mass and thickness of the first unknown object, t Y represents the mass thickness of the second unknown object. Obviously, the above four parameters are known parameters. In addition, a1 represents the first type parameter of the first unknown object, and b1 represents the second type parameter of the second unknown object. These two parameters are unknown parameters. Based on the above four known parameters, the two unknown parameters are solved using formula (13) to obtain a1 and b1.

[0144] Step 305: Determine the effective atomic number of the first unknown object based on the first effective atomic number of the first base material, the second effective atomic number of the second base material, and the first type parameter of the first unknown object, and determine the type of the first unknown object based on the effective atomic number of the first unknown object, thereby completing the detection of the first unknown object.

[0145] Step 306: Determine the effective atomic number of the second unknown object based on the first effective atomic number of the first base material, the second effective atomic number of the second base material, and the second type parameter of the second unknown object, and determine the type of the second unknown object based on the effective atomic number of the second unknown object to complete the detection of the second unknown object.

[0146] Under the above technical concept, an object detection method is proposed in an embodiment of the present application. Based on the first mass thickness value and the second mass thickness value, if the third attribute information of the first unknown object and the fourth attribute information of the second unknown object are known, the fifth attribute information of the first unknown object and the sixth attribute information of the second unknown object are determined. In this example, the third attribute information includes the first type parameter of the first unknown object, the fourth attribute information includes the second type parameter of the second unknown object, the fifth attribute information includes the mass thickness value of the first unknown object, and the sixth attribute information includes the mass thickness value of the second unknown object. Based on this, if the first type parameter a1 of the first unknown object X and the second type parameter b1 of the second unknown object Y are known, the mass thickness value t of the first unknown object X can be solved. X and the mass and thickness value t of the second unknown object Y Y On this basis, see Figure 4 FIG. 1 is a flow chart of the object detection method, which may include:

[0147] Step 401: Obtain a target X-ray intensity value of an object to be detected collected by an X-ray detector. The object to be detected is an object formed by superimposing a first unknown object X and a second unknown object Y.

[0148] Step 402: Query the acquired information table through the target X-ray intensity value to obtain the first mass thickness value of the first base material and the second mass thickness value of the second base material.

[0149] Step 403: Determine the first type parameter (denoted as the first type parameter a1) of the first unknown object X and the second type parameter (denoted as the second type parameter b1) of the second unknown object Y.

[0150] In one possible embodiment, when a first unknown object X and a second unknown object Y are superimposed, the material of the first unknown object is single (i.e., the type of the first unknown object can be known). Therefore, the type of the first unknown object can be measured by a method of prior measurement, and there is no limitation on this measurement method. Alternatively, the type of the first unknown object can be pre-configured. The material of the second unknown object is single (i.e., the type of the second unknown object can be known). Therefore, the type of the second unknown object can be measured by a method of prior measurement. Alternatively, the type of the second unknown object can be pre-configured.

[0151] For example, in scenarios where the relative content of two objects that cannot be mixed evenly is determined, such as in food testing, it is necessary to determine information such as the size of bones and the proportion of meat in the meat. Based on this, the meat and bones can be approximated as a single substance, that is, the meat is the first unknown object and the bones are the second unknown object. Obviously, the type of the first unknown object and the type of the second unknown object can be determined from the sample.

[0152] To sum up, the type of the first unknown object and the type of the second unknown object can be determined. The type of the first unknown object and the type of the second unknown object can be pre-configured or obtained using a certain algorithm. There is no restriction on the method of determining the type of the first unknown object and the type of the second unknown object.

[0153] Since the type and the effective atomic number have a corresponding relationship, the effective atomic number of the first unknown object can be determined based on the determined type of the first unknown object, and the effective atomic number of the second unknown object can be determined based on the determined type of the second unknown object. X1 , the first effective atomic number Z1 of the first base material and the second effective atomic number Z2 of the second base material, the first type parameter of the first unknown object can be determined. For example, the first type parameter a1 of the first unknown object can be determined using the following formula: Z X1 =a1Z1+(1-a1)Z2. Based on the effective atomic number Z of the second unknown object X2 , the first effective atomic number Z1 of the first base material and the second effective atomic number Z2 of the second base material, the second type parameter of the second unknown object can be determined. For example, the second type parameter b1 of the second unknown object can be determined using the following formula: Z X2 =b1Z1+(1-b1)Z2.

[0154] In a possible implementation, steps 301 to 304 may be used to determine a first type parameter a1 of the first unknown object and a second type parameter b1 of the second unknown object.

[0155] For example, for multiple objects to be detected, each object to be detected is composed of a first unknown object and a second unknown object superimposed on each other. That is, the first type parameter a1 of different objects to be detected is the same, and the second type parameter b1 of different objects to be detected is also the same. However, the mass and thickness values ​​of the first unknown object in different objects to be detected are different, and the mass and thickness values ​​of the second unknown object in different objects to be detected are different.

[0156] In this application scenario, for the first object to be detected, the first type parameter a1 and the second type parameter b1 can be determined using steps 301 to 304. For the second and subsequent objects to be detected, the first type parameter a1 and the second type parameter b1 of the first object to be detected are directly used, without repeatedly determining the first type parameter a1 and the second type parameter b1 of the objects to be detected.

[0157] Step 404: Determine the mass thickness value of the first unknown object and the mass thickness value of the second unknown object based on the first mass thickness value of the first base material, the second mass thickness value of the second base material, the first type parameter of the first unknown object, and the second type parameter of the second unknown object.

[0158] For example, formula (13) can be used to determine the mass thickness value of the first unknown object and the mass thickness value of the second unknown object. In formula (13), t1 represents the first mass thickness value, t2 represents the second mass thickness value, a1 represents the first type parameter of the first unknown object, and b1 represents the second type parameter of the second unknown object. Obviously, the above four parameters are known parameters. In addition, t X Indicates the mass and thickness of the first unknown object, t Y Represents the mass thickness value of the second unknown object, and the above two parameters are unknown parameters. Based on the above four known parameters, the two unknown parameters are solved by formula (13), thus obtaining t X and t Y .

[0159] For example, after obtaining the mass thickness value t of the first unknown object X and the mass and thickness of the second unknown object t Y Afterwards, the mass thickness value t X and mass thickness value t Y For example, fat and lean meat are unevenly stacked together, and the mass thickness value of fat is obtained. X and the mass thickness of lean meat t Y Afterwards, by (t X +t Y ) Determine the total weight of the object to be detected by t X / (t X +t Y ) Determine the fat rate of the object to be detected, and use t Y / (t X +t Y ) Determine the lean meat percentage of the object to be tested and thus grade the food.

[0160] Under the above technical concept, an object detection method is proposed in an embodiment of the present application. Based on the first mass thickness value and the second mass thickness value, if the third attribute information of the first unknown object and the fourth attribute information of the second unknown object are known, the fifth attribute information of the first unknown object and the sixth attribute information of the second unknown object are determined. In this example, the third attribute information may include the first type parameter of the first unknown object, the fourth attribute information may include the mass thickness value of the second unknown object, the fifth attribute information may include the mass thickness value of the first unknown object, and the sixth attribute information may include the second type parameter of the second unknown object. Based on this, if the first type parameter a1 of the first unknown object X and the mass thickness value t of the second unknown object Y are known Y Then we can solve the mass and thickness value t of the first unknown object X X and a second type parameter b1 of the second unknown object Y. On this basis, the object detection method may include:

[0161] A target X-ray intensity value of an object to be detected collected by an X-ray detector is obtained, where the object to be detected is an object formed by superimposing a first unknown object X and a second unknown object Y.

[0162] The acquired information table is queried through the target X-ray intensity value to obtain a first mass thickness value of the first base material and a second mass thickness value of the second base material.

[0163] Determine the first type parameter a1 of the first unknown object X and the mass thickness value t of the second unknown object Y Y How to determine the first type parameter a1 of the first unknown object X and the mass thickness value t of the second unknown object Y Y , there is no limitation in this embodiment, and it is sufficient to obtain the above two parameters.

[0164] Based on the first mass thickness value of the first base material, the second mass thickness value of the second base material, the first type parameter a1 of the first unknown object X, and the mass thickness value t of the second unknown object Y Y , determine the mass and thickness value t of the first unknown object X X and the second type parameter b1 of the second unknown object Y. For example, the mass thickness value t of the first unknown object X can be determined using formula (13): X And the second type parameter b1 of the second unknown object Y.

[0165] As can be seen from the above technical solutions, in the embodiments of the present application, it is possible to detect the object to be detected based on the first mass thickness value of the first base material and the second mass thickness value of the second base material, thereby improving detection accuracy and avoiding problems such as detection errors. When two objects are superimposed together, it is also possible to identify the superimposed objects and perform non-invasive detection based on X-rays, thereby realizing the identification of the material type (i.e., determining the type of the unknown object) and the quantitative analysis of the material composition (i.e., determining the mass thickness value of the unknown object). Dual-energy X-ray imaging technology is used to realize material identification, which is used for the identification of material types, the quantitative analysis of material composition, etc., and a material identification method when objects are superimposed under X-rays is provided, which has a good effect on material classification, discrimination, and quantitative calculation.

[0166] Based on the same application concept as the above method, an object detection device is proposed in the embodiment of the present application. Figure 5 FIG. 1 is a schematic diagram of the structure of the object detection device, which may include:

[0167] An acquisition module 51 is configured to acquire a target X-ray intensity value of an object to be detected collected by an X-ray detector; wherein the object to be detected is an object formed by superimposing a first unknown object and a second unknown object;

[0168] a query module 52 configured to query the acquired information table using the target X-ray intensity value to obtain a first mass thickness value of the first base material and a second mass thickness value of the second base material; wherein the mass thickness value is a product of thickness and density; wherein the information table includes a correspondence between the sample X-ray intensity value, the mass thickness value of the first base material, and the mass thickness value of the second base material; wherein the first base material and the second base material are materials with known effective atomic numbers, and the effective atomic numbers of the first unknown object and the second unknown object are within a range of the effective atomic numbers of the first base material and the second base material;

[0169] a determination module 53, configured to determine second attribute information of the second unknown object based on the first mass thickness value and the second mass thickness value, and the first attribute information of the first unknown object;

[0170] Alternatively, based on the first mass thickness value and the second mass thickness value, as well as the third attribute information of the first unknown object and the fourth attribute information of the second unknown object, the fifth attribute information of the first unknown object and the sixth attribute information of the second unknown object are determined.

[0171] Exemplarily, the first attribute information includes a first type parameter of the first unknown object and a mass thickness value of the first unknown object, and the second attribute information includes a second type parameter of the second unknown object, or the second attribute information includes a second type parameter of the second unknown object and a mass thickness value of the second unknown object; wherein the first type parameter is used to identify the type of the first unknown object; and the second type parameter is used to identify the type of the second unknown object.

[0172] Exemplarily, the first unknown object and the second unknown object have overlapping areas and non-overlapping areas, and the target X-ray intensity value is the X-ray intensity value of the overlapping area; the acquisition module 51 is also used to obtain the X-ray intensity value of the non-overlapping area collected by the X-ray detector; wherein the non-overlapping area is the area where the first unknown object itself is located; the determination module 53 is also used to determine the first type parameter of the first unknown object and the mass thickness value of the first unknown object based on the X-ray intensity value of the non-overlapping area, the acquired first mass attenuation coefficient of the first base material, and the acquired second mass attenuation coefficient of the second base material.

[0173] Exemplarily, the third attribute information includes the mass thickness value of the first unknown object, the fourth attribute information includes the mass thickness value of the second unknown object, the fifth attribute information includes the first type parameter of the first unknown object, and the sixth attribute information includes the second type parameter of the second unknown object; or, the third attribute information includes the first type parameter of the first unknown object, the fourth attribute information includes the second type parameter of the second unknown object, the fifth attribute information includes the mass thickness value of the first unknown object, and the sixth attribute information includes the mass thickness value of the second unknown object; or, the third attribute information includes the first type parameter of the first unknown object, the fourth attribute information includes the mass thickness value of the second unknown object, the fifth attribute information includes the mass thickness value of the first unknown object, and the sixth attribute information includes the second type parameter of the second unknown object.

[0174] Exemplarily, the determination module 53 is further used to determine the effective atomic number of the first unknown object based on the determined type of the first unknown object; determine the first type parameter of the first unknown object based on the effective atomic number of the first unknown object, the first effective atomic number of the first base material, and the second effective atomic number of the second base material; in addition, the determination module 53 is further used to determine the effective atomic number of the second unknown object based on the determined type of the second unknown object; determine the second type parameter of the second unknown object based on the effective atomic number of the second unknown object, the first effective atomic number of the first base material, and the second effective atomic number of the second base material.

[0175] Exemplarily, the determination module 53 is further used to determine the effective atomic number of the first unknown object based on the first effective atomic number of the first base material, the second effective atomic number of the second base material and the first type parameter, and determine the type of the first unknown object based on the effective atomic number of the first unknown object; determine the effective atomic number of the second unknown object based on the first effective atomic number of the first base material, the second effective atomic number of the second base material and the second type parameter, and determine the type of the second unknown object based on the effective atomic number of the second unknown object.

[0176] Exemplarily, the effective atomic number of the first unknown object and the first type parameter satisfy the following expression relationship: X1 =a1Z1+(1-a1)Z2; the effective atomic number of the second unknown object and the second type parameter satisfy the following expression relationship: Z X2 =b1Z1+(1-b1)Z2;

[0177] Among them, Z X1 The effective atomic number of the first unknown object, Z X2 Used to represent the effective atomic number of the second unknown object, a1 represents the first type parameter, b1 represents the second type parameter, Z1 represents the first effective atomic number, and Z2 represents the second effective atomic number.

[0178] Exemplarily, the first mass thickness value, the second mass thickness value, the first type parameter of the first unknown object, the second type parameter of the second unknown object, the mass thickness value of the first unknown object, and the mass thickness value of the second unknown object satisfy the following expression relationship:

[0179] t1=a1t X +b1t Y , t2=(1-a1)t X +(1-b1)t Y;

[0180] Wherein, t1 represents the first mass thickness value, t2 represents the second mass thickness value; a1 represents the first type parameter of the first unknown object, b1 represents the second type parameter of the second unknown object; t X Indicates the mass and thickness of the first unknown object, t Y Indicates the mass and thickness of the second unknown object.

[0181] Based on the same application concept as the above method, an electronic device is proposed in the embodiment of the present application, see Figure 6 As shown, the electronic device includes: a processor 61 and a machine-readable storage medium 62, the machine-readable storage medium 62 storing machine-executable instructions that can be executed by the processor 61; the processor 61 is used to execute the machine-executable instructions to implement the object detection method disclosed in the above example of this application.

[0182] Based on the same application concept as the above method, an embodiment of the present application also provides a machine-readable storage medium, on which a number of computer instructions are stored. When the computer instructions are executed by a processor, the object detection method disclosed in the above example of the present application can be implemented.

[0183] The machine-readable storage medium may be any electronic, magnetic, optical, or other physical storage device that may contain or store information, such as executable instructions, data, and the like. For example, the machine-readable storage medium may be: RAM (Random Access Memory), volatile memory, non-volatile memory, flash memory, a storage drive (such as a hard disk drive), a solid-state drive, any type of storage disk (such as a CD, DVD, etc.), or similar storage media, or a combination thereof.

[0184] Based on the same application concept as the above method, an embodiment of the present application further provides a computer program product, which may include a computer program. When the computer program is executed by a processor, it implements the object detection method disclosed in the above example of the present application.

[0185] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the embodiments of the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0186] The foregoing is merely an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. An object detection method, characterized in that: The method comprises: Obtaining a target X-ray intensity value of an object to be detected collected by an X-ray detector; wherein the object to be detected is an object formed by superimposing a first unknown object and a second unknown object; querying the acquired information table using the target X-ray intensity value to obtain a first mass thickness value of the first base material and a second mass thickness value of the second base material; wherein the mass thickness value is a product value of thickness and density; wherein the information table includes a correspondence between the sample X-ray intensity value, the mass thickness value of the first base material, and the mass thickness value of the second base material; wherein the first base material and the second base material are materials with known effective atomic numbers, and the effective atomic numbers of the first unknown object and the second unknown object are within the effective atomic number range of the first base material and the second base material; determining second attribute information of the second unknown object based on the first mass thickness value and the second mass thickness value, and the first attribute information of the first unknown object; Alternatively, based on the first mass thickness value and the second mass thickness value, as well as the third attribute information of the first unknown object and the fourth attribute information of the second unknown object, the fifth attribute information of the first unknown object and the sixth attribute information of the second unknown object are determined.

2. The method according to claim 1, characterized in that The first attribute information includes a first type parameter of the first unknown object and a mass and thickness value of the first unknown object, and the second attribute information includes a second type parameter of the second unknown object, or the second attribute information includes a second type parameter of the second unknown object and a mass and thickness value of the second unknown object; Wherein, the first type parameter is used to identify the type of the first unknown object; The second type parameter is used to identify the type of the second unknown object.

3. The method according to claim 2, characterized in that The first unknown object and the second unknown object have an overlapping area and a non-overlapping area, and the target X-ray intensity value is the X-ray intensity value of the overlapping area; before determining the second attribute information of the second unknown object based on the first mass thickness value and the second mass thickness value and the first attribute information of the first unknown object, the method further includes: Acquiring an X-ray intensity value of the non-overlapping area collected by the X-ray detector; wherein the non-overlapping area is the area where the first unknown object itself is located; Based on the X-ray intensity value of the non-overlapping area, the acquired first mass attenuation coefficient of the first base material and the acquired second mass attenuation coefficient of the second base material, the first type parameter of the first unknown object and the mass thickness value of the first unknown object are determined.

4. The method according to claim 1, wherein The third attribute information includes the mass and thickness value of the first unknown object, the fourth attribute information includes the mass and thickness value of the second unknown object, the fifth attribute information includes the first type parameter of the first unknown object, and the sixth attribute information includes the second type parameter of the second unknown object; Alternatively, the third attribute information includes a first type parameter of the first unknown object, the fourth attribute information includes a second type parameter of the second unknown object, the fifth attribute information includes a mass and thickness value of the first unknown object, and the sixth attribute information includes a mass and thickness value of the second unknown object; Alternatively, the third attribute information includes the first type parameter of the first unknown object, the fourth attribute information includes the mass thickness value of the second unknown object, the fifth attribute information includes the mass thickness value of the first unknown object, and the sixth attribute information includes the second type parameter of the second unknown object.

5. The method according to claim 4, characterized in that The method further comprises: determining an effective atomic number of the first unknown object based on the determined type of the first unknown object; determining a first type parameter of the first unknown object based on the effective atomic number of the first unknown object, a first effective atomic number of the first base material, and a second effective atomic number of the second base material; Determine the effective atomic number of the second unknown object based on the determined type of the second unknown object; determine the second type parameter of the second unknown object based on the effective atomic number of the second unknown object, the first effective atomic number of the first base material, and the second effective atomic number of the second base material.

6. The method according to claim 4, characterized in that The method further comprises: determining an effective atomic number of the first unknown object based on a first effective atomic number of the first base material, a second effective atomic number of the second base material, and the first type parameter, and determining a type of the first unknown object based on the effective atomic number of the first unknown object; The effective atomic number of the second unknown object is determined based on the first effective atomic number of the first base material, the second effective atomic number of the second base material and the second type parameter, and the type of the second unknown object is determined based on the effective atomic number of the second unknown object.

7. The method according to claim 5 or 6, characterized in that The effective atomic number of the first unknown object and the first type parameter satisfy the following expression relationship: X1 =a1Z1+(1-a1)Z2; the effective atomic number of the second unknown object and the second type parameter satisfy the following expression relationship: Z X2 =b1Z1+(1-b1)Z2; Among them, Z X1 The effective atomic number of the first unknown object, Z X2 Used to represent the effective atomic number of the second unknown object, a1 represents the first type parameter, b1 represents the second type parameter, Z1 represents the first effective atomic number, and Z2 represents the second effective atomic number.

8. The method according to claim 2 or 4, characterized in that The first mass thickness value, the second mass thickness value, the first type parameter of the first unknown object, the second type parameter of the second unknown object, the mass thickness value of the first unknown object, and the mass thickness value of the second unknown object satisfy the following expression relationship: t1=a1t X +b1t Y ,t2=(1-a1)t X +(1-b1)t Y ; Wherein, t1 represents the first mass thickness value, t2 represents the second mass thickness value; a1 represents the first type parameter of the first unknown object, b1 represents the second type parameter of the second unknown object; t X Indicates the mass and thickness of the first unknown object, t Y Indicates the mass and thickness of the second unknown object.

9. An object detection device, characterized in that: The device comprises: an acquisition module, configured to acquire a target X-ray intensity value of an object to be detected collected by the X-ray detector; wherein the object to be detected is an object formed by superimposing a first unknown object and a second unknown object; a query module, configured to query the acquired information table using the target X-ray intensity value to obtain a first mass thickness value of the first base material and a second mass thickness value of the second base material; wherein the mass thickness value is a product value of thickness and density; wherein the information table includes a correspondence between the sample X-ray intensity value, the mass thickness value of the first base material, and the mass thickness value of the second base material; wherein the first base material and the second base material are materials with known effective atomic numbers, and the effective atomic numbers of the first unknown object and the second unknown object are within a range of the effective atomic numbers of the first base material and the second base material; a determining module, configured to determine second attribute information of the second unknown object based on the first mass thickness value and the second mass thickness value, and the first attribute information of the first unknown object; Alternatively, based on the first mass thickness value and the second mass thickness value, as well as the third attribute information of the first unknown object and the fourth attribute information of the second unknown object, the fifth attribute information of the first unknown object and the sixth attribute information of the second unknown object are determined.

10. An electronic device, characterized in that: include: a processor and a machine-readable storage medium storing machine-executable instructions capable of being executed by the processor; The processor is configured to execute machine-executable instructions to implement the method according to any one of claims 1 to 8.

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