Image data generation method and inspection device

Abstract

Provided is an image data generation method that can reduce interference between cross-sectional image data generated by filtering in filtered back projection, and an inspection device in which this image data generation method is implemented. [Solution] The image data generation method for generating three-dimensional image data of the object to be inspected 12 using at least two pieces of transmission image data acquired by changing the relative positions of the radiation generator 22, the detector 26, and the holder 24 that holds the object to be inspected 12 includes a first step of correcting pixel values ​​in at least a portion of the transmission image data in accordance with an offset value, a second step of performing a predetermined filtering process on the corrected transmission image data, and a third step of generating three-dimensional image data from the filtered transmission image data using a back projection method.

Description

[Technical Field]

[0001] The present invention relates to an image data generating method and an inspection device. [Background technology]

[0002] In electronic circuit boards, the connection state between electronic components (e.g., pins) and the wiring on the board by solder (hereinafter referred to as "solder joint state") is difficult to determine by visual inspection, so a tomosynthesis X-ray inspection device is used. Specifically, the device is configured to rotate and move the object to be inspected (electronic circuit board) and detector held by a holder within the beam of X-rays emitted from a light source, acquire transmitted image data, and generate 3D image data.

[0003] Back projection is used to generate three-dimensional image data (cross-sectional image data) from transmitted image data. However, simply generating three-dimensional image data (cross-sectional image data) using back projection results in an unclear image. Therefore, filtering (edge ​​enhancement) is performed on the transmitted image data, and then the three-dimensional image data (cross-sectional image data) is generated using back projection (this method is called the "Filtered-Backprojection (FBP) method").

[0004] When three-dimensional image data (cross-sectional image data) is generated using the FBP method, edges of voids (air bubbles in solder joints) are emphasized to make the image clearer, but as a result, edge images may be formed on cross sections where the voids do not actually exist. In order to remove such unwanted images, a method of applying a filter in frequency space has been proposed (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Publication No. 2020-065614 Summary of the Invention [Problem to be solved by the invention]

[0006] However, the location where voids and other defects occur within a solder joint varies for each test piece, and there was a problem in that it was difficult to remove in frequency space only the portion of the image of the void edge that is formed on a cross section where it does not actually exist.

[0007] The present invention has been made in consideration of such problems, and aims to provide an image data generation method that can reduce interference between cross-sectional image data that occurs due to filtering processing by performing a correction on each pixel in at least a portion of the transmitted image data by increasing or decreasing the pixel value based on predetermined conditions before performing filtering processing (edge ​​enhancement processing) in the filtered back projection method, and an inspection device in which this image data generation method is implemented. [Means for solving the problem]

[0008] In order to solve the above problem, the image data generating method of the present invention is an image data generating method that generates three-dimensional image data of the object under test by changing the relative positions of a light source, a detector, and a holding unit that holds the object under test, and using at least two pieces of transmission image data of the object under test, which light emitted from the light source and transmitted through the object under test is acquired by the detector, and the method comprises the following steps: a first step of correcting, for each pixel in at least a part of the transmission image data, a difference between the pixel value and the predetermined value when the pixel value exceeds a predetermined value and the predetermined value is reduced in accordance with the predetermined value, or a first step of correcting, for each pixel in at least a part of the transmission image data, a difference between the pixel value and the predetermined value and the predetermined value is reduced in accordance with the predetermined value when the pixel value is below the predetermined value and the predetermined value is increased in accordance with the predetermined value; a second step of performing a predetermined filtering process on the corrected transmission image data; and a third step of generating the three-dimensional image data from the filtered transmission image data using a back projection method.

[0009] Furthermore, in the image data generating method according to the present invention, it is preferable that the first step comprises: step 1-1 of performing the correction on each pixel in at least a portion of the area of ​​the transmitted image data; step 1-2 of calculating a difference for each pixel between the transmitted image data and the transmitted image data corrected in step 1-1; step 1-3 of averaging the differences for each pixel calculated in step 1-2; step 1-4 of calculating, for each pixel, the difference between the differences for each pixel calculated in step 1-2 and the differences for each pixel averaged in step 1-3; and step 1-5 of adding the minute variation information to the value of each pixel of the transmitted image data corrected in step 1-1 when the minute variation information satisfies a predetermined condition.

[0010] In the image data generating method according to the present invention, it is preferable that the first step repeats the correction by changing the predetermined value.

[0011] In the image data generating method according to the present invention, it is preferable that the first step performs correction for each pixel of the transmission image data using the following equation: When Voc < Vc(x,y) V′(x,y) = Vo+(V(x,y)-Vo)×β When V(x,y) ≦ Vo V′(x,y) = V(x,y) however, V(x, y): the value of the pixel at the position (x, y) in the transmission image data V'(x,y): the value of the pixel at position (x,y) in the transmission image data offset by the predetermined value Vo: the predetermined value Vmax: the maximum value of the pixel β: correction coefficient

[0012] In the image data generating method according to the present invention, the first step converts the predetermined value into a complement using the following formula: Voc = Vmax-Vo however, Vo: the predetermined value Voc: the predetermined value converted to its complement Vmax: the maximum value of the pixel For each pixel of the transmitted image data, convert the value of the pixel into a complement using the following formula: Vc(x,y) = Vmax-V(x,y) however, V(x, y): the value of the pixel at the position (x, y) in the transmission image data Vc(x,y): the complemented pixel value at position (x,y) in the transmission image data Vmax: the maximum value of the pixel Correct each pixel of the transmission image data converted into its complement using the following formula: When Voc < Vc(x,y) Vc′(x,y) = Voc+(Vc(x,y)-Voc)×β When Vc(x,y) ≦ Voc Vc′(x,y) = Vc(x,y) however, Vc(x,y): the complemented pixel value at position (x,y) in the transmission image data Vc'(x, y): a value obtained by offsetting the value of the pixel converted to its complement at the position (x, y) in the transmission image data by the predetermined value converted to its complement Voc: the predetermined value converted to its complement Vmax: the maximum value of the pixel β: correction coefficient It is desirable to convert the value of each pixel of the corrected transmitted image data into a complement using the following formula: V′(x,y) = Vmax-Vc′(x,y) however, Vc'(x, y): A value obtained by offsetting the value converted to the complement of the pixel at the position (x, y) in the transmission image data by the predetermined value converted to the complement. V'(x,y): the value of the pixel at position (x,y) in the transmission image data offset by the predetermined value Vmax: the maximum value of the pixel

[0013] In addition, the inspection device of the present invention includes a light source, a detector, a holding unit that holds an object under inspection, and a control unit that changes the relative positions of the light source, the detector, and the holding unit, and generates three-dimensional image data of the object under inspection using at least two pieces of transmission image data of the object under inspection, obtained by the detector using light emitted from the light source and transmitted through the object under inspection, and the control unit generates the three-dimensional image using any of the image data generation methods described above. [Effects of the Invention]

[0014] According to the image generation method and inspection device of the present invention, when generating three-dimensional image data (cross-sectional image data) from transmission image data using the filtered back projection method, before performing the filtering process (edge ​​enhancement process), a correction is performed on each pixel in at least a portion of the transmission image data to increase or decrease the value of the pixel based on predetermined conditions, thereby reducing interference between cross-sectional image data that occurs due to the filtering process. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is an explanatory diagram for explaining a configuration of an inspection device according to an embodiment of the present invention. [Figure 2] FIG. 2 is an explanatory diagram for explaining each functional block of a control unit of the inspection device. [Figure 3] 4 is a flowchart for explaining an inspection process in the inspection device. [Figure 4] 10 is a flowchart for explaining a transmission image capturing and reconstruction image generating process in the inspection process. [Figure 5]10 is a flowchart for explaining the reconstructed image generating process and offset processing in the transmission image capturing and reconstructed image generating process. [Figure 6] 10A and 10B are explanatory diagrams for explaining the relationship between differences in edge height and reconstructed image data generated by filtered back projection. [Figure 7] FIG. 10 is an explanatory diagram for explaining offset processing. [Figure 8] 10 is a flowchart for explaining a reconstructed image generating process in a first modified example. [Figure 9] FIG. 10 is an explanatory diagram for explaining offset processing in the first modified example. [Figure 10] 10 is a flowchart for explaining a reconstructed image generating process in a second modified example. [Figure 11] FIG. 10 is an explanatory diagram for explaining offset processing in a second modified example. DETAILED DESCRIPTION OF THE INVENTION

[0016] A preferred embodiment of the present invention will now be described with reference to the drawings. As shown in Fig. 1, an examination device 1 according to this embodiment includes a control unit 10, which is configured as a processing device such as a personal computer (PC), a monitor 11, and an imaging unit 32. The imaging unit 32 further includes a radiation quality changing unit 14, a radiation generator driving unit 16, a holder driving unit 18, a detector driving unit 20, a radiation generator 22, a holder 24, and a detector 26.

[0017] The radiation generator 22 is a device (ray source) that generates radiation such as X-rays, and generates radiation by, for example, colliding accelerated electrons with a target such as tungsten or diamond. Note that, although the radiation in this embodiment is described as X-rays, the radiation is not limited to this. For example, the radiation may be alpha rays, beta rays, gamma rays, ultraviolet rays, visible light, or infrared rays. The radiation may also be microwaves or terahertz waves.

[0018] The holder 24 holds an electronic board, which is the object under inspection 12. The object under inspection 12 held by the holder 24 is irradiated with radiation generated by the radiation generator 22, and the radiation that has passed through the object under inspection 12 is detected by the detector 26 to capture an image (acquire as image data). Hereinafter, data of the radiographic image of the object under inspection 12 captured by the detector 26 will be referred to as "transmission image data." As will be described later, in this embodiment, the detector 26 and the holder 24 that holds the electronic board, which is the object under inspection 12, are moved relative to the radiation generator 22 to acquire multiple pieces of transmission image data, and reconstructed image data (cross-sectional image data), which is three-dimensional image data, is generated from the transmission image data.

[0019] The transmission image data captured by the detector 26 is sent to the control unit 10, where it is reconstructed into image data including the three-dimensional shape of the solder at the joint using a known technique such as the filtered backprojection (FBP) method. The reconstructed image data and transmission image data are then stored in a storage unit within the control unit 10 (for example, a storage unit 34, which will be described later) or in an external storage unit (not shown). Hereinafter, image data obtained by extracting one cross section of the three-dimensional shape calculated based on the transmission image data will be referred to as "cross-sectional image data." Furthermore, a set of one or more cross-sectional image data will be referred to as "three-dimensional image data" or "reconstructed image data." In other words, image data obtained by cutting out an arbitrary cross section from the three-dimensional image data (reconstructed image data) is cross-sectional image data. Such reconstructed image data and cross-sectional image data are output to the monitor 11. Note that the monitor 11 displays not only the reconstructed image data and cross-sectional image data, but also the inspection results of the solder joint state, which will be described later. Hereinafter, the reconstructed image data in this embodiment is also referred to as "planar CT" because it is reconstructed from planar image data (transmission image data) captured by the detector 26, as described above.

[0020] The radiation quality changing unit 14 changes the radiation quality of the radiation generated by the radiation generator 22. The radiation quality is determined by a voltage (hereinafter referred to as "tube voltage") applied to accelerate electrons to be bombarded with a target, and a current (hereinafter referred to as "tube current") that determines the number of electrons. The radiation quality changing unit 14 is a device that controls the tube voltage and tube current. This radiation quality changing unit 14 can be realized using known technology such as a transformer or a rectifier.

[0021] The quality of radiation is determined by its brightness and wavelength (spectral distribution). Increasing the tube current increases the number of electrons colliding with the target and the number of radiation photons generated. As a result, the brightness of the radiation increases. For example, some components, such as capacitors, are thicker than other components, and high-brightness radiation must be irradiated to capture transmission images of these components. In such cases, the brightness of the radiation can be adjusted by adjusting the tube current. Furthermore, increasing the tube voltage increases the energy of the electrons colliding with the target, thereby increasing the energy (spectrum) of the generated radiation. Generally, the higher the energy of radiation, the greater its penetration power into materials and the less it is absorbed by them. Transmission images captured using such radiation have lower contrast. Therefore, the tube voltage can be used to adjust the contrast of transmission images.

[0022] The inspection device 1 is configured to capture a transmission image of the inspected object 12 and acquire transmission image data by changing the relative positions of the radiation generator 22, which is a light source, the holder 24 that holds the inspected object 12, and the detector 26, and detecting with the detector 26 the radiation emitted from the radiation generator 22 and transmitted through the inspected object 12. Here, however, the description will be based on a configuration in which the inspected object 12 held by the holder 24 is rotationally moved within the beam of radiation emitted from the radiation generator 22 along a rotational orbit (substrate rotational orbit 28) on a substrate rotational orbit plane that is a plane perpendicular to the axis A, and the detector 26 is rotationally moved along a rotational orbit (detector rotational orbit 30) on a detector rotational orbit plane that is different from the substrate rotational orbit plane, thereby detecting the radiation that has transmitted through the inspected object 12 and capturing a transmission image of the inspected object 12 and acquiring transmission image data. However, the present invention is not limited to this configuration. For example, the transmission image data may be acquired by rotating the radiation generator 22 and the detector 26 relative to the holder 24 that holds the object under inspection 12, or by rotating the radiation generator 22 and the holder 24 that holds the object under inspection 12 relative to the detector 26. Furthermore, the transmission image data may be acquired by moving any of the radiation generator 22, the holder 24 that holds the object under inspection 12, and the detector 26 in a straight line rather than by rotating them.

[0023] The radiation generator driving unit 16 has a driving mechanism such as a motor (not shown), and can move the radiation generator 22 up and down along an axis A passing through its focal point (an axis (optical axis) passing through the center of the radiation direction of the radiation emitted from the radiation generator 22, the direction of this axis being referred to as the "Z-axis direction"). This makes it possible to change the distance between the radiation generator 22 and the object under test (electronic board) 12 held by the holder 24, thereby changing the irradiation field and changing the magnification ratio of the transmitted image captured by the detector 26. The position of the radiation generator 22 in the Z-axis direction is detected by a generator position detection unit (not shown), and output to the control unit 10.

[0024] The detector driver 20 also has a drive mechanism such as a motor (not shown) and rotates the detector 26 along the detector rotation orbit 30. The holder driver 18 also has a drive mechanism such as a motor (not shown) and rotates the holder 24 along the substrate rotation orbit 28, thereby moving the holder 24 in parallel with the detector 26. The holder 24 is configured to rotate on the substrate rotation orbit 28 in conjunction with the rotation of the detector 26. This makes it possible to acquire multiple pieces of transmission image data with different projection directions and projection angles while changing the relative positional relationship between the object under test 12 held by the holder 24 and the radiation generator 22. In the inspection apparatus 1 according to this embodiment, the area on the object under test 12 from which transmission image data can be acquired is determined by the size of the radiation detection area of ​​the detector 26 and the relative positions of the radiation generator 22, the object under test 12 (holder 24), and the detector 26. This area from which transmission image data can be acquired is called the "FOV (field of view)."

[0025] The rotation radii of the substrate rotation orbit 28 and the detector rotation orbit 30 are not fixed but can be freely changed. This makes it possible to arbitrarily change the irradiation angle of the radiation irradiated onto the electronic substrate, which is the inspected object 12, and onto the components attached to this substrate. The orbital planes of the substrate rotation orbit 28 and the detector rotation orbit 30 are perpendicular to the Z-axis direction described above. If the directions perpendicular to this orbital plane are the X-axis direction and the Y-axis direction, the positions of the holder 24 in the X-axis direction and the Y-axis direction are detected by a substrate position detection unit (not shown) and output to the control unit 10, and the positions of the detector 26 in the X-axis direction and the Y-axis direction are detected by a detector position detection unit (not shown) and output to the control unit 10.

[0026] The control unit 10 controls all operations of the above-mentioned inspection device 1. The main functions of the control unit 10 will be described below with reference to Fig. 2. Although not shown, input devices such as a keyboard and a mouse are connected to the control unit 10.

[0027] The control unit 10 includes a storage unit 34, an imaging processing unit 35, a cross-sectional image generating unit 36, a substrate inspection surface detecting unit 38, a pseudo-cross-sectional image generating unit 40, and an inspection unit 42. Although not shown, the imaging processing unit 35 of the control unit 10 also has the function of an imaging control unit that controls the operation of the radiation quality changing unit 14, the radiation generator driving unit 16, the holder driving unit 18, and the detector driving unit 20. Furthermore, each of these functional blocks is realized by the cooperation of hardware, such as a CPU that performs various arithmetic processing and RAM that is used as a work area for storing data and executing programs, and software. Therefore, these functional blocks can be realized in various ways by combining hardware and software.

[0028] The storage unit 34 stores information such as imaging conditions for imaging the electronic board and acquiring transmission image data, and the design of the electronic board as the inspected object. The storage unit 34 also stores transmission image data and reconstructed image data (cross-sectional image data, pseudo-cross-sectional image data) of the electronic board, as well as inspection results of the inspection unit 42 (described later). The storage unit 34 also stores information for driving the radiation generator driving unit 16, the holder driving unit 18, and the detector driving unit 20 (for example, the speed at which the radiation generator driving unit 16 drives the radiation generator 22, the speed at which the holder driving unit 18 drives the holder 24, and the speed at which the detector driving unit 20 drives the detector 26, the position at which the transmission image data is acquired, etc.).

[0029] In order to generate reconstructed image data (cross-sectional image data) by a cross-sectional image generating unit 36, which will be described later, the imaging processing unit 35 drives the radiation generator 22, the holder 24, and the detector 26 using the radiation generator driving unit 16, the holder driving unit 18, and the detector driving unit 20, and captures an image of the inspected object 12 held by the holder 24 to obtain transmission image data. A method for obtaining transmission image data by the imaging processing unit 35 will be described later.

[0030] The cross-sectional image generating unit 36 ​​generates cross-sectional image data (reconstructed image data) based on the multiple transmission image data acquired from the storage unit 34. This can be achieved using known techniques, such as the FBP method or the maximum likelihood estimation method. Different reconstruction algorithms result in different properties of the reconstructed image and different times required for reconstruction. Therefore, multiple reconstruction algorithms and parameters used for the algorithms may be prepared in advance and the user may select one. This provides the user with the freedom of choice, such as prioritizing a shorter reconstruction time or prioritizing better image quality even if it takes longer. Each of the generated cross-sectional images is output as cross-sectional image data to the storage unit 34 along with attribute information, such as information determining the position of each cross-sectional image in the Z-axis direction and the positions (coordinates) of pixels in the X-axis and Y-axis directions, and is stored in the storage unit 34. A method for generating reconstructed image data (cross-sectional image data) by the cross-sectional image generating unit 36 ​​will be described later.

[0031] The substrate inspection surface detection unit 38 identifies an image (cross-sectional image data) that shows the surface to be inspected on the electronic substrate (for example, the surface of the electronic substrate) from the multiple cross-sectional image data generated by the cross-sectional image generation unit 36. Hereinafter, the cross-sectional image data that shows the inspection surface of the electronic substrate will be referred to as "inspection surface image data."

[0032] The pseudo-sectional image generating unit 40 stacks a predetermined number of consecutive cross-sectional image data from the cross-sectional image data generated by the cross-sectional image generating unit 36 ​​to image regions of the substrate that are thicker than each cross-sectional image data. The number of cross-sectional image data to be stacked is determined based on the thickness of the substrate region depicted by the cross-sectional image data (hereinafter referred to as the "slice thickness") and the slice thickness of the pseudo-sectional image data. For example, if the slice thickness of the cross-sectional image data is 50 μm and the height (e.g., 500 μm) of a BGA solder ball (hereinafter simply referred to as "solder") is to be used as the slice thickness for the pseudo-sectional image data, then 500 / 50 = 10 cross-sectional image data should be stacked. In this case, the inspection surface image data identified by the substrate inspection surface detecting unit 38 is used to identify the position of the solder.

[0033] The inspection unit 42 inspects the solder joint state based on the cross-sectional image data generated by the cross-sectional image generation unit 36, the inspection surface image data identified by the board inspection surface detection unit 38, and the pseudo cross-sectional image data generated by the pseudo cross-sectional image generation unit 40. Because the solder joining the electronic board and the component is located near the board inspection surface, it is possible to determine whether the solder is properly joining the board and the component by inspecting the inspection surface image data and the cross-sectional image data (pseudo cross-sectional image data) that shows the area on the radiation generator 22 side of the inspection surface image data.

[0034] Here, "solder joint condition" refers to whether an electronic board and a component are joined by solder and an appropriate conductive path is formed. Inspections of solder joint condition include bridge inspection, melting condition inspection, and void inspection. A "bridge" refers to an undesirable conductive path between conductors created by solder joining. Furthermore, a "melting condition" refers to whether the joint between the electronic board and the component is insufficient due to insufficient solder melting, or whether there is a so-called "floating" condition. A "void" refers to a defect in the solder joint caused by air bubbles in the solder joint. Therefore, the inspection unit 42 includes a bridge inspection unit 44, a melting condition inspection unit 46, and a void inspection unit 48.

[0035] The operations of the bridge inspection unit 44, the molten state inspection unit 46, and the void inspection unit 48 will be described in detail below, but the bridge inspection unit 44 and the void inspection unit 48 inspect bridges and voids, respectively, based on the pseudo cross-sectional image data generated by the pseudo cross-sectional image generation unit 40, and the molten state inspection unit 46 inspects the molten state of the solder based on the inspection surface image data identified by the board inspection surface detection unit 38. The inspection results of the bridge inspection unit 44, the molten state inspection unit 46, and the void inspection unit 48 are stored in the memory unit 34. The inspection contents using the reconstructed image data (cross-sectional image data) described here are merely examples, and the present invention is not limited to these inspection contents.

[0036] 3 is a flowchart showing the flow of the inspection process from capturing an image of the inspected object 12 to acquiring transmission image data, generating reconstructed image data (cross-sectional image data) based on the transmission image data, and further specifying inspection surface image data and inspecting the solder joint state. The inspection process in this flowchart starts, for example, when the control unit 10 receives an instruction to start the inspection from an input device (not shown).

[0037] When the inspection is started, the control unit 10 carries the object under inspection 12 into the inspection space in the inspection apparatus 1, as shown in FIG. 3, and holds the object under inspection 12 with the holder 24 (step S100). Next, the imaging processing unit 35 of the control unit 10 positions the ray generator 22 in the Z-axis direction using the ray generator driving unit 16, and moves the holder 24 and the detector 26 to an imaging start position, thereby setting the irradiation field of the radiation emitted from the ray generator 22 (the imaging region to which the radiation is irradiated to obtain transmission image data of the above-mentioned field of view FOV) (step S102). Note that, if there are multiple imaging regions (fields of view FOV) on the object under inspection 12, one imaging region is selected and set from among them. Then, the transmission image capturing and reconstructed image generation process is started (step S104).

[0038] 4, when the transmission image capturing / reconstruction image generating process S104 is started, the imaging processing unit 35 starts the rotational movement of the holder 24 and the detector 26, and moves the holder 24 and the detector 26 on the rotational orbits (substrate rotation orbit 28 and detector rotation orbit 30) (step S1041). Then, while the holder 24 and the detector 26 are moving on the rotational orbits 28 and 30, the imaging processing unit 35 determines whether the holder 24 and the detector 26 are at the imaging position (S1042). If it determines that the holder 24 and the detector 26 are not at the imaging position (step S1042: N), the imaging processing unit 35 repeats the determination of step S1042. On the other hand, if it determines that the holder 24 and the detector 26 are at the imaging position (step S1042: Y), the imaging processing unit 35 images the inspected object 12 with the detector 26 to obtain transmission image data, stores the data in the storage unit 33 (step S1043), and determines whether imaging has been performed at all imaging positions (step S1044). When it is determined that there is an imaging position for which transmission image data has not yet been acquired (step S1044: N), the imaging processing unit 35 returns to step S1042 and repeats the above-described process. On the other hand, when it is determined that transmission image data has been acquired at all imaging positions (step S1044: Y), the imaging processing unit 35 moves the holder 24 and the detector 26 from the rotation orbit to the retracted position and stops them (step S1045).

[0039] When the transmission image data of the object 12 is acquired in this manner, the cross-sectional image generating unit 36 ​​of the control unit 10 executes a reconstructed image generating process for generating reconstructed image data of the object 12 using the transmission image data (step S1046). As shown in FIG. 5(a), in the reconstructed image generating process S1046, the cross-sectional image generating unit 36 ​​executes an offset process on each of the transmission image data used to generate the reconstructed image data (step S1050), and executes a filter process on each of the transmission image data corrected in the offset process S1050 ("offset image data" or "corrected image data" to be described later) (step S1060). The offset process S1050 will be described in detail later. The filter process S1060 is an edge enhancement process in the frequency domain used in the FBP method, and for example, a ramp filter is used on each of the corrected transmission image data. Then, the cross-sectional image generating unit 36 ​​performs a back projection process to generate cross-sectional image data at predetermined intervals in the Z-axis direction using the edge-enhanced transmission image data, thereby generating reconstructed image data (step S1070), and ends the reconstructed image generating process S1046.Furthermore, returning to Figure 4, the transmission image capturing / reconstructed image generating process S104 is ended.

[0040] Returning to FIG. 3 , the board inspection surface detection unit 38 of the control unit 10 receives the transmission image data or reconstructed image data (cross-sectional image data) from the cross-sectional image generation unit 36 ​​and executes a board inspection surface detection process to identify an inspection surface image from the received data (step S106). The storage unit 34 pre-stores cross-sectional image data (referred to as "reference image data") of a board inspection surface of a normal object to be inspected, with no abnormalities in the solder joint state or the like. The board inspection surface detection unit 38 reads the reference image data of the current field of view (FOV) from the storage unit 34, and further reads cross-sectional image data within a search range that includes the board inspection surface from the reconstructed image data of the current field of view (the reconstructed image data generated in step S104). The board inspection surface detection unit 38 then compares the reference image data with each of the cross-sectional image data within the search range, identifies the cross-sectional image data that most closely matches the reference image data as inspection surface image data, and stores the position of the identified cross-sectional image data (inspection surface image data) in the Z-axis direction as the position of the board inspection surface within the current field of view (FOV). Here, as a method for identifying the cross-sectional image data that most closely matches the reference image data from among multiple cross-sectional image data, for example, phase-only correlation can be used, which allows the matching rate to be calculated quickly regardless of positional deviation.

[0041] Then, the pseudo cross-sectional image generating unit 40 of the control unit 10 generates pseudo cross-sectional image data from the reconstructed image data (cross-sectional image data) based on the inspection surface image data and the Z-direction position of the substrate inspection surface identified in step S106 (step S108).

[0042] Next, the bridge inspection unit 44 of the control unit 10 acquires pseudo cross-sectional image data of a slice thickness similar to that of the solder balls from the pseudo cross-sectional image generation unit 40 (read from the storage unit 34), inspects for the presence of a bridge (step S110), and determines whether a bridge is detected (step S112). If a bridge is not detected (step S112: N), the melted state inspection unit 46 of the control unit 10 acquires inspection surface image data from the substrate inspection surface detection unit 38 (read from the storage unit 34), inspects for the presence of molten solder (step S114), and determines whether a portion of molten solder is detected (step S116). If solder is present (step S116: Y), the void inspection unit 48 of the control unit 10 acquires pseudo cross-sectional images of partial images of the solder balls from the pseudo cross-sectional image generation unit 40 (read from the storage unit 34), inspects for the presence of voids (step S118), and determines whether a void is detected (step S120). If no voids are found (step S120: N), inspection unit 42 of control unit 10 determines that the solder joint state is normal and outputs a message to that effect to storage unit 34 (step S122). If a bridge is detected (step S112: Y), the solder is not melted (step S116: N), or a void is present (step S120: Y), inspection unit 42 determines that the solder joint state is abnormal and outputs a message to that effect to storage unit 34 (step S124).

[0043] When the state of the solder is output to the memory unit 34 in step S122 or step S124, the image capturing processing unit 35 of the control unit 10 determines whether or not there is a next image capturing area (field of view FOV) (step S126). If it is determined that there is a next image capturing area (the object under inspection 12 currently being inspected still has an image capturing area that has not yet been inspected) (step S126: Y), the image capturing processing unit 35 returns to step S102, sets the next image capturing area (field of view FOV), and repeats the subsequent processes. On the other hand, if it is determined that inspection of all image capturing areas (field of view FOV) has been completed (step S126: N), the control unit 10 carries the object under inspection 12 out of the inspection area of ​​the inspection device 1 (step S128), and ends the inspection process.

[0044] In the process shown in FIG. 3, the case where an inspection is performed for each of the above-mentioned imaging areas (FOVs) has been described. However, the configuration may be such that after capturing transmission image data in all imaging areas (FOVs), an inspection is performed for each imaging area (FOV), or the configuration may be such that the inspection is performed in parallel with capturing images of other imaging areas (FOVs) in order from the imaging area (FOV) for which generation of reconstructed image data (cross-sectional image data and pseudo-cross-sectional image data) has been completed.

[0045] (offset processing) As described above, the inspection apparatus 1 according to this embodiment employs the FBP (filtered back projection) method, which performs a filtering process (edge ​​enhancement process) on the transmission image data and then performs a back projection process when generating reconstructed image data (cross-sectional image data) that is three-dimensional image data from the transmission image data. FIG. 6 shows a cross-section of the substrate surface of the object under inspection 12 in the X-axis direction. FIG. 6(a) shows the cross-sectional shape of the substrate surface of the object under inspection 12, where a shallow step portion is formed upwardly and convexly. FIG. 6(b) shows image data reconstructed after performing a filtering process (edge ​​enhancement process) using the FBP method on the transmission image data capturing the step portion (actually, the image data is composed of cross-sectional image data stacked at a predetermined slice thickness in the Z-axis direction). The step region Gs shown in FIG. 6(a) is the edge. However, in the image data reconstructed by the FBP method, as shown in the region Gs′, as a result of the filtering process, the height of the low portion near the edge is emphasized lower (undershoot occurs) and the high portion is emphasized higher (overshoot occurs). Similarly, FIG. 6(c) shows a cross-sectional shape of the substrate surface of the inspection object 12, in which a deep concave hole is formed downward. When such a hole is reconstructed after performing a filter process (edge ​​enhancement process) on the transmission image data as shown in FIG. 6(d), the region Gd of the edge portion is emphasized more in the low portion near the edge, and more in the high portion near the edge, as shown in region Gd' (which results in undershoot or overshoot). The amount of this emphasis (the amount of increase or decrease in the Z-axis direction) is affected by the height of the edge: as shown in FIGS. 6(a) and 6(b), the lower the edge height (shallower), the smaller the amount of emphasis (the amount of undershoot or overshoot). As shown in FIGS. 6(c) and 6(d), the higher the edge height (deeper), the larger the amount of emphasis (the amount of undershoot or overshoot).

[0046] As described above, when the FBP method is used, filtering (edge ​​enhancement) of transmission image data enhances edges in the reconstructed image data, making the image clearer. However, as a result, as shown in FIGS. 6(b) and 6(d), a portion of the image (a portion where an undershoot or overshoot occurs) may be formed in the cross-sectional image data where the image does not exist. The transmission image data is image data obtained by detecting radiation emitted from the radiation generator 22 and transmitted through the object 12 by the detector 26. Therefore, when the height of the edge is low, as shown in FIG. 6(a), there is little difference in the amount of attenuation of the radiation transmitted around the edge and detected by the detector 26, and the difference in brightness value (contrast) is small. On the other hand, when the height of the edge is high, as shown in FIG. 6(c), the amount of attenuation of the radiation transmitted around the edge and detected by the detector 26 varies greatly depending on the transmitted portion, resulting in a large difference in brightness value (contrast). Therefore, in this embodiment, as described above, offset processing S1050 is performed on the transmission image data before filter processing (edge ​​enhancement processing) S1060 is performed, and the difference in brightness values ​​(contrast) around the edge is reduced so that the image near the edge in the reconstructed image data is not enhanced in the Z-axis direction (so as to reduce the amount of undershoot or overshoot).

[0047] The offset process S1050 shown in FIG. 5(b) is configured to select pixels with high brightness values ​​from the transmission image data and perform correction to reduce the brightness values ​​of those pixels. Specifically, the cross-sectional image generating unit 36 ​​first selects one of the transmission image data to be used for reconstruction (step S1051). The selected transmission image data is referred to as "original image data." Then, an offset process is performed to correct the value V(x,y) of each pixel in the selected original image data based on the following equation (1) (step S1052). Specifically, the pixel value V(x,y) of the original image data is compared with an offset value Vo. If the pixel value V(x,y) is greater than the offset value Vo, the pixel value is reduced to calculate a value V'(x,y). If the pixel value V(x,y) is equal to or less than the offset value Vo, V'(x,y) = V(x,y). Here, (x,y) indicates the position of the pixel in the transmission image data (here, the transmission image data refers to the original image data, but the following offset image data etc. are also managed using the same coordinates). For example, if the original image data (transparent image data) is composed of M pixels and N pixels in the X-axis direction and Y-axis direction, respectively, then x = 0 to M-1, y = 0 to N-1. Note that image data corrected to pixel value V'(x,y) is called "offset image data."

[0048] When Vo < V(x,y) V′(x,y) = Vo+(V(x,y)-Vo)×β When V(x,y) ≦ Vo V′(x,y) = V(x,y) (1) however, V(x,y): The pixel value at the position (x,y) of the original image data V'(x,y): The pixel value at the position (x,y) of the offset image data Vo: Offset value β: correction coefficient

[0049] The process using equation (1) involves reducing the portion of the pixel value that exceeds the offset value Vo by the aforementioned correction coefficient β when the value V(x, y) of a pixel in the original image data exceeds the offset value Vo. The correction coefficient β is, for example, in the range of 0<β<1. With equation (1), pixels that exceed the offset value Vo can be reduced while preserving the characteristics of the pixel value, thereby reducing the difference in value (difference in brightness, i.e., contrast) between pixels greater than the offset value Vo and pixels equal to or less than the offset value Vo.

[0050] As described above, when the original image data is converted into offset image data by applying equation (1), the contrast of pixels near the edges becomes smaller. Therefore, when the offset image data (pixel value V'(x, y)) is used to generate reconstructed image data (cross-sectional image data) using the FBP method (steps S1060, S1070), the amount of undershoot or overshoot occurring in the reconstructed image data (cross-sectional image data) can be reduced.

[0051] Furthermore, the accuracy of the reconstructed image data (cross-sectional image data) can be improved by further performing the following process: The cross-sectional image generating unit 36 ​​calculates the difference ΔV(x, y) between the values ​​of each pixel between the original image data and the offset image data based on the following equation (2) (step S1053).

[0052] ΔV(x,y) = V(x,y)-V′(x,y) (2) however, V(x,y): The pixel value at the position (x,y) of the original image data V'(x,y): The pixel value at the position (x,y) of the offset image data ΔV(x,y): Difference in value for each pixel

[0053] Furthermore, the cross-sectional image generating unit 36 ​​performs an averaging process on the difference ΔV(x,y) (step S1054). For example, a median filter process is performed on the difference ΔV(x,y). Here, the median filter process is a process in which the difference (ΔV(x,y)) of each pixel of the currently selected transmission image data is compared in magnitude with the value (difference) of surrounding pixels, and the value (difference) of the pixel is converted to the value (difference) of the median pixel. The averaged difference is represented as ΔVa(x,y).

[0054] Furthermore, the cross-sectional image generating unit 36 ​​calculates the minute fluctuation component (minute fluctuation information) d(x, y) for each pixel from the difference ΔV(x, y) and the averaged difference ΔVa(x, y) based on the following equation (3) (step S1055). Note that, as is clear from equation (2), the difference ΔV(x, y) is a positive, 0, or negative value, and therefore the minute fluctuation component d(x, y) is also a positive, 0, or negative value.

[0055] d(x,y) = ΔV(x,y)-ΔVa(x,y) (3) however, ΔV: Difference in value for each pixel ΔVa: averaged difference per pixel d(x,y): Small fluctuation component for each pixel

[0056] Then, for each pixel V'(x, y) of the offset image data, the cross-sectional image generating unit 36 ​​adds the small fluctuation component d(x, y) to pixels that satisfy the condition based on the following equation (4) (step S1056). Specifically, it is determined whether the magnitude (absolute value) of the small fluctuation component d(x, y) is smaller than a predetermined threshold TH, and if it is smaller than the predetermined threshold, the small fluctuation component d(x, y) is added to the value V'(x, y) of the pixel to obtain a value V"(x, y). Furthermore, the small fluctuation component d(x, y) is not added to pixels whose magnitude (absolute value) of the small fluctuation component d(x, y) is equal to or greater than the predetermined threshold TH, and V"(x, y) = V'(x, y). The image data corrected to the value V"(x, y) (image data to which the small fluctuation component has been added) is called "corrected image data."

[0057] When |d(x,y)| < TH V″(x,y) = V′(x,y)+d(x,y) When TH ≦ |d(x, y)| V″(x,y) = V′(x,y) (4) however, d(x,y): Small fluctuation component for each pixel TH: Threshold V'(x,y): The pixel value at the position (x,y) of the offset image data V″(x,y): The pixel value at the position (x,y) of the corrected image data

[0058] When the value V(x,y) of each pixel in the original image data is reduced based on the offset value Vo using equation (1), the slight fluctuation component of the offset image data V'(x,y) is also reduced based on the correction coefficient β. Therefore, in equation (4), when the slight fluctuation component d(x,y) is smaller than a predetermined threshold TH, the slight fluctuation component d(x,y) is added back (added) to the offset image data, thereby allowing the characteristics of the original image data to be reflected in the corrected image data.

[0059] The cross-sectional image generation unit 36 ​​determines whether or not any transmission image data remains among the transmission image data used for reconstruction for which offset processing has not yet been performed (step S1057). If there is any transmission image data for which offset processing has not yet been performed (step S1057: Y), the unit returns to step S1051 to select the next transmission image data and perform the subsequent processing. If offset processing has been performed on all transmission image data (step S1057: N), the unit terminates the offset processing S1050.

[0060] The image data that has undergone the offset processing as described above (offset image data or corrected image data) is processed by the filtering process S1060 using the FBP method, as described above, and then reconstructed image data is generated by the back projection process S1070.

[0061] FIG. 7 shows pixel values ​​(brightness values) in the X-axis direction near an edge of the transmission image data. Note that the pixel values ​​of the transmission image data are discrete values, but are shown as continuous values ​​in FIG. 7. In FIG. 7, position xe is the edge position, and the brightness values ​​before and after it change from an average V1 to an average V2. FIG. 7(a) shows the original image data, and FIG. 7(b) shows the corrected image data. By performing the offset process described above, it is possible to obtain corrected image data that reduces the values ​​of pixels that are greater than the offset value Vo of the original image data while retaining the slight fluctuation component d of the original image data. This makes it possible to reduce the difference (contrast) in the values ​​of pixels near the edge.

[0062] Although the correction by the offset process S1050 has been described as being performed on all pixels of the transmitted image data, it may also be configured to perform correction only on pixels in a certain area within the transmitted image data, for example, pixels in a specified area within the field of view FOV currently being examined (especially areas where edge processing is required).

[0063] As described above, the offset process S1050 is configured to correct each pixel in at least a part of the region of the transmission image data by reducing the difference between the pixel value and the offset value according to the offset value when the pixel value exceeds a predetermined value (offset value). If the value of a pixel with a low brightness value is increased in order to reduce the difference (contrast) in brightness values ​​near an edge, the minute fluctuation component may disappear. However, as described above, by lowering (reducing) the value of a pixel with a high brightness value, the minute fluctuation component can also be maintained, and clear reconstructed image data (cross-sectional image data) can be generated by the subsequent filtering process and back projection process using the FBP method.

[0064] (First Modification) In the offset processing described above, the values ​​of pixels with brightness values ​​higher than the offset value are reduced in order to reduce the difference in brightness values ​​(contrast) near the edge, but it is also possible to configure the processing so that the values ​​of pixels with brightness values ​​lower than the offset value are increased.

[0065] In addition, this first modified example is configured to utilize the above-mentioned offset processing (processing to reduce the values ​​of pixels with brightness values ​​higher than the offset value) to realize processing to increase the values ​​of pixels with brightness values ​​lower than the offset value. Specifically, the complement of the offset value and the transmission image data is obtained, and correction is performed to reduce the values ​​of pixels with brightness values ​​higher than the offset value converted to the complement in the transmission image data converted to the complement, and the corrected transmission image data is then converted back to the complement. As a result of this processing, it is possible to increase the values ​​of pixels with brightness values ​​lower than the offset value in the transmission image data.

[0066] Here, the complement Vc of the luminance value V of a pixel in the image data can be calculated by the following formula (a).

[0067] Vc = Vmax-V (a) however, V: pixel value Vc: pixel value converted to its complement Vmax: Maximum pixel value

[0068] 8, in the reconstruction image generation process S1046, the cross-sectional image generation unit 36 ​​first calculates the complement Voc of the offset value Vo using the above-mentioned formula (a) (step S1047). The complement Voc of the offset value Vo is expressed by the following formula (5).

[0069] Voc = Vmax-Vo (5) however, Vo: Offset value Voc: Offset value converted to its complement Vmax: maximum pixel value

[0070] Furthermore, the cross-sectional image generating unit 36 ​​calculates a value Vc(x,y) obtained by converting the pixel values ​​V(x,y) of all the transmission image data (original image data) into their complements using the above-mentioned formula (a) (step S1048). The converted transmission image data is called "original image data converted into complements." Specifically, it is expressed by the following formula (6).

[0071] Vc(x,y) = Vmax-V(x,y) (6) however, V(x,y): The pixel value at the position (x,y) of the original image data Vc(x,y): The pixel value at position (x,y) of the original image data converted to its complement Vmax: maximum pixel value

[0072] Then, the cross-sectional image generating unit 36 ​​performs offset processing S1050 using the offset value Voc converted to its complement and the original image data (pixel value Vc(x,y)) converted to its complement. At this time, in the above description, the "offset value Vo" is replaced with the "offset value Voc converted to its complement" and the "original image data" is replaced with the "original image data converted to its complement" (the "pixel value V(x,y) of the original image data" is replaced with the "pixel value Vc(x,y) of the original image data converted to its complement"). Specifically, the pixel value Vc(x,y) of the original image data converted to its complement is compared with the offset value Voc converted to its complement using the following equation (1'). If the pixel value Vc(x,y) is greater than the offset value Voc, a value Vc'(x,y) obtained by reducing the pixel value is calculated. If the pixel value Vc(x,y) is equal to or less than the offset value Voc, Vc'(x,y)=Vc(x,y).

[0073] When Voc < Vc(x,y) Vc′(x,y) = Voc+(Vc(x,y)-Voc)×β When Vc(x,y) ≦ Voc Vc′(x,y) = Vc(x,y) (1′) however, Vc(x,y): The pixel value at position (x,y) of the original image data converted to its complement Vc'(x,y): The pixel value at position (x,y) of the offset image data converted to its complement Voc: Offset value converted to its complement β: correction coefficient

[0074] In this way, when the offset processing S1050 is performed on the original image data converted to a complement based on the offset value Voc converted to a complement, offset image data converted to a complement is generated, and the pixel value Vc'(x,y) of this offset image data is generated from the offset value Voc converted to a complement and the pixel value Vc(x,y) of the original image data converted to a complement, as described above. Therefore, the cross-sectional image generating unit 36 ​​converts the pixel value Vc'(x,y) of the corrected image data into a complement again based on equation (a) as shown in the following equation (7) (step S1059).

[0075] V′(x,y) = Vmax-Vc′(x,y) (7) however, Vc'(x,y): The pixel value at position (x,y) of the offset image data converted to its complement V'(x,y): The value of the pixel at the position (x,y) of the offset image data converted to its complement, converted back to its complement. Vmax: maximum pixel value

[0076] In this way, the pixel value V'(x, y) converted back to its complement is the value that has been subjected to the process of raising the pixel value V(x, y) whose brightness value is lower than the offset value Vo, as described above. When this image data is used to generate reconstructed image data (cross-sectional image data) using the FBP method (steps S1060, S1070), the amount of undershoot or overshoot that occurs in the reconstructed image data (cross-sectional image data) can be reduced.

[0077] Although detailed description will be omitted, in step S1050 described above, corrected image data to which minute fluctuation components have been added may be generated by applying the above-described equations (2) to (4) to the offset image data (pixel value Vc′(x,y)) converted to complements (since this corrected image data is also based on the original image data converted to complements, it is referred to as “corrected image data converted to complements,” and its pixel values ​​are represented as Vc″(x,y)). Then, using image data (pixel values ​​are represented as V″(x,y)) obtained by converting the pixel values ​​Vc″(x,y) of the corrected image data converted to complements again, reconstructed image data (cross-sectional image data) may be generated by the FBP method in steps S1060 and S1070.

[0078] As described above, by performing a filter process S1060 on the offset image data that has been converted back to its complement or the corrected image data that has been converted back to its complement, and then performing an inverse correction process S1070, reconstructed image data can be generated.

[0079] The offset processing according to the first modification will be described with reference to FIG. 9. FIG. 9(a) shows original image data in which position xe is the edge position and the brightness values ​​before and after the edge change from an average V1 to an average V2. In FIG. 9(a), the offset processing according to the first modification performs a correction to raise pixels smaller than the offset value Vo. FIG. 9(b) shows the pixel values ​​of the original image data in FIG. 9(a) converted to their complements. At this time, the offset value Vo is also converted to its complement Voc, and the values ​​V1 and V2 are also converted to their complements V1c and V2c. In this way, when the image data converted to its complement is corrected to lower pixels larger than the converted offset value Voc, the corrected image data is generated, resulting in the state shown in FIG. 9(c). Furthermore, when the pixel values ​​of the corrected image data are converted to their complements again, the state shown in FIG. 9(d) is obtained. Comparing Figure 9(d) with Figure 9(a), when the offset value Voc and the values ​​V1c and V2c before and after the edge, which have been converted to complements from the state in Figure 9(c), are converted back to complements, they are converted back to the initial state Vo, V1, and V2, and the values ​​of pixels smaller than the offset value Vo are raised, resulting in a reduction in the difference in brightness values ​​(contrast) near the edge.

[0080] In addition, the correction by the offset processing S1050 according to the first modified example may be configured not only to be performed on all pixels of the transmitted image data, but also to be performed only on pixels in a specified area (particularly an area requiring edge processing) within the imaging area (field of view FOV) currently being inspected.

[0081] As described above, the offset processing S1050 according to the first modified example is configured to correct each pixel in at least a part of the region of the transmitted image data by increasing the difference between the pixel value and the offset value according to the offset value when the pixel value falls below a predetermined value (offset value). As described above, if the value of a pixel with a low brightness value is increased in order to reduce the difference in brightness value (contrast) near the edge, there is a possibility that the minute fluctuation component will disappear, but this method can be applied when the difference in brightness value (contrast) near the edge is large or when the part with a low brightness value is not used for inspection.

[0082] (Second Modification) In the above example, a case has been described in which offset processing involves a single correction to lower or raise the pixel value of the transmissive image data for one offset value. However, multiple offset values ​​may be set and multiple corrections to lower or raise the pixel value may be performed. Alternatively, both a correction to raise and a correction to lower the pixel value may be performed. In this case, the order of the correction to raise and the correction to lower the pixel value may not matter, and either or both of the correction to raise and the correction to lower the pixel value may be performed multiple times. Here, using Figures 10 and 11, a case will be described in which multiple offset values ​​are set and multiple corrections to lower the pixel value of the transmissive image data are performed.

[0083] 10, first, in the reconstruction image generation process S1046, the cross-sectional image generation unit 36 ​​selects one offset value Von from among the plurality of offset values ​​in descending order (step S1047). Here, n is an identification number of the offset value, and for example, it is assumed that the numbers are assigned in descending order starting from 1. Note that the plurality of offset values ​​may be stored in advance in the storage unit 34, or may be set by the operator via an input device of the control unit 10 when the examination is performed.

[0084] Then, the cross-sectional image generating unit 36 ​​executes the offset processing described above using the currently selected offset value Von and the transmission image data (original image data) (step S1050). When the offset processing S1050 is executed, corrected image data is generated. The cross-sectional image generating unit 36 ​​determines whether all offset values ​​have been selected (step S1059). If it determines that there is an offset value that has not yet been selected (step S1059: N), the process returns to step S1047, selects the next largest offset value Von, and repeats the subsequent processing. At this time, in the offset processing S1050, the corrected image data corrected with the previous offset value is corrected with the newly selected offset value as the original image data.

[0085] On the other hand, if it is determined that all offset values ​​have been selected (step S1059: Y), the cross-sectional image generation unit 36 ​​performs a filter process (edge ​​enhancement process) on the last generated corrected image data (step S1060), and further performs a backprojection process to generate reconstructed image data (step S1070), thereby terminating the reconstructed image generation process S1046.

[0086] FIG. 11(a) shows the original image data, where positions xe1 and xe2 are edge positions, and the luminance values ​​before and after position xe1 change from an average V1 to an average V2, and the luminance values ​​before and after position xe2 change from an average V2 to an average V3. In FIG. 11(a), the offset processing according to the second modification performs a correction on a first offset value Vo1 to reduce pixels greater than this value Vo1. Specifically, pixels to the right of position xe2 are corrected. The result of this correction is shown in FIG. 11(b). At this time, the small fluctuation component d1 to the right of position xe2 is also maintained. Next, a second offset value Vo2 is performed on FIG. 11(b), to reduce pixels greater than this value Vo2. Specifically, pixels to the right of position xe1 are corrected. The result of this correction is shown in FIG. 11(c). At this time, the small fluctuation component d2 to the right of position xe1 and to the left of position xe2 is also maintained. Furthermore, the small fluctuation component to the right of the position xe2 is maintained as d1'.

[0087] Note that the threshold value TH in the offset process S1050 may be changed for each of a plurality of offset values. Also, the case of raising the pixel value of the transmission image data for a plurality of offset values ​​can be realized in a similar manner based on the first modified example.

[0088] In this way, when there are multiple edges with different brightness value differences (contrast), by setting multiple offset values ​​and performing offset processing S1050 individually, it is possible to perform correction appropriate for each edge and generate clear reconstructed image data.

[0089] (Main effects) The main features and effects of the image data generation method in the inspection device 1 according to the present embodiment described above will be described below.

[0090] First, as described above, when pre-processing (filtering (edge ​​enhancement)) is performed on the generation process of reconstructed image data (three-dimensional image data) by the back projection method, edge portions are enhanced in the reconstructed image data, but there are cases where parts that are higher than the actual value (overshooting parts) and parts that are lower than the actual value (undershooting parts) are generated in the image of the edge. In contrast, by performing the above-described correction process (offset process S1050) on the transmission image data before pre-processing, even if filtering (edge ​​enhancement) is performed, the generation of parts that are higher than the actual value or lower than the actual value (parts where overshooting or undershooting occurs) in the edge portions of the generated reconstructed image data can be suppressed. This improves the accuracy of the process of determining defective areas using reconstructed image data (cross-sectional image data), and reduces over-determination.

[0091] Secondly, the reconstructed image data, which is three-dimensional image data, is composed of multiple cross-sectional image data (generally, image data of a cross section along a plane perpendicular to the optical axis (axis A) of the light source (radiation generator 22)) that overlap in a predetermined direction. However, by performing the offset processing S1050 described above on the transmission image data, the image of the edge portion is emphasized and the amount of extension in the Z direction is reduced, thereby reducing interference between the cross-sectional image data. In multi-layer inspection using pseudo-cross-sectional image data, the images between layers (between cross sections) can be separated more accurately, thereby improving the accuracy of the judgment process. [Explanation of symbols]

[0092] 1. Inspection equipment 10 Control Unit 12 Test subject 22 Radiation generator (light source) 24 Holding part 26 detector

Claims

1. 1. An image data generation method for generating three-dimensional image data of an object under inspection using at least two pieces of transmission image data of the object under inspection, which are obtained by the detector using light emitted from the light source and transmitted through the object under inspection, while changing relative positions of a light source, a detector, and a holder that holds the object under inspection, a first step of correcting each pixel in at least a partial area of ​​the transmitted image data by decreasing a difference between the pixel value and the predetermined value when the pixel value exceeds a predetermined value in accordance with the predetermined value, or by increasing a difference between the pixel value and the predetermined value when the pixel value falls below the predetermined value in accordance with the predetermined value; a second step of performing a predetermined filtering process on the corrected transmission image data; a third step of generating the three-dimensional image data from the filtered transmission image data using a backprojection method. How image data is generated.

2. The first step comprises: a first-1 step of performing the correction on each pixel in at least a partial area of ​​the transmission image data; a first-second step of calculating a difference for each pixel between the transmitted image data and the transmitted image data corrected in the first-first step; a first-third step of averaging the differences between the pixels obtained in the first-second step; a 1-4 step of calculating, as minute variation information for each pixel, the difference between the difference for each pixel calculated in the 1-2 step and the difference for each pixel averaged in the 1-3 step; and a 1-5 step of adding the minute variation information to the value of each pixel of the transmitted image data corrected in the 1-1 step when the minute variation information satisfies a predetermined condition. The image data generating method according to claim 1 .

3. The first step comprises: The predetermined value is changed and the correction is repeated. The image data generating method according to claim 1 .

4. The first step comprises: Correction is performed for each pixel of the transmitted image data using the following formula: The image data generating method according to claim 1 . When Vo < V(x, y) V'(x,y) = Vo+(V(x,y)-Vo)×β When V(x, y)≦Vo V'(x,y) = V(x,y) however, V(x, y): the value of the pixel at the position (x, y) in the transmission image data V'(x,y): the value of the pixel at position (x,y) in the transmission image data offset by the predetermined value Vo: the predetermined value Vmax: maximum value of the pixel β: correction coefficient

5. The first step comprises: converting the predetermined value to its complement using the following formula: Voc=Vmax-Vo however, Vo: the predetermined value Voc: the predetermined value converted to its complement Vmax: maximum value of the pixel For each pixel of the transmitted image data, convert the value of the pixel into a complement using the following formula: Vc(x,y) = Vmax-V(x,y) however, V(x, y): the value of the pixel at the position (x, y) in the transmission image data Vc(x, y): the value of the pixel converted to its complement at the position (x, y) in the transmission image data Vmax: maximum value of the pixel Correct each pixel of the transmission image data converted into its complement using the following formula: When Voc < Vc(x, y) Vc'(x,y) = Voc+(Vc(x,y)-Voc)×β When Vc(x, y)≦Voc Vc'(x,y) = Vc(x,y) however, Vc(x, y): the value of the pixel converted to its complement at the position (x, y) in the transmission image data Vc'(x, y): A value obtained by offsetting the pixel value converted to its complement at the position (x, y) in the transmission image data by the predetermined value converted to its complement. Voc: the predetermined value converted to its complement Vmax: maximum value of the pixel β: correction coefficient For each pixel of the corrected transmitted image data, the value of the pixel is converted to a complement using the following formula: The image data generating method according to claim 1 . V'(x,y) = Vmax-Vc'(x,y) however, Vc'(x, y): A value obtained by offsetting the value converted to the complement of the pixel at the position (x, y) in the transmission image data by the predetermined value converted to the complement. V'(x,y): the value of the pixel at position (x,y) in the transmission image data offset by the predetermined value Vmax: maximum value of the pixel

6. A light source and A detector; a holder for holding an object to be inspected; a control unit that generates three-dimensional image data of the object under inspection using at least two pieces of transmission image data of the object under inspection, which are obtained by the detector using light emitted from the light source and transmitted through the object under inspection by changing the relative positions of the light source, the detector, and the holding unit; The control unit generates the three-dimensional image by the image data generation method according to any one of claims 1 to 5. Inspection equipment.

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