JP2019178941A - Inspection system and inspection method - Google Patents

Abstract

To prevent excessive detection in an area where the gradient of a surface is suddenly changed regardless of the presence/absence of abnormality.SOLUTION: An inspection system of an embodiment comprises: an areal illumination unit that gives, to a body to be inspected, periodic temporal change and spatial change of the intensity of light; an image creation unit that creates, from image data output from a time correlation camera or an imaging system having an equivalent operation to the camera, a difference image indicating the difference between a complex time correlation image represented by a complex number and a restored image created by performing, on the complex time correlation image, processing using a Weiner filter that removes abnormality on an image as a noise component; a correction unit that corrects the difference image on the basis of the value of phase only differentiation of at least one of the time correlation image and restored image and the value of the amplitude of at least one of the time correlation image and restored image; and an abnormality determination unit that determines abnormality of a surface to be inspected of the body to be inspected on the basis of the difference image after the correction performed by the correction unit.SELECTED DRAWING: Figure 1

Description

  Embodiments described herein relate generally to an inspection system and an inspection method.

  Conventionally, a time that includes not only the intensity of light but also information about temporal transition of light by irradiating the object to be inspected periodically and imaging the reflected light from the surface of the object to be inspected A technique for acquiring a correlation image has been proposed. Such a time correlation image is used, for example, to detect an abnormality of the object to be inspected.

Japanese Patent Laying-Open No. 2015-197345

  In the technique as described above, for example, there are a region where the amplitude shows a value far from a predetermined reference value, a region where the degree of phase change is larger than the predetermined reference value (that is, the phase changes rapidly), and the like. , Easy to detect as abnormal.

  However, in areas where the gradient of the surface changes abruptly regardless of whether there is an abnormality, such as the edge area or corner area of the inspection target surface of the inspected object viewed from the time correlation camera, there is no abnormality. Even in such a state, the amplitude observed by the time correlation camera shows a value far from the predetermined reference value, or the amount of phase change observed by the time correlation camera becomes larger than the predetermined reference value. It's easy to do. Therefore, in this case, overdetection that is detected to be abnormal up to a normal part is likely to occur.

  Further, when the object to be inspected is a coated product, the coating is easily accumulated in the end region and the corner region, and the surface is likely to bulge. However, such a bulge is inevitably generated in the painting process, and should basically be determined to be normal, so determining it to be abnormal corresponds to overdetection.

  Therefore, it is desired to suppress overdetection in a region where the surface gradient changes rapidly regardless of whether there is an abnormality, such as the above-described end region or corner region.

  The inspection system of the embodiment is output from a planar illumination unit that gives a periodic temporal change and a spatial change of light intensity to an object to be inspected, and a time correlation camera or an imaging system that performs an equivalent operation. The difference between the complex time correlation image represented by complex numbers from the image data and the restored image generated by applying a process using a Wiener filter that removes abnormalities on the image as noise components to the complex time correlation image Based on an image generation unit that generates a difference image, a phase-only differential value of at least one of the time correlation image and the restored image, and an amplitude value of at least one of the time correlation image and the restored image, A correction unit that corrects the difference image, and an abnormality determination unit that determines an abnormality of the inspection target surface of the object to be inspected based on the difference image corrected by the correction unit.

Drawing 1 is a figure showing the example of composition of the inspection system of an embodiment. FIG. 2 is a block diagram illustrating a configuration of the time correlation camera of the embodiment. FIG. 3 is a conceptual diagram showing frames accumulated in time series by the time correlation camera of the embodiment. FIG. 4 is a diagram illustrating an example of a fringe pattern irradiated by the illumination device of the embodiment. FIG. 5 is a diagram illustrating a first detection example of abnormality of the inspection object by the time correlation camera of the embodiment. FIG. 6 is a diagram illustrating an example of the amplitude of light that changes in accordance with the abnormality when the abnormality illustrated in FIG. 5 is present in the test object in the embodiment. FIG. 7 is a diagram illustrating a second detection example of an abnormality of an object to be inspected by the time correlation camera of the embodiment. FIG. 8 is a diagram illustrating a third example of detection of abnormality of an object to be inspected by the time correlation camera of the embodiment. FIG. 9 is a diagram illustrating an example of a fringe pattern output from the illumination control unit of the embodiment to the illumination device. FIG. 10 is a diagram illustrating an example of a wave shape representing a stripe pattern after passing through the screen of the embodiment. FIG. 11 is a diagram for explaining a difference image used in the embodiment. FIG. 12 is a diagram illustrating an example of the complex time correlation image of the embodiment. FIG. 13 is a diagram for explaining a method of correcting a difference image based on the value of the phase only derivative in the embodiment. FIG. 14 is a diagram for explaining a difference image correction method based on the amplitude value in the embodiment. FIG. 15 is a flowchart showing a series of processing executed when the inspection system of the embodiment inspects an object to be inspected. FIG. 16 is a flowchart illustrating details of an information acquisition process for abnormality determination executed by the inspection system according to the embodiment. FIG. 17 is a diagram illustrating a switching example of a fringe pattern output from the illumination control unit of the second modification. FIG. 18 is a diagram illustrating an example in which the illumination control unit according to the second modification irradiates the surface of the inspection object including an abnormality (defect) with a stripe pattern. FIG. 19 is a diagram showing the relationship between the abnormality (defect) and the stripe pattern on the screen when the stripe pattern is changed in the y direction in FIG. FIG. 20 is a diagram illustrating an example of a fringe pattern output from the illumination control unit of the third modified example to the illumination device.

<Embodiment>
Hereinafter, the inspection system of the embodiment will be described. The inspection system of the embodiment has various configurations for inspecting an object to be inspected. Drawing 1 is a figure showing the example of composition of the inspection system of an embodiment. As shown in FIG. 1, the inspection system according to the embodiment includes a PC 100, a time correlation camera 110, a lighting device 120, a screen 130, and an arm 140.

  The arm 140 is used to fix the inspection object 150 and changes the position and orientation of the surface of the inspection object 150 that can be imaged by the time correlation camera 110 according to control from the PC 100.

  The illuminating device 120 is a device that irradiates light to the object 150 to be inspected, and can control the intensity of irradiated light in units of regions in accordance with a stripe pattern from the PC 100. Furthermore, the illuminating device 120 can control the intensity | strength of the light of the said area unit according to periodic time transition. In other words, the lighting device 120 can give a periodic temporal change and a spatial change of the light intensity. A specific light intensity control method will be described later.

  The screen 130 diffuses the light output from the illuminating device 120 and then irradiates the test object 150 with light in a plane. The screen 130 according to the embodiment irradiates the object 150 in a surface with the light input from the lighting device 120 and subjected to periodic time change and space change. An optical system component (not shown) such as a condensing Fresnel lens may be provided between the illumination device 120 and the screen 130.

  In addition, although embodiment demonstrates the example which comprises the planar illumination part which combines the illumination device 120 and the screen 130 and gives the periodic time change and spatial change of light intensity, the illumination part of embodiment is described. It is not limited to such a combination. In the embodiment, for example, the illumination unit may be configured by arranging LEDs on a surface or arranging a large monitor.

  FIG. 2 is a block diagram illustrating a configuration of the time correlation camera 110 according to the embodiment. The time correlation camera 110 includes an optical system 210, an image sensor 220, a data buffer 230, a control unit 240, and a reference signal output unit 250.

  The optical system 210 includes an imaging lens and the like, transmits a light beam from a subject (including the inspection object 150) outside the time correlation camera 110, and forms an optical image of the subject formed by the light beam.

  The image sensor 220 is a sensor that can output the intensity of light incident through the optical system 210 as a light intensity signal at high speed for each pixel.

  The light intensity signal of the embodiment is a signal obtained by the illumination device 120 of the inspection system irradiating a subject (including the inspected object 150) with light and the image sensor 220 receiving reflected light from the subject.

  The image sensor 220 is, for example, a sensor that can be read out at a higher speed than a conventional sensor, and has a two-dimensional planar shape in which pixels are arranged in two kinds of directions: a row direction (x direction) and a column direction (y direction). It shall be configured. Each pixel of the image sensor 220 is defined as a pixel P (1,1),..., P (i, j),..., P (X, Y) (Note that the image size of the embodiment is XX). Y.) Note that the reading speed of the image sensor 220 is not limited and may be the same as the conventional one.

  The image sensor 220 receives a light beam from the subject (including the inspected object 150) transmitted by the optical system 210 and photoelectrically converts the light intensity signal (intensity of light reflected from the subject) ( A two-dimensional planar frame composed of (imaging signals) is generated and output to the control unit 240. The image sensor 220 according to the embodiment outputs the frame for each readable unit time.

  The control unit 240 according to the embodiment includes hardware similar to that of a normal computer such as a processor and a memory, and the software (inspection program) stored in the memory is executed by the processor, so that the transfer unit 241 and the reading unit 242, intensity image superimposing unit 243, first multiplier 244, first correlation image superimposing unit 245, second multiplier 246, second correlation image superimposing unit 247, image An output unit 248. In the embodiment, part or all of the functional configuration of the control unit 240 may be realized only by dedicated hardware (circuit) using an FPGA, an ASIC, or the like.

  The transfer unit 241 stores the frames composed of the light intensity signals output from the image sensor 220 in the data buffer 230 in time series order.

  The data buffer 230 accumulates frames composed of light intensity signals output from the image sensor 220 in time series.

  FIG. 3 is a conceptual diagram illustrating frames accumulated in time series in the time correlation camera 110 according to the embodiment. As shown in FIG. 3, the data buffer 230 of the embodiment stores a plurality of light intensity signals G (1, 1, t),... At each time t (t = t0, t1, t2,..., Tn). .., G (i, j, t),..., G (X, Y, t), a plurality of frames Fk (k = 1, 2,..., N) are accumulated in chronological order. Is done. Note that one frame generated at time t is a light intensity signal G (1, 1, t),..., G (i, j, t), ..., G (X, Y, t). Composed.

  The light intensity signal (imaging signal) G (1,1, t),..., G (i, j, t),..., G (X, Y, t) of the embodiment has a frame Fk (k = Each pixel P (1, 1),..., P (i, j),.

  The frame output from the image sensor 220 includes only a light intensity signal, in other words, it can be considered as monochrome image data. In the embodiment, an example in which the image sensor 220 generates monochrome image data in consideration of resolution, sensitivity, cost, and the like will be described. However, the image sensor 220 is not limited to a monochrome image sensor. Alternatively, a color image sensor may be used.

  Returning to FIG. 2, the reading unit 242 of the embodiment receives the light intensity signals G (1,1, t),..., G (i, j, t),. , T) are read out in frame-by-frame order and output to the first multiplier 244, the second multiplier 246, and the intensity image superimposing unit 243.

  The time correlation camera 110 according to the embodiment generates image data for each output destination of the reading unit 242. In other words, the time correlation camera 110 generates three types of image data.

  The time correlation camera 110 according to the embodiment generates intensity image data and two types of time correlation image data as three types of image data. The embodiment is not limited to generating the intensity image data and the two types of time correlation image data. When the intensity image data is not generated, one type or three or more types of time correlations are used. A case where image data is generated is also conceivable.

  As described above, the image sensor 220 according to the embodiment outputs a frame composed of a light intensity signal for each unit time. However, in order to generate normal image data, a light intensity signal corresponding to the exposure time necessary for imaging is required. Therefore, in the embodiment, the intensity image superimposing unit 243 generates intensity image data by superimposing a plurality of frames for an exposure time necessary for imaging. In addition, each pixel value (value representing the intensity of light) G (x, y) of the intensity image data can be derived from the following equation (1). The exposure time is the time difference between t0 and tn.

  Thereby, the intensity image data in which the subject (including the inspected object 150) is imaged is generated in the same manner as the conventional camera imaging. Then, the intensity image superimposing unit 243 outputs the generated intensity image data to the image output unit 248.

  The time correlation image data is image data indicating changes in light intensity according to time transition. That is, in the embodiment, for each frame in time series order, the light intensity signal included in the frame is multiplied by the reference signal indicating the time transition, and the time that is the result of multiplying the reference signal and the light intensity signal is obtained. Temporal correlation image data is generated by generating a temporal correlation value frame composed of correlation values and superimposing a plurality of temporal correlation value frames.

  By the way, in order to detect an abnormality of the inspection object 150 using the time correlation image data, it is necessary to change the light intensity signal input to the image sensor 220 in synchronization with the reference signal. For this reason, as described above, the illumination device 120 according to the embodiment is configured to irradiate the surface light through the screen 130 so as to periodically change the time and spatially move the stripes. The

In the embodiment, two types of time correlation image data are generated. The reference signal may be a signal representing a time transition, but in the embodiment, a complex sine wave e ^−jωt is used. It is assumed that the angular frequency ω and time t. The angular frequency so that the complex sine wave e ^−jωt representing the reference signal correlates with one period of the above-described exposure time (in other words, the time necessary for generating the intensity image data and the time correlation image data). Assume that ω is set. In other words, the planar and dynamic light formed by the illumination unit 120 and the illumination unit such as the screen 130 has a first period (time period) at each position on the surface (reflection surface) of the object 150 to be inspected. And a distribution of increase or decrease in spatial irradiation intensity in a second period (spatial period) along at least one direction along the surface. When this planar light is reflected by the surface, it is complex-modulated according to the specifications of the surface (normal vector distribution, etc.). The time correlation camera 110 receives the light complex-modulated on the surface and performs quadrature detection (orthogonal demodulation) using the reference signal of the first period, thereby obtaining time correlation image data as a complex signal. By modulation / demodulation based on such time-correlated image data as a complex signal, it is possible to detect features corresponding to the distribution (spatial distribution) of normal vectors on the surface.

The complex sine wave e ^−jωt can also be expressed as e ^−jωt = cos ωt−j · sin ωt. Accordingly, each pixel value C (x, y) of the time correlation image data can be derived from the following equation (2).

  In the embodiment, in the formula (2), two types of time correlation image data are divided into a pixel value C1 (x, y) representing the real part and a pixel value C2 (x, y) representing the imaginary part. Generate.

For this reason, the reference signal output unit 250 generates and outputs different reference signals for the first multiplier 244 and the second multiplier 246, respectively. Embodiment of the reference signal output section 250 outputs the first reference signal cosωt corresponding to the real part of the complex sine wave e ^-Jeiomegati the first multiplier 244, corresponding to the imaginary part of the complex sine wave e ^-Jeiomegati The second reference signal sin ωt is output to the second multiplier 246. As described above, the reference signal output unit 250 according to the embodiment outputs two types of reference signals expressed as time functions of a sine wave and a cosine wave that form a Hilbert transform pair as an example. However, the reference signal is not limited to the example described here, and may be a reference signal that changes according to a time transition, such as a time function.

Then, the first multiplier 244 ^calculates the real part cosωt of the complex sine wave e ^−jωt input from the reference signal output unit 250 for each light intensity signal of the frame in units of frames input from the reading unit 242. Multiply.

  The first correlation image superimposing unit 245 performs a process of superimposing the multiplication result of the first multiplier 244 on a pixel-by-pixel basis for a plurality of frames for an exposure time necessary for imaging. Thereby, each pixel value C1 (x, y) of the first time correlation image data is derived from the following equation (3).

Then, the second multiplier 246 multiplies the light intensity signal of the frame input from the reading unit 242 by the imaginary part sinωt of the complex sine wave e ^−jωt input from the reference signal output unit 250.

  The second correlation image superimposing unit 247 performs a process of superimposing the multiplication result of the second multiplier 246 on a pixel-by-pixel basis for a plurality of frames corresponding to the exposure time necessary for imaging. Thereby, each pixel value C2 (x, y) of the second time correlation image data is derived from the following equation (4).

  By performing the processing described above, two types of time correlation image data, in other words, time correlation image data having two degrees of freedom can be generated.

Further, the embodiment does not limit the type of reference signal. For example, in the embodiment, two types of time correlation image data of the real part and the imaginary part of the complex sine wave e ^−jωt are generated, but two types of image data based on the light amplitude and the light phase are generated. May be.

  Note that the time correlation camera 110 of the embodiment can generate a plurality of systems as time correlation image data. Thereby, for example, when light in which stripes having a plurality of widths are combined is irradiated, two types of time correlation image data of the real part and the imaginary part described above can be generated for each stripe width. For this purpose, the time correlation camera 110 includes a combination of two multipliers and two correlation image superimposing units for a plurality of systems, and the reference signal output unit 250 has an angular frequency suitable for each system. The reference signal by ω can be output.

  Then, the image output unit 248 outputs two types of time correlation image data and intensity image data to the PC 100. As a result, the PC 100 detects an abnormality of the inspected object 150 using the two types of time correlation image data and the intensity image data. For that purpose, it is necessary to irradiate the test object 150 with light.

  The illuminating device 120 of embodiment irradiates the fringe pattern which moves at high speed. FIG. 4 is a diagram illustrating an example of a fringe pattern irradiated by the illumination device 120 of the embodiment. In the example illustrated in FIG. 4, a stripe pattern in which the stripe width for one period is set to W is scrolled (moved) in the x direction. A white area is a bright area corresponding to the stripe, and a black area is an interval area (dark area) corresponding to the stripe.

  In the embodiment, the fringe pattern irradiated by the illuminating device 120 moves by one period with the exposure time when the time correlation camera 110 captures the intensity image data and the time correlation image data. Thereby, the illuminating device 120 gives the time change of the light intensity periodically by the spatial movement of the stripe pattern of the light intensity. In the embodiment, by associating the time during which the fringe pattern in FIG. 4 moves by one period with the exposure time, each pixel of the time-correlated image data has information on the light intensity signal for at least one period of the fringe pattern. Is embedded.

  As shown in FIG. 4, in the embodiment, an example in which the illumination device 120 irradiates a stripe pattern based on a rectangular wave will be described, but other than a rectangular wave may be used. In the embodiment, the illumination device 120 is irradiated through the screen 130, so that the boundary area between the light and dark of the rectangular wave can be blurred.

  In the embodiment, the fringe pattern irradiated by the illumination device 120 is represented as A (1 + cos (ωt + kx)). That is, the stripe pattern includes a plurality of stripes repeatedly (periodically). Note that the intensity of light applied to the inspection object 150 can be adjusted between 0 and 2A, and is a light phase kx. k is the wave number of the stripe. x is the direction in which the phase changes.

  Then, the fundamental frequency component of the light intensity signal f (x, y, t) of each pixel of the frame can be expressed as the following equation (5). As shown in Expression (5), the brightness of the stripe changes in the x direction.

f (x, y, t) = A (1 + cos (ωt + kx))
= A + A / 2 {e ^{j (ωt + kx)} + e ^{−j (ωt + kx)} } (5)

  As shown in Expression (5), the intensity signal of the fringe pattern irradiated by the illumination device 120 can be considered as a complex number.

  Then, the light from the illumination device 120 is reflected and input to the image sensor 220 from the subject (including the inspection object 150).

  Therefore, the light intensity signal G (x, y, t) input to the image sensor 220 is used as the light intensity signal f (x, y, t) of each pixel of the frame when the illumination device 120 is irradiated. Can do. Therefore, by substituting equation (5) into equation (1) for deriving intensity image data, equation (6) shown below can be derived. Note that the phase is kx.

  From Expression (6), it can be confirmed that each pixel of the intensity image data is input with a value obtained by multiplying the exposure time T by the intermediate value A of the intensity of the light output from the illumination device 120. Further, by substituting equation (5) into equation (2) for deriving time correlation image data, equation (7) shown below can be derived. Note that AT / 2 is the amplitude and kx is the phase.

  Thereby, the time correlation image data represented by the complex number shown by Formula (7) can be replaced with the two types of time correlation image data described above. That is, the time correlation image data composed of the real part and the imaginary part described above includes a phase change and an amplitude change in the light intensity change irradiated on the object 150. In other words, the PC 100 according to the embodiment may be described as a phase change in the intensity change of light emitted from the illumination device 120 (hereinafter simply referred to as a light phase change) based on two types of time correlation image data. ) And an amplitude change in the light intensity change (hereinafter sometimes simply referred to as a light amplitude change).

  Therefore, the PC 100 according to the embodiment includes a phase image representing a phase change of light entering each pixel and an amplitude image representing the amplitude of light entering each pixel based on the time correlation image data and the intensity image data. Generate. In addition, the PC 100 generates an intensity image representing the intensity of light entering each pixel based on the intensity image data. Then, the PC 100 detects an abnormality of the inspected object 150 based on at least one of the phase image, the amplitude image, and the intensity image.

  By the way, when an abnormality based on the unevenness occurs in the surface shape of the inspection object 150, the distribution of the normal vectors on the surface of the inspection object 150 changes corresponding to the abnormality. In addition, when an abnormality that absorbs light occurs on the surface of the inspection object 150, the intensity of the reflected light changes. A change in the normal vector distribution is detected as at least one of a phase change and an amplitude change of light. Therefore, in the embodiment, using the time correlation image data, at least one of the light phase change and the amplitude change corresponding to the change in the normal vector distribution is detected. As a result, it is possible to specify a region where there is a possibility that a surface shape abnormality exists. Hereinafter, the relationship between the abnormality of the inspected object 150, the normal vector, and the light phase change or amplitude change will be described by way of example.

  FIG. 5 is a diagram illustrating a first detection example of an abnormality of the inspected object 150 by the time correlation camera 110 according to the embodiment. In the example shown in FIG. 5, it is assumed that the inspection object 500 as an example of the inspection object 150 has a protruding shape abnormality 501. In this situation, it can be confirmed that the normal vectors 521, 522, and 523 are in different directions in the region near the point 502 of the abnormality 501. Then, the normal vectors 521, 522, 523 are directed in different directions, so that diffusion (for example, light 511, 512, 513) occurs in the light reflected from the anomaly 501, and the image sensor 220 of the time correlation camera 110. The width 503 of the fringe pattern entering the arbitrary pixel 531 is increased.

  FIG. 6 is a diagram showing an example of the amplitude of light that changes in accordance with the abnormality 501 shown in FIG. In the example shown in FIG. 6, the amplitude of light is divided into a real part (Re) and an imaginary part (Im) and is represented on a two-dimensional plane. In FIG. 6, the light amplitudes 611, 612, and 613 corresponding to the lights 511, 512, and 513 in FIG. The light amplitudes 611, 612, and 613 cancel each other, and light having an amplitude 621 is incident on the arbitrary pixel 531 of the image sensor 220.

  Therefore, in the situation shown in FIG. 6, it can be confirmed that the amplitude is locally small in the region where the abnormality 501 of the inspection object 500 is imaged. In other words, when there is a region that is darker than the surroundings in the amplitude image showing the amplitude change, it can be assumed that there is local cancellation of the amplitude of the light in the region. It can be determined that an abnormality 501 has occurred at the position of the inspection object 500 corresponding to the region. Here, the case where the amplitude image is locally dark in the region corresponding to the protrusion-shaped abnormality 501 is illustrated, but the amplitude image is also locally dark in the region corresponding to the dent-like abnormality such as a scratch. Become.

  The inspection system of the embodiment is not limited to the one in which the inclination changes steeply like the abnormality 501 in FIG. 5, and can also detect an abnormality that changes gently. FIG. 7 is a diagram illustrating a second detection example of abnormality of the inspected object 150 by the time correlation camera 110 according to the embodiment. FIG. 7 shows a situation in which a gentle gradient 701 is generated in the inspected object 700 as an example of the inspected object 150 having a normal surface that is flat (in other words, the normal lines are parallel). . In such a situation, the normal vectors 721, 722, and 723 on the gradient 701 also change gently. Accordingly, the light beams 711, 712, and 713 input to the image sensor 220 are also shifted little by little. In the example shown in FIG. 7, since the light amplitudes do not cancel each other due to the gentle gradient 701, the light amplitudes shown in FIGS. 5 and 6 hardly change. However, although the light originally projected from the screen 130 should enter the image sensor 220 as it is, the light projected from the screen 130 does not enter the image sensor 220 in a parallel state due to the gentle gradient 701. In addition, a phase change occurs in the light. Accordingly, by detecting the difference between the light phase change and the surroundings, an abnormality due to the gentle gradient 701 as shown in FIG. 7 can be detected.

  Further, there may be an abnormality other than the surface shape of the inspection object 150 (in other words, the distribution of the normal vector of the inspection object 150). FIG. 8 is a diagram illustrating a third detection example of the abnormality of the inspected object 150 by the time correlation camera 110 according to the embodiment. In the example shown in FIG. 8, the dirt 801 is attached to the inspected object 800 as an example of the inspected object 150, so that the light emitted from the illumination device 120 is absorbed or diffusely reflected, and the time correlation camera 110 This shows an example in which the intensity of light hardly changes in an arbitrary pixel area where the dirt 801 is imaged. In other words, in an arbitrary pixel area where the dirt 801 is imaged, changes in the light intensity cancel each other and cancel each other, resulting in almost direct current brightness.

  In such a case, in the pixel region where the dirt 801 is imaged, there is almost no light amplitude. Therefore, when an amplitude image is displayed, a region darker than the surroundings is generated. Therefore, it can be estimated that the dirt 801 is present at the position of the inspection object 800 corresponding to the region.

  As described above, in the embodiment, an area in which an abnormality may exist in the inspected object is detected by detecting the change in the amplitude of the light and the change in the phase of the light based on the time correlation image data. Can be specified.

  Returning to FIG. 1, the PC 100 will be described. The PC 100 controls the entire detection system. The PC 100 includes an arm control unit 101, an illumination control unit 102, and a control unit 103.

  The arm control unit 101 controls the arm 140 in order to change the surface of the object 150 to be imaged by the time correlation camera 110. In the embodiment, a plurality of surfaces to be imaged of the inspection object 150 are set in the PC 100 in advance. Then, every time the time correlation camera 110 completes imaging of the test object 150, the arm control unit 101 controls the arm 140 according to the setting so that the surface on which the time correlation camera 110 is set can be imaged. The inspection object 150 is moved. Note that the moving method of the arm 140 according to the embodiment is not limited to repeating the movement of the arm 140 every time imaging is completed and stopping the imaging before the imaging is started, and the arm 140 is continuously moved. Driving can also be included. The arm 140 may also be referred to as a transport unit, a moving unit, a position changing unit, a posture changing unit, or the like.

  The illumination control unit 102 outputs a fringe pattern irradiated by the illumination device 120 in order to inspect the inspected object 150. The illumination control unit 102 according to the embodiment transfers at least three or more stripe patterns to the illumination device 120 and instructs the illumination device 120 to switch and display the stripe patterns during the exposure time.

  FIG. 9 is a diagram illustrating an example of a fringe pattern output from the illumination control unit 102 to the illumination device 120. In accordance with the rectangular wave shown in FIG. 9B, the illumination control unit 102 performs control so that the stripe pattern in which the black region and the white region shown in FIG. 9A are set is output.

  The stripe interval (stripe width) for each stripe pattern irradiated in the embodiment is set according to the size of the abnormality (defect) to be detected, and detailed description thereof is omitted here.

  In the embodiment, it is assumed that the angular frequency ω of the rectangular wave for outputting the fringe pattern corresponds (for example, coincides) with the angular frequency ω of the reference signal.

  As shown in FIG. 9, the fringe pattern output from the illumination control unit 102 can be shown as a rectangular wave, but the border area of the fringe pattern is blurred through the screen 130, that is, the bright area in the fringe pattern. By making the intensity change of light at the boundary between the (stripe region) and the dark region (interval region) gentle (dull), it can be approximated to a sine wave. FIG. 10 is a diagram illustrating an example of a wave shape representing a stripe pattern after passing through the screen 130. As shown in FIG. 10, the measurement accuracy can be improved by the wave shape approaching a sine wave. Further, a gray region in which the brightness changes in multiple steps may be added to the stripe, or a gradation may be given. Further, a stripe pattern including color stripes may be used.

  Returning to FIG. 1, the control unit 103 includes an image generation unit 104, a correction unit 105, and an abnormality determination unit 106. Similar to the control unit 240 described above, in the embodiment, the functional configuration of the control unit 103 may be realized by cooperation of hardware and software, or may be realized only by hardware.

  The image generation unit 104 generates an amplitude image, a phase image, and an intensity image as inspection images used for inspection based on image data such as intensity image data and time correlation image data input from the time correlation camera 110. . As described above, an amplitude image is an image that represents the amplitude of light entering each pixel, a phase image is an image that represents a phase of light entering each pixel, and an intensity image is a pixel-by-pixel. It is an image showing the intensity of light entering.

  In the embodiment, the image generation unit 104 executes the complex number instead of the time correlation image data (which may be referred to as complex time correlation image data) indicated by a polar complex number divided into an amplitude component and a phase component. It is assumed that two types of time correlation image data divided into a part and an imaginary part are received from the time correlation camera 110.

  Although the embodiment does not limit the calculation method of the amplitude image, for example, the image generation unit 104 determines from the pixel values C1 (x, y) and C2 (x, y) of the two types of time correlation image data. It is possible to derive each pixel value F (x, y) of the amplitude image using the following equation (8).

  Further, the image generation unit 104 derives each pixel value P (x, y) of the phase image from the pixel values C1 (x, y) and C2 (x, y) using the following equation (9). It is possible.

  As can be seen from Equation (9), each pixel value of the phase image is folded in the range of −π to π. Accordingly, each pixel value of the phase image can periodically and discontinuously change from −π to π or from π to −π (phase jump). As a result, even when the inspection target surface is a flat surface that does not include local abnormalities (defects) such as irregularities, the phase image obtained by imaging the flat surface is periodically affected by the phase jump. An edge appears.

  In the embodiment, it is also possible to generate a complex time correlation image including both amplitude information and phase information. The complex time correlation image is generated, for example, as a color image in which amplitude information is represented by brightness and phase information is represented by color.

  It goes without saying that the image generation unit 104 can also generate an intensity image based on the intensity image data input from the time correlation camera 110. Therefore, here, a method for deriving each pixel value of the intensity image is described. Description is omitted.

  Further, in the embodiment, the image generation unit 104 generates a difference image based on a Wiener filter as described below as an inspection image different from the amplitude image, the phase image, and the intensity image.

  A Wiener filter is a filter that removes abnormalities on an image as noise components. Therefore, according to the Wiener filter, the information on the abnormality of the inspection target surface is removed from the complex time correlation image as the original image including the information on the abnormality of the inspection target surface, that is, the restoration corresponding to the non-defective inspection target surface. A complex time correlation image as an image (ideal image) can be generated.

  In the embodiment, the Wiener filter is, for example, an object to be inspected based on, for example, a complex time correlation image obtained by imaging the inspection object surfaces of a plurality of non-defective samples without defects. It is assumed that each surface is generated in advance.

  Here, since the difference between the original image and the restored image described above corresponds to information related to the abnormality of the inspection target surface, it is useful for detecting an abnormality by image processing. Therefore, the image generation unit 104 according to the embodiment generates a difference image indicating a difference between a complex time correlation image and a restored image generated by performing processing using a Wiener filter on the complex time correlation image. The amplitude image, the phase image, and the intensity image are generated as one of the other inspection images.

  Various methods for generating the difference image are conceivable. In the embodiment, for example, a method using Fourier transform and inverse Fourier transform as described below can be used.

  FIG. 11 is a diagram for explaining a difference image that is one of the inspection images of the embodiment. In the example shown in FIG. 11, first, a complex time correlation image 1101 as an original image is acquired.

  In the example shown in FIG. 11, a spectrum image 1102 corresponding to the original image is generated by applying (two-dimensional) Fourier transform 1111 to the complex time correlation image 1101 as the original image.

  In the example shown in FIG. 11, the spectral image 1103 corresponding to the restored image is generated by performing the filtering process 1112 based on the Wiener filter on the spectral image 1102 corresponding to the original image.

  In the example shown in FIG. 11, a difference process 1113 for obtaining a difference between the spectrum image 1103 corresponding to the restored image and the spectrum image 1102 corresponding to the original image is executed, so that the spectrum corresponding to the difference image is executed. An image 1104 is generated.

  In the example illustrated in FIG. 11, the inverse Fourier transform 1114 is performed on the spectrum image 1104 corresponding to the difference image, thereby generating a complex time correlation image 1105 as the difference image.

  By the way, there is an abnormality even in an area where the surface gradient changes abruptly regardless of whether there is an abnormality, such as an end area or a corner area of the inspection target surface of the inspection object 150 viewed from the time correlation camera 110. Even in a normal state, the amplitude observed by the time correlation camera 110 shows a value far from the predetermined reference value, or the amount of phase change observed by the time correlation camera 110 is smaller than the predetermined reference value. It is easy to grow. Therefore, in this case, overdetection that is detected to be abnormal up to a normal part is likely to occur.

  Further, when the object to be inspected 150 is a coated product, the coating tends to accumulate in the end region and the corner region, and the surface is likely to bulge. However, such a bulge is inevitably generated in the painting process, and should basically be determined to be normal, so determining it to be abnormal corresponds to overdetection.

  Here, as described above, the difference image used in the inspection according to the embodiment is an image generated based on a complex time correlation image including both amplitude information and phase information. For this reason, abnormalities related to the amplitude and phase change amount as described above, which are observed regardless of the presence or absence of actual abnormality in the end region or corner region of the inspection target surface, also appear in the difference image, and as a result, Overdetection may occur.

  For example, FIG. 12 is a diagram illustrating an example of the complex time correlation image of the embodiment. As described above, the complex time correlation image is generated as a color image in which amplitude information is represented by brightness and phase information is represented by color. In the complex time correlation image shown in FIG. 12, the width of the stripe expressed by the color gradation (corresponding to a steady and periodic change in phase) is abruptly narrowed in the end region of the inspection target surface. At the same time, the brightness (corresponding to the amplitude) is dark. Therefore, when a difference image is generated based on the complex time correlation image shown in FIG. 12, the difference image also shows the influence of the darkness in the edge region and the narrowness of the stripes, and as a result, overdetection occurs. May occur.

  Therefore, referring back to FIG. 1, the correction unit 105 occurs in a region where the amplitude tends to be dark and the phase is likely to change abruptly, regardless of whether there is an actual abnormality, such as an end region or a corner of the inspection target surface. The difference image generated by the image generation unit 104 is corrected so as to suppress possible overdetection.

  More specifically, in the embodiment, the correction unit 105 relatively dulls the gradient of the phase change in the region of the difference image where the value of the phase-only derivative is large, that is, the region where the phase changes rapidly. Correct the difference image. By correcting in this way, the detection sensitivity is increased so that areas with narrow stripes represented by color gradations in complex time correlation images, such as the end areas and corner areas described above, are less likely to be detected as abnormal. It becomes possible to adjust.

  That is, based on a predetermined calculation formula using the reciprocal of the value of the phase only derivative, the correction unit 105 reduces the correction magnification as the value of the phase limited derivative increases, that is, as the reciprocal of the value of the phase limited derivative decreases. The first correction coefficient set so as to be calculated is calculated, and the difference image is corrected based on the first correction coefficient. More specifically, the correction unit 105 calculates the distance on the complex plane between the complex number representing the complex number representing the complex time correlation image as the original number and the real number representing the amplitude value of the complex number representing the difference image. The difference image is corrected by correcting the real number representing the value based on the first correction coefficient.

  FIG. 13 is a diagram for explaining a method of correcting a difference image based on the value of the phase only derivative in the embodiment. In FIG. 13, the horizontal axis corresponds to the reciprocal of the phase-only differential value, and the vertical axis corresponds to the correction magnification realized by the first correction coefficient.

  As shown in FIG. 13, in the embodiment, the calculation formula for obtaining the first correction coefficient is set so that the correction magnification decreases as the reciprocal of the phase-only derivative decreases. As a result, it is possible to make it harder to detect areas with narrow stripes expressed by color gradations in complex-time correlation images, such as the edge areas and corner areas described above, and suppress overdetection. can do.

  Furthermore, in the embodiment, the correction unit 105 corrects the difference image so as to relatively increase the brightness of a region having a small amplitude value, that is, a dark region in the complex time correlation image. By correcting in this way, it is possible to adjust the detection sensitivity so that dark areas such as the end areas and corner areas described above are less likely to be detected as abnormal.

  That is, the correction unit 105 calculates a second correction coefficient that is set such that the smaller the amplitude value is, the larger the correction magnification is, based on a predetermined calculation formula that uses the amplitude value. Based on the correction coefficient, the difference image corrected by the first correction coefficient is further corrected. More specifically, the correction unit 105 further corrects the real number indicating the value of the complex amplitude representing the difference image based on the first correction coefficient, based on the second correction coefficient. The corrected difference image with the correction coefficient of 1 is further corrected.

  FIG. 14 is a diagram for explaining a difference image correction method based on the amplitude value in the embodiment. In FIG. 13, the horizontal axis corresponds to the amplitude value, and the vertical axis corresponds to the correction magnification realized by the second correction coefficient.

  As shown in FIG. 14, in the embodiment, the calculation formula for obtaining the second correction coefficient is set so that the correction magnification increases as the amplitude decreases. Thereby, it becomes possible to make it difficult to detect dark areas in the complex time correlation image, such as the end areas and corner areas described above, as abnormal, and it is possible to suppress overdetection.

  In the embodiment, since the complex time correlation image as the original image that is the source of the difference image may include an abnormality that should be detected originally, the value of the phase-only differential and the amplitude of the original image may be included. If the detection sensitivity is corrected using the value, there is a possibility that the abnormality that should be detected is not detected.

  Therefore, in the embodiment, the correction unit 105 uses a restored image as an ideal image from which the abnormality that should be detected is removed at least for an area that is determined to have a sufficiently high possibility that the abnormality that should be detected is present. The difference image is corrected based on the phase-only differential value of the restored image and the amplitude value of the restored image.

  However, there is no inconvenience in correcting a region where there is no abnormality that should be detected by using a complex time correlation image as an original image. Therefore, in the embodiment, the correction unit 105 is based on the value of the phase only derivative of at least one of the original image and the restored image and the value of the amplitude of at least one of the original image and the restored image, that is, the original image. The difference image is corrected by properly using the data and the restored image data.

  That is, in the embodiment, the correction unit 105 converts the real number representing the value of the complex amplitude representing the difference image from the first correction coefficient based on the value of the phase-only differential of at least one of the original image and the restored image, and the original The difference image is corrected by setting a value corrected based on the second correction coefficient based on the amplitude value of at least one of the image and the restored image as a corrected difference value representing the corrected difference image.

  Returning to FIG. 1, the abnormality determination unit 106 performs abnormality determination based on data extracted based on the difference image corrected by the correction unit 105. More specifically, the abnormality determination unit 106 includes first difference data (absolutely related to a correction difference value in an area in which the correction difference value is greater than or equal to a predetermined size in the difference image corrected by the correction unit 105. Difference data) and the correction difference value of the entire region standardized (normalized, normalized) based on the average and standard deviation of the correction difference values of the entire region corresponding to the inspection target surface in the difference image corrected by the correction unit 105 The abnormality is determined based on the second difference data (relative difference data). In addition, in the abnormality determination, not only the first difference data and the second difference data but also other information can be considered.

  Hereinafter, processing executed in the embodiment will be described.

  FIG. 15 is a flowchart illustrating a series of processing executed when the inspection system according to the embodiment inspects the inspected object 150. In the following, it is assumed that the inspected object 150 is already fixed to the arm 140 and arranged at the initial position of the inspection.

  As shown in FIG. 15, the PC 100 according to the embodiment first outputs a fringe pattern for inspecting the object to be inspected to the illumination device 120 (S1501).

  The illuminating device 120 stores the fringe pattern input from the PC 100 (S1521). And the illuminating device 120 displays the stored fringe pattern so that it may change according to a time transition (S1522). Note that the condition for starting display by the illumination device 120 is not limited to storing the fringe pattern, and may be that the inspector performs a start operation on the illumination device 120, for example.

  Then, the control unit 103 of the PC 100 transmits an imaging start instruction to the time correlation camera 110 (S1502).

  Next, in accordance with the transmitted imaging start instruction, the time correlation camera 110 starts imaging for the inspection object 150 and a region including the periphery of the inspection object 150 (S1511). Then, the control unit 240 of the time correlation camera 110 generates intensity image data and time correlation image data (S1512). Then, the control unit 240 of the time correlation camera 110 outputs the intensity image data and the time correlation image data to the PC 100 (S1513).

  The control unit 103 of the PC 100 receives the intensity image data and the time correlation image data (S1503). Then, the image generation unit 104 generates a difference image from the received intensity image data and time correlation image data (S1504). Here, for convenience of explanation, description of an example in which an image other than the difference image is generated is omitted, but in the embodiment, not only the difference image but also the intensity image, the amplitude image, the phase image, and the like in S1504. Other inspection images that can be used for inspection can also be generated.

  Then, the correction unit 105 corrects the difference image generated in S1504 (S1505). More specifically, as described above, the correction unit 105 performs the first correction based on the value of the phase-only derivative of at least one of the original image and the restored image, using the real number indicating the value of the complex number representing the difference image. The difference image is obtained by setting a value corrected based on the coefficient and the second correction coefficient based on the amplitude value of at least one of the original image and the restored image as a corrected difference value representing the corrected difference image. Correct.

  Then, the abnormality determination unit 106 acquires information for abnormality determination from the difference image corrected in S1505 according to the processing procedure described below (S1506).

  FIG. 16 is a flowchart illustrating details of an information acquisition process for abnormality determination executed by the inspection system according to the embodiment.

  As illustrated in FIG. 16, the abnormality determination unit 106 of the embodiment first identifies an area where the correction difference value is greater than or equal to a predetermined size from the difference image corrected in S1505 (S1601). Then, the abnormality determination unit 106 acquires first difference data (absolute difference data) related to the correction difference value of the area specified in S1601 (S1602).

  In addition, the abnormality determination unit 106 calculates the average and standard deviation of the correction difference values of the entire region corresponding to the inspection target surface in the difference image corrected in S1505 (S1603). Then, the abnormality determination unit 106 corrects the entire region by standardizing the correction difference value of the entire region corresponding to the inspection target surface in the difference image corrected in S1505 based on the average and the standard deviation calculated in S1503. Second difference data (relative difference data) related to the difference value is acquired (S1604).

  When the process of S1602 in FIG. 16 ends, the process of S1506 in FIG. 15 ends, and the process proceeds to S1507. Then, the abnormality determination unit 106 performs abnormality determination processing based on the information (first difference data and second difference data) acquired in S1506 (S1507).

  Then, the control unit 103 determines whether or not the inspection of the inspection object 150 has ended (S1508).

  When it is determined that the inspection of the inspected object 150 is not completed (S1508: No), the arm control unit 101 can capture the surface of the inspected object 150 to be inspected with the time correlation camera 110. Then, arm movement control is performed according to a predetermined setting (S1509). When the arm movement control ends, the control unit 103 transmits an imaging start instruction to the time correlation camera 110 again (S1502).

  On the other hand, when it is determined that the inspection of the inspected object 150 has ended (S1508: Yes), the control unit 103 outputs an end instruction for notifying that the inspection has ended to the time correlation camera 110 ( S1510). As a result, a series of processes executed by the PC 100 is completed.

  Then, the time correlation camera 110 determines whether an end instruction has been received (S1514). If an end instruction has not been received (S1514: No), the processing from S1511 is performed again. On the other hand, when an end instruction is accepted (S1514: Yes), the process ends.

  Note that the inspecting process of the illumination device 120 may be performed by an inspector, or may be ended in accordance with an instruction from another configuration.

  With the above, a series of processes executed when the inspection system of the embodiment inspects the object to be inspected is completed.

  In the above-described embodiment, the example in which the intensity image data and the time correlation image data are generated using the time correlation camera 110 having the configuration illustrated in FIG. 2 has been described. However, the generation of the intensity image data and the time correlation image data is not equivalent to the time correlation camera 110 having the configuration shown in FIG. It can also be realized by an imaging system that performs various operations. For example, image data generated by a normal digital still camera is output, and the information processing apparatus superimposes a reference signal using the image data generated by the digital still camera as frame image data, thereby generating time-correlated image data. The time correlation image data may be generated by using a digital camera that superimposes a reference signal on a light intensity signal in the image sensor.

  As described above, the inspection system according to the embodiment uses a complex time correlation image as an original image represented by a complex number from the image data output from the time correlation camera 110, and the complex time correlation image on the image. An image generation unit 104 that generates a difference image indicating a difference between a restored image generated by performing processing using a Wiener filter that removes abnormalities as noise components, and phase limitation of at least one of the original image and the restored image Based on the differential value and the amplitude value of at least one of the original image and the restored image, the correction unit 105 that corrects the difference image, and the inspection object based on the difference image corrected by the correction unit 105 And an abnormality determination unit 106 that determines abnormality of 150 inspection target surfaces. According to such a configuration, an abnormal region such as an end region or a corner region of the inspection target surface of the inspected object 150 viewed from the time correlation camera 110 according to the phase-only differential value and the amplitude value of the restored image. Since the detection sensitivity for a region where the surface gradient changes abruptly regardless of the presence or absence, overdetection can be suppressed.

  Hereinafter, some modified examples of the embodiment will be described.

<First Modification>
In the above-described embodiment, the example in which the abnormal region is specified based on the local change (difference from the surroundings) of the phase, amplitude, and intensity has been described. However, the abnormal region is specified based on the difference from the surroundings. It is not limited to. For example, as a first modification, an abnormal region may be specified based on a difference from reference shape data (reference data) set (acquired) in advance. In this case, it is necessary to match the position and synchronization status of the spatial phase modulation illumination (stripe pattern) with the status when the reference data is set (acquired).

  In the first modified example, the abnormality determining unit 106 stores a phase image, an amplitude image, and an intensity image obtained from the reference surface, which are stored in advance in a storage unit (not shown), and a phase image and an amplitude image of the inspected object 150. And the intensity image, and whether or not there is a difference more than a predetermined standard for any one or more of the phase, amplitude, and intensity of light between the surface of the inspected object 150 and the reference surface judge.

  Hereinafter, in the first modification, an inspection system having the same configuration as that of the embodiment is used, and the surface of a normal inspection object is used as an example of the reference surface.

  In this case, while the illumination device 120 irradiates the fringe pattern via the screen 130, the time correlation camera 110 images the surface of a normal object to be inspected, and intensity image data, time correlation image data, Is generated. Then, the PC 100 generates a phase image, an amplitude image, and an intensity image from the intensity image data and the time correlation image data generated by the time correlation camera 110, and generates the generated phase image in a storage unit (not shown) of the PC 100. The amplitude image and the intensity image are stored.

  Then, the time correlation camera 110 captures an object to be inspected to determine whether or not there is a possibility of abnormality, and generates intensity image data and time correlation image data. Then, the PC 100 generates a phase image, an amplitude image, and an intensity image from the intensity image data and the time correlation image data, and then stores the phase image, the amplitude image, and the intensity image of a normal inspection object stored in the storage unit in the past. And compare.

  In the above comparison, the PC 100 determines that the comparison result between the phase image, amplitude image, and intensity image of a normal object to be inspected and the phase image, amplitude image, and intensity image of the object to be inspected are abnormal. It is assumed that data representing characteristics for specifying a region is output. Thereby, the PC 100 identifies each abnormal region of the phase image, the amplitude image, and the intensity image by identifying pixels (regions) whose characteristics for identifying the abnormal region are equal to or greater than a predetermined reference. be able to.

  According to the above procedure, in the first modification, it is possible to determine whether or not there is a difference from the surface of a normal inspection object, in other words, whether or not there is a possibility that an abnormality exists on the surface of the inspection object. Note that any method may be used as a method for comparing the phase image, the amplitude image, and the intensity image, and the description thereof will be omitted.

  In the first modification, an example in which data indicating characteristics for extracting an abnormal region is output based on a difference from the reference surface has been described. However, it is also conceivable to identify the abnormal region by combining the technique using the difference in the reference surface described in the first modification and the technique using the difference between the surroundings described in the embodiment. Note that any technique may be used as a technique for combining the technique of the first modification and the technique of the embodiment, and the description thereof is omitted here.

<Second Modification>
In the above-described embodiment, an example in which an abnormality (defect) of an inspection object is detected by moving a stripe pattern in the x direction has been described. However, when an abnormality (defect) in which the normal distribution changes sharply in the y direction perpendicular to the x direction is generated in the inspection object, the fringe pattern is moved in the y direction rather than in the x direction. It may be easier to detect defects. Therefore, as a second modification, an example in which a fringe pattern moving in the x direction and a fringe pattern moving in the y direction are alternately switched will be described.

  The illumination control unit 102 of the second modified example switches the stripe pattern output to the illumination device 120 at every predetermined time interval. Thereby, the illuminating device 120 outputs the some fringe pattern extended in the different direction with respect to one test object surface.

  FIG. 17 is a diagram illustrating a switching example of a fringe pattern output from the illumination control unit 102 according to the second modified example. As shown in FIG. 17A, in the second modification, the illumination control unit 102 first transitions the fringe pattern displayed by the illumination device 120 in the x direction. Thereafter, as illustrated in FIG. 17B, the illumination control unit 102 causes the stripe pattern displayed by the illumination device 120 to transition in the y direction.

  And the control part 103 of PC100 performed abnormality detection based on the time correlation image data obtained from the stripe pattern irradiation of FIG. 17 (A), and was obtained from the stripe pattern irradiation of FIG. 17 (B). Anomaly detection is performed based on the time correlation image data.

  FIG. 18 is a diagram illustrating an example in which the illumination control unit 102 according to the second modified example irradiates a surface including an abnormality (defect) 1801 with a fringe pattern. In the example shown in FIG. 18, an abnormality (defect) 1801 extends in the x direction. In this case, the illumination control unit 102 sets the fringe pattern to move in the y direction that intersects the x direction, in other words, in the direction that intersects the longitudinal direction of the abnormality (defect) 1801. With this setting, detection accuracy can be improved.

  FIG. 19 is a diagram showing the relationship between the abnormality (defect) 1801 and the stripe pattern on the screen 130 when the stripe pattern is changed in the y direction in FIG. In FIG. 18, the y direction corresponds to a direction orthogonal to the longitudinal direction of the abnormality (defect) 1801. As shown in FIG. 19, when an abnormality (defect) 1801 having a narrow width in the y direction and a longitudinal direction in the x direction crossing the y direction occurs, the light emitted from the illumination device 120 is In the y direction that intersects the x direction, the cancellation of the amplitude of light increases. Therefore, the PC 100 can detect the abnormality (defect) 1801 from the amplitude image data corresponding to the fringe pattern moved in the y direction.

  In the inspection system of the second modified example, when the longitudinal direction of the defect generated in the inspection object is random, the fringe pattern is displayed in a plurality of directions (for example, the x direction and the y direction crossing the x direction). Thus, the defect can be detected regardless of the shape of the defect, and the abnormality (defect) detection accuracy can be improved. Further, by projecting a fringe pattern that matches the shape of the abnormality, the abnormality detection accuracy can be improved.

<Third Modification>
Furthermore, the technique of the embodiment is not limited to the technique of switching the fringe pattern in order to perform abnormality detection in the x direction and abnormality detection in the y direction as in the second modification described above. Therefore, as a third modification, an example in which the fringe pattern output from the illumination control unit 102 to the illumination device 120 is simultaneously moved in the x direction and the y direction will be described.

  FIG. 20 is a diagram illustrating an example of a fringe pattern output from the illumination control unit 102 according to the third modified example to the illumination device 120. In the example shown in FIG. 20, the illumination control unit 102 moves the fringe pattern in the direction 2001.

  The stripe pattern shown in FIG. 20 includes a stripe pattern with one period 2002 in the x direction and includes a stripe pattern with one period 2003 in the y direction. That is, the stripe pattern shown in FIG. 20 has a plurality of stripes extending in the intersecting directions having different widths. Here, in the third modified example, it is necessary to make the width of the stripe pattern in the x direction different from the width of the stripe pattern in the y direction. Thereby, when generating the time correlation image data corresponding to the x direction and the time correlation image data corresponding to the y direction, the corresponding reference signals can be made different. Note that the period (frequency) of the change in the intensity of light due to the fringe pattern only needs to be changed. Therefore, the moving speed of the fringe pattern (stripe) may be changed instead of changing the width of the stripe.

  Then, the time correlation camera 110 generates time correlation image data corresponding to the stripe pattern in the x direction based on the reference signal corresponding to the stripe pattern in the x direction, and based on the reference signal corresponding to the stripe pattern in the y direction. Thus, time correlation image data corresponding to the stripe pattern in the y direction is generated. Then, the control unit 103 of the PC 100 detects abnormality based on the time correlation image data corresponding to the stripe pattern in the x direction, and then detects abnormality based on the time correlation image data corresponding to the stripe pattern in the y direction. I do. Thereby, in the 3rd modification, it becomes possible to detect regardless of the direction where a defect has occurred, and the detection accuracy of abnormality (defect) can be improved.

  The inspection program executed by the PC 100 of the above-described embodiment is a file in an installable format or an executable format, and is a computer such as a CD-ROM, a flexible disk (FD), a CD-R, a DVD (Digital Versatile Disk). It is recorded on a readable recording medium and provided.

  Further, the inspection program executed by the PC 100 of the above-described embodiment may be provided by being stored on a computer connected to a network such as the Internet and downloaded via the network. Further, the inspection program executed on the PC 100 according to the above-described embodiment may be provided or distributed via a network such as the Internet.

  As mentioned above, although embodiment of this invention and some modification were demonstrated, these embodiment and modification are shown as an example, and are not intending limiting the range of invention. These novel embodiments and modifications can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention. These embodiments and modifications thereof are included in the scope and gist of the invention, and are included in the invention described in the claims and equivalents thereof.

  DESCRIPTION OF SYMBOLS 100 ... PC, 104 ... Image generation part, 105 ... Correction | amendment part, 106 ... Abnormality determination part, 110 ... Time correlation camera, 120 ... Illumination device (illumination part), 130 ... Screen (illumination part).

Claims (6)

A planar illumination unit that gives periodic temporal and spatial changes in the intensity of light to the object to be inspected;
A complex time correlation image represented by a complex number from image data output from a time correlation camera or an imaging system that operates equivalently, and a Wiener filter that removes abnormalities on the image as noise components from the complex time correlation image. An image generation unit that generates a difference image indicating a difference between the restored image generated by performing the processing used;
The difference image is corrected based on a phase-only differential value of at least one of the complex time correlation image and the restored image and an amplitude value of at least one of the complex time correlation image and the restored image. A correction unit;
Based on the difference image after correction by the correction unit, an abnormality determination unit that determines abnormality of the inspection target surface of the object to be inspected;
An inspection system comprising: The correction unit corrects the difference image based on a first correction coefficient that is set such that a correction magnification becomes smaller in a region where the value of the phase-only differential is larger in the difference image.
The inspection system according to claim 1. The correction unit corrects the difference image based on a second correction coefficient that is set so that the correction magnification becomes larger in a region where the amplitude value is smaller.
The inspection system according to claim 1 or 2. The correction unit converts a real number representing a value of a complex number representing the difference image, a first correction coefficient based on a phase-only differential value of at least one of the complex time correlation image and the restored image, and the complex number. The difference corrected based on the second correction coefficient based on the amplitude value of at least one of the time-correlated image and the restored image is set as a corrected difference value representing the corrected difference image. Correct the image,
The inspection system according to any one of claims 1 to 3. The abnormality determination unit includes: first difference data relating to the correction difference value in a region where the correction difference value is greater than or equal to a predetermined size in the difference image after correction; and the inspection in the difference image after correction. Determining the abnormality based on the second difference data relating to the correction difference value of the entire region normalized based on the average and standard deviation of the correction difference value of the entire region corresponding to the target surface;
The inspection system according to claim 4. Complex number from image data output from a time-correlation camera or an imaging system that operates equivalently to image an inspected object illuminated by a planar illumination unit that gives periodic temporal and spatial changes in light intensity A difference image indicating a difference between the complex time correlation image represented by the above and a restored image generated by applying a process using a Wiener filter that removes an abnormality on the image as a noise component to the complex time correlation image. An image generation step to generate;
The difference image is corrected based on a phase-only differential value of at least one of the complex time correlation image and the restored image and an amplitude value of at least one of the complex time correlation image and the restored image. A correction step;
Based on the difference image after correction by the correction step, an abnormality determination step for determining an abnormality of the inspection target surface of the inspection object;
An inspection method comprising: