JPH01307645A - Inspecting method for sample - Google Patents

Abstract

PURPOSE:To shorten the inspection time extending over many items by deriving an absolute value of transmittivity of a sample, based on image data which has been obtained by bringing an illuminating part to image pickup and image data which has been obtained by bringing the sample to image pickup. CONSTITUTION:A CCD camera 1 is used for an image pickup device, a sample 6 such as a shadow mask, etc., is irradiated by a lighting equipment 7, and its transmission light is brought to image formation through a lens 3, desirably under the condition that no moire is generated between a periodic pattern and a picture element of the image pickup device. Subsequently, from image data at the time when there is no sample, data at the time when a sample has been put in, and data at the time when a shutter 4 has been closed, an absolute value of transmittivity of the sample is derived, and from its absolute value, a defect of the sample and unevenness and/or transmittivity of the pattern are inspected. In this regard, it is desirable to execute an inspection by performing a differential processing or a smoothing processing to each image data.

Description

Detailed Description of the Invention [Field of Industrial Application] The present invention relates to a shadow mask used in a cathode ray tube for a color television, a color separation filter for a color imaging device, a color filter for a liquid crystal display panel, and a mesh type used in an electron tube. Electrodes, VDT filters, mesh filters for filtration equipment, rotary encoders, linear encoders, ICs
Industrial products such as photomasks, Fresnel lenses, lenticular lenses, etc., in which units (hereinafter referred to as unit patterns) with certain optical properties and shapes are regularly and repeatedly arranged in a one-dimensional direction or two-dimensional direction, or in which unit patterns are regularly arranged. Defects, unevenness, transmittance, and patterns such as scratches, pinholes, sunspots, and dust on industrial products whose optical properties, shapes, and arrangement pitches in one and two dimensions are repeatedly arranged while gradually changing. This invention relates to a sample inspection method for automatically inspecting glass, colored films, etc. that do not have

[Conventional technology]

Conventionally, defect inspections of industrial products in which unit patterns are periodically and repeatedly arranged are usually carried out by visual or microscopic observation, but such methods require a large amount of time to inspect a large number of products. Various testing methods have been proposed because it requires a lot of manpower and lacks test accuracy and reliability because it is a sensory test.

For example, for industrial products with periodic patterns arranged at equal pitches, pattern recognition may be performed by examining a video signal obtained by a microscope imaging device that sufficiently resolves the arrangement unit and the shape of the defect. Defects are detected by means such as comparing with signals obtained by similarly photographing patterns without defects.

In addition, for products with periodic apertures, such as mesh-like electrodes for electron tubes, defects can be detected using optical F-Rier transform spatial filtering, which utilizes the diffraction phenomenon of light due to periodic patterns when irradiated with coherent light. Detected.

Next, a conventionally proposed method for inspecting periodic patterns efficiently and with high accuracy will be explained with reference to FIG.

In order to detect an abnormality in the opening area of a pattern having periodic openings as a unit pattern 51 as shown in FIG. Incandescent lamp 48 and diffuser 47 lit by 49
The pattern to be inspected 46 is illuminated by a transmitted illumination unit composed of a transmissive illumination section, and the inspection area is photographed by a TV camera 41. The image processing device 42 A/D converts the output signal of the TV camera into digital image data, and performs various image processing including addition and subtraction on the screen at high speed using a frame memory and an arithmetic unit. The control device 43 controls the image processing device 42 and a pattern movement mechanism composed of an XY stage 50 and a drive mechanism 45 to move the pattern.

In addition, in FIG. 7, 52 and 53 are unit patterns with defects.

In FIG. 6, the photographing conditions are such that changes due to the unit aperture of the video signal by the TV camera 41 can be ignored, for example, about 10 unit apertures 11 are included in the pattern area corresponding to one pixel, and the direction in which the pattern is moved and displaced is set by the TV camera. A case where the pattern variation distance in the scanning line direction 41 is an integral multiple of the pixel pitch will be explained with reference to FIG.

The light transmittance distribution on a straight line passing through a defective part of the pattern is as shown in FIG. 8(a), for example, and 53 in FIG.
A change 54 in light transmittance due to a defect whose opening area is larger than that of the normal pattern 51 as shown in FIG.
As shown by 52 in the figure, a change in light transmittance 55 due to a defect whose opening area is smaller than that of the normal pattern 51, that is, a black defect
is detected. In addition, when the video signal is scanned on the same line as in the case of Fig. 8 (a), it becomes as shown in Fig. 8 (b), and the gradual signal change (shading) due to uneven illumination of the pattern, uneven sensitivity of the imaging surface, etc. ), random noise generated in the video signal processing device, and local changes 56 in the signal due to dust adhering to the optical system.

By adding multiple frames of such video signals, the ratio of random noise components can be reduced to t/,/''i when the number of additions is N (Fig. 8(c)). When similar screen addition processing is performed by displacing the pattern, the signal due to the defect on the pattern also moves as the pattern moves, as shown in Figure 8(d), but the shading of the imaging system and the signal due to the defect on the pattern also move. The position of the signal 56 has not changed due to dust etc. in the optical system.
When the data shown in Figure 8(d) is subtracted from the data shown in c), the signal 5G due to shading and dust contained in both data is erased, and the signal due to the change in light transmittance of the pattern and the reduced random noise component are removed. Only one thing remains;
As a result, the signal due to a defect appears with almost the same difference in value from the average value in the vicinity at a position where pixels are scattered according to the amount of movement of the pattern, and the sign appears reversed, and the order of reversal depends on the type of defect (white defect, black defect).

In the image data processed as above, the brightness changes locally only in the defective area, so it can be easily recognized as a defect by observing it on a monitor, and the brightness at the defective area is reversed relative to the surrounding area. It is also possible to identify the type of defect in the order of .

In addition, in the case of a shadow mask, defects are detected not only by the shape of the aperture on the horizontal projection plane, but also by abnormalities in the cross-sectional shape of the aperture and scratches on surfaces other than the aperture. It is also required to detect foreign matter such as dust attached to the surface separately from other defects, and the conventional method for this purpose is shown in Figure 9.
This will be explained with reference to FIG.

In Figures 9 and 10, if transmitted light illumination (i3 hyperbright field illumination) is used, defective apertures with large aperture areas are treated as white defects, and defective apertures with small aperture areas and positions that block the apertures. Foreign matter 61 can be detected as a black defect, and if reflected illumination light (reflected dark field illumination) is used, scratches 62 and foreign matter 61 on the shadow mask surface can be detected, and foreign matter that blocks the opening can be detected as a white defect. can do. Defect detection is then performed using these different illumination methods, and the location and type of detected defects (white defects,
By examining data such as black defects) and signal levels, the type of defect can be identified in more detail.

Furthermore, as shown in Fig. 11, if the imaging method is set to oblique imaging, it becomes possible to detect defects in the cross-sectional shape of the aperture that cannot be detected by imaging from the vertical direction. Defect detection is performed multiple times sequentially from at least two or more directions as the rotation axis, and if no defects are detected in any of those cases, the shadow mask has defects as shown in Figure 10. It can be determined that 63 did not exist.

Next, a method of moving the pattern will be explained.

As shown in FIG. 12, there are inspected object positions P0 to P, and the above-mentioned movement corresponds to P and P in this figure. In this case, if processing is performed using only image data obtained from two locations, the gap caused by a change in the aperture ratio in the H direction in the figure will be detected, but if the change occurs in another direction, for example in the V direction, the gap will be detected. Although there is a drawback that anisotropy in detection sensitivity occurs in that large gaps with small changes in the H direction are not detected, for example, the image obtained by imaging at P, , P, , P, , Pl, P in the same figure. Based on the data, P, and P+, Pa and Pl, P, and P
The anisotropy can be eliminated by performing predetermined processing on each of the combinations of s, Po, and P. Also, P in the figure
Even if detection is performed based on the image data obtained by subtracting the sum of image data at each position arranged on the circumference from the image data at the center position P0, such as from , to P, the anisotropy is similarly detected. A value that approximates the curvature of the brightness distribution that can be avoided and that is easily visually responsive can be obtained, resulting in inspection results that are close to visual inspection. The image data obtained by imaging at each position includes the aforementioned random noise component, shading component, and fixed noise component, and the random noise component is obtained by adding multiple frames at each moving position. In addition, shading components and fixed noise components can be eliminated by performing calculations on image data such that the sum of the number of frames of image data becomes "0". For example, P in Figure 12,
Add 32 frames at the position and 8 frames at P, and from the image data obtained by multiplying the image data at Pl by 4, P
, the sum of both image data is ``
0'', and the shading component and fixed noise component are eliminated. In addition, if the screen addition for 4 frames is performed at each position from P to P, then from Pl to P
The addition result of the image data of Il corresponds to the addition result of the image data of 32 frames, so if it is subtracted from the result of adding the image data of 32 frames at the position of Po, the shading component and fixed Noise components are eliminated, and a two-dimensional differential value of the brightness distribution is obtained. moreover,
By applying smoothing processing to the image data whose shading components and fixed noise components have been reduced through the processing described above, the random noise components are further reduced, making it possible to detect extremely slight unevenness components and to detect minute defects. It is also possible to suppress changes in image data due to short period irregularities.

A method has also been proposed for automatically determining whether a product is good or bad based on image data that has been subjected to the above-described image processing.

Figure 13 shows an example measured under the same conditions as Figure 8, and Figures 13 (a) to (e) are the same as Figure 8, where A is a part where the aperture ratio changes gradually, and B is a part where the aperture ratio changes gradually. C is a part where the aperture ratio changes periodically, C is a large and isolated part, D is a local change component (fixed noise component) of the video signal due to dirt in the optical system, etc. be. It can be seen in FIG. 13(e) that components due to changes in the aperture ratio of the object to be inspected are extracted. In this case, the amount of movement of the object to be inspected varies depending on the state of the unevenness to be detected, but as the period of variation of the unevenness increases, the amount of movement of the object to be inspected also increases, which is converted into the number of pixels in the frame memory. The number of pixels is set to about 2 to 20 pixels. Next, by subtracting the average value of the image data in a sufficiently wide 9i range from the image data in FIG. 13(e), the result is as shown in FIG. 13(f), and the image in FIG. 13(e) is When the data is differentiated, it becomes as shown in Figure 13 (g), and by setting a predetermined darkness value S, , S, according to the nature of the unevenness to be detected, it is possible to automatically detect unevenness. . Figure 13(h) is
) threshold values S+ and St are set for the image data of ), and the binary data is shown as "1" when the threshold value is exceeded, and as "0" when it is not exceeded. If an isolated unevenness as shown in C of Fig. 13(a) is detected and the product is determined to be defective, a dark spot such as Sl may be detected in the image data of Fig. 13(f) or (g). Just set the value.

In addition, when detecting periodically changing unevenness as shown in B in FIG. 13(a) and determining the product as defective,
) or (g), set a darkness value such as S2, convert it to binarized data as shown in FIG. i) The number of irregularities in a predetermined area as shown in (i) is converted into density data, and a predetermined threshold value S is set for this density data and compared to determine only irregularities that change periodically. It is possible to detect whether the product is good or bad based on the results.

In addition, to measure the light transmittance and its distribution of light-transmitting articles, and the aperture ratio and its distribution of industrial products with periodic apertures such as shadow masks, meshes, and cloth, a projector 73 is used as shown in FIG. The light transmittance was measured based on the output of the light receiver with and without a sample intervening, or in a light shielded state.

[Problem to be solved by the invention]

However, the method of examining the video signal obtained by a microscopic imaging device requires mechanical precision depending on the size of the defect to be detected, which makes the equipment expensive, and because the imaging is performed using a microscopic method. There is a problem in that the size of the screen that can be processed at one time becomes smaller and it takes a lot of time to inspect the entire pattern to be inspected.

In addition, the optical Fourier transform spatial filtering method, which utilizes the diffraction phenomenon of light due to periodic patterns, can improve inspection speed,
Although the detection sensitivity is excellent, a spatial filter must be created for each pattern to be inspected, and a precise optical system is required, making the device expensive. There was a problem in that the magnitude relationship with respect to the reference value could not be determined.

In addition, with the methods shown in FIGS. 6 to 13, if there is a change in transmittance, it is not known whether it is due to a defect in the pattern or due to noise or dust attached to the imaging device. Because it is necessary to repeatedly move the pattern and integrate the frame, it takes time to measure, and
It was not possible to measure the magnitude of the transmittance itself or its distribution, only by observing the change in transmittance.

In addition, in the method shown in Fig. 14, when measuring the transmittance of a dome swell used in a cathode ray tube, as shown in Fig. 15, originally, the transmittance is It is necessary to measure the ratio, but if you try to measure it with a set of emitters and receivers, you will need to mount the emitters and receivers at an angle as shown in Figure 16.
Therefore, there was a problem that the structure became complicated.

Although each method can inspect individual items, it is not possible to inspect all items from image data obtained by one-time imaging.

The present invention is intended to solve the above-mentioned problems, and provides a sample inspection method that allows inspection of various items to be performed in a short time through image processing from image data captured once for each sample. The purpose is to

[Means to solve the problem]

For this purpose, the present invention includes an illumination means and an imaging means,
The absolute value of the transmittance of the sample is determined based on the image data obtained by imaging the illumination section and the image data obtained by imaging the sample illuminated by the illumination section, and the quality of the sample is inspected from the absolute value. It is characterized by a cooling type CC as an imaging means.
D, and the image data obtained by imaging the illumination part is stored and used for each sample.
In the case of a periodic pattern, detection is performed under imaging conditions that do not cause moire between the pixels of the imaging device, and furthermore, each image data is subjected to differential processing or smoothing processing, and the level of each image data is approximately equal. Imaging conditions are set so that defects, pattern unevenness, and/or transmittance of an object to be inspected consisting of a repetitive arrangement of unit patterns such as a shadow mask are inspected.

[Effect]

The present invention calculates the transmittance distribution from image data captured in advance of the light source and image data obtained when the sample is illuminated, and detects defects, pattern irregularities, and other abnormalities in the transmittance distribution in a single measurement.
This is used to test transmittance, etc. By using a cooled CCD camera, dark current and noise can be significantly reduced to a negligible level, and the absolute value of transmittance can be measured, making it possible to measure the absolute value of transmittance. There is no need to move the sample and take the difference in order to eliminate noise components, which can significantly shorten inspection time, and it is also possible to perform image processing such as differential processing and smoothing processing on the obtained image data. This makes it possible to test all items in one measurement.

〔Example〕

Examples will be described below based on the drawings.

FIG. 1 is a diagram showing an embodiment of the present invention using a cooled CCD camera as an imaging device, and in the figure, 1 indicates a cooled CCD camera.
2 is a camera, 2 is an image processing device, 3 is a lens, 4 is a shutter, 5 is a shutter drive device, 6 is a sample, 7 is an illumination device, 8
is the power supply.

A cooled CCD camera is a CCD camera that is cooled using an electronic cooling method, etc. to significantly reduce dark current and noise to a negligible level, and is capable of long exposures in dark areas. It is characterized by its excellent image quality, and can clearly capture dark areas that could not be captured even with conventional high-sensitivity television cameras.
It is possible to detect up to several photons per pixel per second.

Using such a CCD camera 1, a sample 6 is irradiated by an illumination device 7 driven by a power source 8, and the transmitted light is formed into an image through a lens 3. In this case, conditions such as blurring the focus with lens 3 or 1
A plurality of unit patterns are arranged in a pattern area corresponding to a pixel.

At this time, image data taken without the sample is shown as 11, image data taken with the sample inserted is shown as ■, and image data taken with the shutter 4 closed is shown as ■. Then, the transmittance T at a point on the sample can be calculated as 1.-1°. Here, ■, I6, and ■1 are image data at corresponding positions, and if the image data when the shutter is closed (light amount = 0) can be ignored, then T-1/T.

The transmittance is obtained as . This calculation can be performed by inter-screen calculation after each image data is stored in the frame memory by the image processing device 2. If the number of pixels of the cooled CCD camera is 512 x 512, this calculation will result in approximately 2
Transmittance data for 50,000 points will be obtained. The re-imaging data obtained in this way does not contain components such as shading or dust in the imaging system, so by performing image processing according to each inspection item as described above on this image, it is possible to perform a single measurement. It is possible to perform the inspection at

Further, if the light source is stable, the image data I is stored in the memory and used, thereby eliminating the need to perform measurement for each sample and reducing the measurement time.

With ordinary solid-state image sensors and image pickup tubes, the linearity of the light intensity and video signal is not sufficient, and the influence of thermionic electrons is large, making it difficult to perform high-precision measurements. are spatial resolution, linearity, S/N
was good, but there was a problem that the imaging time was long (
(about 1 ms per pixel, about 4 minutes for 250,000 pixels), but in the present invention, by using a cooled CCD camera 1, an image can be captured in about several seconds, and linearity is also good.

In addition, defect detection is performed on image data by performing differential processing on image data, which is equivalent to the result of conventional imaging (frame integration) → sample movement → imaging (frame integration), without moving the sample. After this is obtained, defects can be detected by performing similar image processing. In this case, feature extraction may be performed by using spatial filters of differential processing as shown in FIGS. 2(a), (b), and (c). One-dimensional edge extraction can be performed by using a filter, as shown in Figure 2 (c
) can be used to perform two-dimensional edge enhancement. Then, the spatial filter can be selected depending on the image data variation, resolution characteristics, and the nature of the defect to be detected (see Figure 2 (C) for white/black defect identification).
Determine the size of the pixel of interest using the spatial filter of
It can be identified by the size of the pixel of interest relative to surrounding pixels.

Furthermore, by using the spatial filter shown in Fig. 2(C) for the detection and judgment of unevenness, the same results as when performing a series of imaging operations as explained in Fig. 13 can be obtained, and in the case of Fig. 13, Similarly, detection and judgment can be performed by performing screen addition processing and setting the darkness value.

By the way, in the transmittance measurement method shown in Fig. 1, - Variations in data for each pixel directly affect the data, so in order to perform highly accurate measurements, image data of a small area centered around the measurement point, for example 5. It is necessary to calculate an average value such as ×5 pix to 10×10 pix. If the number of measurement points is limited, the time required for calculation by the CPU can be reduced, but if the number of measurement points is large, the processing by the CPU will require a lot of time. If predetermined image data is read out after performing smoothing filter processing, which is a type of image processing, on the frame memory that has been stored, speeding up can be achieved.

As mentioned above, the cooled COD is characterized by good linearity of the video signal with respect to the integrated scene, but when measuring a sample with low transmittance, it is necessary to use image data captured without a sample. Even if it is set to 1σ, which is close to max, the value of the image data (2) captured by inserting the sample becomes small, and slight errors in linearity, dark current, etc. affect the transmittance value.

Therefore, when capturing images of ■ and 11, it is better to capture images so that the data levels of these two images are approximately equal and have sufficient size, and in that case, image processing requires , correction calculations are required.

One way to do that! , the exposure time during imaging is
Operate the shutter so that the ratio becomes 1/T when ■ and 1.
1 can be set to approximately the same value.

However, mechanical shutters have the disadvantage that the operating time varies, so the error becomes large especially when the shutter open time is short. If this error cannot be ignored, measure the shutter open time and use that value. Just correct the data.

FIG. 3 is a diagram showing another embodiment of the present invention for realizing this, and the same numbers as in FIG. 1 indicate the same contents. In addition, in the figure, 9 is a half mirror, 11O is an optical sensor, 1
1 is a measuring device.

In this embodiment, a sensor 10 detects a part of the light when an image is captured by a half mirror 9, and a measuring device 11 measures the time during which a detection signal is obtained, thereby determining the exposure time.

Correct the data using the exposure time obtained in this way, and
The two image data levels of 1 can be made approximately equal.

In addition, by changing the storage time of the cooled CCD, for example, the image data (2) captured with the sample inserted is longer than the image data (1) and (11).
may have the same level. In this case, the time can be set with sufficient precision, but if the light transmittance is low, the time to image ■ is 1/T times that of ■. Sometimes it takes 1000 times more time.

Also I and 1. Similar results can be obtained by changing the brightness of the light source when taking images.

In the conventional method using a light emitter/receiver shown in Figs. 14 and 16, the number of measurement points is limited, so it is difficult to obtain transmittance data at a fixed position on a sample with a predetermined shape, such as a shadow mask. In this case, the sample had to be positioned with respect to the measurement system before being measured. In contrast, in the method of the present invention, transmittance data is obtained as high-resolution image data, and this image data is processed to automatically recognize the position and rotation of the sample to obtain data at a predetermined position. This allows for easy automatic measurement.

In addition, changes in the product to be measured can be handled simply by changing the program without mechanical adjustment.

FIG. 4 is a diagram showing a measurement method when changes in measured values such as fluctuations, dispersion, and drift of illumination light pose a problem.

In this embodiment, the field of view 2 provided by the illumination device 7 for the sample 6 is
1 is enlarged as shown in Figure 2, a reference plate 22 with a constant transmittance is placed in the imaging area so that there is a part that is not obstructed by the sample, and the image data of the reference plate is acquired for each imaging data. If read out, for example, if the intensity of the illumination light fluctuates, the exposure amount of the reference plate 22 will also fluctuate, so by making corrections using this data, fluctuations in the illumination light can be corrected. It is possible to eliminate the influence and improve reproducibility.

As mentioned above, the transmittance measurement of the shadow mask must originally be carried out in the beam direction within the cathode ray tube, and the measuring method in this case will be explained with reference to FIG.

FIG. 5 is a diagram showing another embodiment of the present invention, in which 31 is a light source, 32 is a Fresnel lens, and 33 is a shadow mask.

In the figure, by illuminating and exposing a shadow mask with light from a light source 31, and selecting a photographing angle in relation to the distance to the sample and the photographing area of the cooled COD camera, the beam direction relative to the shadow mask within the cathode ray tube is adjusted. Measurement can be performed using an approximate angle θ.

In this case, if parallelism of the illumination light at each point in the measurement area is required, the Foursnel lens 32 can be used as a condensing lens as shown in the figure to accommodate large-area samples such as shadow masks and aperture grilles. Can be measured with a simple lighting device.

Although the method for inspecting periodic patterns has been explained above, images with negative signal levels can be obtained even when images are taken without periodic patterns, such as on glass or transparent films with colored layers. The present invention can be applied to any type of material.

〔Effect of the invention〕

As described above, according to the present invention, the transmittance distribution is determined from the image data captured in advance of the light source and the image data when the sample is illuminated, and defects and patterns can be detected from abnormalities in the transmittance distribution in a single measurement. This is used to inspect unevenness, transmittance, etc. By using a cooled CCD camera, dark current and noise can be significantly reduced to a negligible level, and the absolute value of transmittance can be measured. There is no need to move the sample and take the difference in order to eliminate noise components, which greatly reduces inspection time, and allows image processing such as differentiation and smoothing to be performed on the obtained image data. By doing so, it becomes possible to test all items in one measurement. If the light source is stable, the stored image data without a sample can be used, and various inspections can be performed, making high-speed automatic inspection possible. In the case of a shadow mask, sample exchange and detection judgment processing proceed in parallel in 1 second of imaging, so it takes several seconds.
Automatic cycle inspection becomes possible. In addition, if it is necessary to improve the data accuracy for each screen, frame integration may be performed, such as shadow masking or AG (abercagrill).
When applied to
It has the advantage of being able to inspect in the beam direction. In addition, in the inspection method of the present invention, the depth of focus is not a problem because the focus is blurred, for example, to prevent moire from occurring between the periodic pattern and the pixels of the imaging device, and therefore molded products are also subject to inspection. Is possible.

[Brief explanation of the drawing]

FIG. 1 is a diagram showing one embodiment of the present invention, FIG. 2 is a diagram showing a spatial filter, FIG. 3 is a diagram showing another embodiment of the present invention in which exposure time is measured, and FIG. 4 is a diagram showing an embodiment of the present invention. FIG. 5 is a diagram showing another embodiment of the present invention in which fluctuations in illumination light and changes in measured values are corrected; FIG. 5 is a diagram showing another embodiment of the invention in which the photographing angle is adjusted; FIG. 7 is a diagram for explaining a conventional periodic pattern inspection method. FIG. 7 is a diagram for explaining a periodic pattern and its defects. FIG. 8 is a diagram for explaining a conventional detection method. FIG. 9 , FIG. 10 and FIG. 11 are diagrams for explaining the illumination method, FIG. 12 is a diagram for explaining the pattern movement method, and FIG. 13 is a diagram for explaining the method for automating inspection. Figure 14 shows the conventional transmittance measurement method using a light emitter and receiver, Figure 15 shows the angle of incidence of the beam on the shadow mask, and Figure 16 shows the angle of the transmitter and receiver relative to the sample. FIG. 1... Cooled CCD camera, 2... Image processing device,
3... Lens, 4... Shutter, 5... Shutter drive device, 6... Sample, 7... Illumination device, 8...
Power supply, 9...half mirror, 10...light sensor, 1
1... Measuring device, 31... Light source, 32... Fresnel lens, 33... Shadow mask. Applicant Dainippon Printing Co., Ltd. Agent Patent attorney Masanobu Hirukawa (4 others) Figure 1 (a) (b) Figure 4 Figure 5 Figure 6 Figure 7: ll': s1 - ○O ○○go- 1---○σ○○○- -○○q○○- : : : : S : Z : : Figure 8 Figure 9 Figure 10 End of page〒 Figure 11 Figure 12 Figure 14 Figure 15 Figure 16 Kure

Claims (8)

[Claims] (1) It has an illumination means and an imaging means, and calculates the transmittance of the sample based on the image data obtained by imaging the illumination part and the image data obtained by imaging the sample illuminated by the illumination part. A method for inspecting a sample, characterized by determining an absolute value and inspecting the quality of the sample based on the absolute value. (2) The method for inspecting a sample according to claim 1, wherein the imaging means is a cooled CCD. (3) The method for inspecting a sample according to claim 1 or 2, wherein defects, pattern unevenness, and/or transmittance are inspected. (4) The method for inspecting a sample according to claim 1 or 2, wherein image data obtained by imaging the illumination section is stored and used for each sample. (5) The sample inspection method according to claim 1 or 2, wherein the detection is performed under imaging conditions that do not cause moiré between the periodic pattern and the pixels of the imaging device. (6) The sample inspection method according to claim 1 or 2, wherein each image data is subjected to differential processing or smoothing processing. (7) The sample inspection method according to claim 1 or 2, wherein the imaging conditions are set so that the levels of each image data are approximately equal. (8) The method for inspecting a sample according to claim 1, wherein the sample is a shadow mask.