JPH0794974B2 - Inspection method for shed mask - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION Object of the Invention (Industrial field of application) The present invention relates to a unit (hereinafter referred to as a unit pattern) having a one-dimensional direction, which has optical properties and a shape of a shadow mask used for a cathode ray tube for a color television. Or, an industrial product or a unit pattern that is regularly and repeatedly arrayed in a two-dimensional direction is repeatedly arrayed while its optical properties, shape and array pitch in a one-dimensional direction and a two-dimensional direction are gradually changed. The present invention relates to an optical inspection method capable of automatically inspecting spots and local defects caused by nonuniformity of optical properties due to the shape, size, position, etc. of a unit pattern of existing industrial products.

(Prior Art) Conventionally, it is customary to rely on a naked eye or a visual method with a microscope for inspection of spots and defects generated in a shadow mask.
Also, as a means for inspecting only defects in industrial products that have a periodic pattern with an equal pitch array, such as some shadow masks, microscopic imaging that sufficiently resolves the array unit and the shape of the defects. A method for detecting and inspecting defects by means such as checking the video signal obtained by the means for pattern recognition or comparing a signal having no defect with a signal obtained by similarly photographing has been proposed. , There are also some examples.

In addition, as another means to inspect only for defects, for products with periodic openings such as shadow masks,
A defect inspection method has been proposed that applies a principle called an optical Fourier transform spatial filtering method that utilizes the diffraction phenomenon of light due to a periodic pattern when irradiating coherent light.

(Problems to be Solved by the Invention) According to the conventional method, the step of inspecting spots and defects generated in the shadow mask is usually performed with the naked eye or using a microscope, but a large number of products are required. There are problems that a large amount of manpower is required for the inspection and that the sensory inspection is lacking in reliability and inspection accuracy.

Further, according to the method using the video signal obtained by the microscopic photographing means, the mechanical accuracy according to the size of the defect to be detected is required, and the high accuracy is required for detecting the minute defect. Since the device is required, the device is expensive, and the size of the screen that can be processed at one time is small because it is microscopic imaging, and it takes a lot of time to inspect the entire pattern to be inspected. There was a problem.

Furthermore, according to the method using the optical Fourier transform spatial filtering method, although the inspection speed and the detection sensitivity are excellent, a spatial filter must be created for each pattern to be inspected, and a precise filter is required. Since an optical system is required, the apparatus becomes expensive, and a defect can be detected, but there is a problem that the size relationship of the defect opening with respect to the reference value cannot be determined.

The above-mentioned inspection method using the video signal and the inspection method using the optical Fourier transform spatial filtering method have not only the above-mentioned problems, but also the problem that they cannot deal with the inspection of the shadow mask spots at all. .

Therefore, an object of the present invention is to provide a method capable of simultaneously inspecting spots and defects of a shadow mask with the same inspection device with high efficiency and high accuracy.

[Structure of Invention]

(Means for Solving the Invention) The present invention does not sufficiently resolve the unit pattern of the shadow mask. Or, even in the case of a large-area influential field of view that does not resolve at all, paying attention to the fact that the video signal obtained by imaging the imaging field of view contains information about the defect and the aperture ratio of the shadow mask, Random noise components contained in the video signal, by eliminating unnecessary components such as shading components and fixed noise components, to extract signal components due to defects and spots on the shadow mask,
The defect and spot of the shadow mask are inspected based on the signal component.

Then, the shadow mask pattern is divided into a plurality of pixels by an image input device, stored as digital data for each pixel in an image memory in frame units, and means for obtaining image data in frame units, and the image data The periodic pattern by suppressing the random noise component generated in the obtaining step, the shading component caused by the luminance distribution of the light source, and the pulsed noise (hereinafter referred to as fixed noise) caused by the dirt attached to the optical system or the product. With the means for facilitating recognition by extracting the spot component of No. 1 and the means for judging good or bad of the product based on the image data obtained as described above, the above-mentioned object is achieved. is there.

(Operation) According to the present invention described above, the defect and spot components can be emphasized and displayed by applying the digital image processing technique to extract the defect and spot components of the shadow mask. In the visual inspection process, if used as an auxiliary means for visual recognition, there is an effect that defects and spots that are difficult to catch by the conventional method can be easily recognized at the same time.

Furthermore, by comparing the extracted defect and spot components with the judgment criteria by electrical means, it is possible to automate the defect and spot inspection, so that a great deal of manpower is not required, and it is possible to match the flow of the manufacturing process. It also has the effect of enabling quick and accurate inspection.

(Examples) Hereinafter, the present invention will be described in more detail based on the illustrated examples.

FIG. 1 is a block diagram showing an example of an apparatus for carrying out the method according to the present invention. In the figure, 1 is a TV camera, 2 is an image processing device, 3 is a control unit, 4 is an image display, and 5 is a drive mechanism. , 6 is a shadow mask, 7 is a diffuser, 8 is an incandescent lamp, 9 is a DC power supply, 1
0 indicates the XY stage. To explain the operation of the present invention, first, the shadow mask 6 is illuminated by the transillumination unit composed of the incandescent lamp 8 and the diffuser plate 7 which are turned on by the DC power supply 9, and the shadow mask 6 is illuminated by the TV camera 1. A video signal obtained by photographing the inspection area of is input to the image processing apparatus 2, the video signal is A / D converted in the image processing apparatus, stored in the frame memory, and the processing described later is performed. At the same time, under the control of the control device 3, the inspection object moving mechanism including the drive mechanism 5 and the XY stage 10 moves the inspection region to inspect the shadow mask 6 for defects and spots.

FIG. 2 shows an example of the shadow mask 6, which is a periodic pattern having periodic openings as the unit pattern 11. In the figure, 12 and 13 indicate defective unit patterns, 12 is an example in which the opening area is smaller than the surrounding regular unit pattern opening, and 13 is an opening from the surrounding regular unit pattern opening. An example where the area is large is shown.

FIGS. 3A to 3I schematically show the data corresponding to each processing step as an analog waveform in order to explain the processing contents of the image processing apparatus 2 and the effect thereof.

FIG. 3A is an example of the aperture ratio distribution of the shadow mask 6, and is an imaging condition such that the shape of the unit pattern 11 is ignored in the video signal waveform of the TV camera 1, for example, 1 in the frame memory of the image processing apparatus 2. The figure shows the case where the imaging condition is such that there are about 10 unit patterns 11 on the shadow mask 6 corresponding to the pixels. In the figure, A indicates a portion where the aperture ratio changes slowly, and B indicates that the aperture ratio is periodic. , C has a large change in aperture ratio, and is an isolated part, and E ₁ is a defect 13 having a larger opening area than the surrounding regular unit pattern opening shown in FIG. It corresponds to each such defective part.

FIG. 3B shows the TV camera 1 input to the image processing apparatus 2.
The video signal waveform for one scanning line corresponds to the aperture ratio distribution shown in FIG. 3 (a), and the non-uniformity of the illuminance distribution of the transillumination unit and the non-uniformity of the sensitivity distribution of the image pickup surface. A signal component (shading component) showing a gradual change due to uniformity, a random noise component generated in the video signal processing circuit, and a local change component (fixed noise component) D of the video signal due to contamination of the optical system It is shown.

FIG. 3 (c) shows image data as a result of suppressing the random noise component by the image processing device 2. By storing the video signal in the frame memory and adding N frames, While the signal component that does not change in increases, the random noise component has no correlation between frames, so the average amplitude is The random noise component is suppressed by utilizing the attenuation to. Although N frame memories may be used, the same effect can be obtained by using one frame memory in a cyclic structure.

Further, in FIG. 3 (d), after the inspection object 6 is slightly moved,
The result of suppressing the above-mentioned random noise component is shown.

3 (e) is image data obtained by subtracting the image data shown in FIG. 3 (d) from the image data shown in FIG. 3 (c). Of the shading components and fixed noise components included in the image data of the shadow mask 6 that do not change due to the minute movement of the shadow mask 6 are erased, and the components due to the change of the aperture ratio of the shadow mask 6 are extracted, resulting in reduction. Random noise component and change component (DC component) of average value of image data due to slight fluctuation of illumination light intensity and sensitivity of image pickup system before and after the movement are shown to remain. . The movement amount of the minute movement of the shadow mask 6 is
Although it depends on the state of the spots to be detected, the amount of movement of the shadow mask 6 also increases with an increase in the period in which the spots change, and in this embodiment, it is 2 in terms of the number of pixels in the frame memory.
An appropriate value is in the range of 20 pixels from pixels.

The above shows the method of extracting the defect and spot component by processing the shadow mask 6 minutely in the one-dimensional direction once and processing it based on the image data between two screens obtained before and after the shadow mask 6. However, the same result can be obtained by subtracting the image data of the screen after the movement from the image data obtained by performing the screen addition before the movement by the same number of screens as the number of the screen addition. Further, the processing at that time can be performed by the frame memory for one screen.

4 (a) and 4 (b) schematically show the moving position for explaining the moving method when the shadow mask 6 is moved minutely, and P ₀ to P _{8 in the} drawing show the shadow mask 6 respectively. It corresponds to the imaging position of. For example, the positions imaged by the above movement correspond to P ₀ and P ₁ in FIG. However, regarding the spots, when the processing is performed only with the image data obtained from these two locations, the spots caused by the change in the aperture ratio in the H direction in FIG. For example, there is a defect that anisotropy of detection sensitivity occurs in that a spot having a large change in the V direction and a small change in the H direction is not detected. For example, P ₀ , P ₁ , P ₂ , P _{3 in FIG.} , based on the image data obtained by imaging at P _4, and P ₀ and P _1, P ₀ and P _2, P ₀
By performing the process described in FIG. 3 (e) for each of the combinations of P ₃ , P ₀ and P ₄ , the anisotropy is eliminated because the change in each direction can be detected. Also from P ₁ of FIG. 4 (a) P ₈ or, in the center position P ₀ the sum of image data at each position which are arranged on the circumference as in the fourth diagram (b) P ₁ from P ₄ of Even if the detection process is performed based on the image data obtained by subtracting from the image data, the above-mentioned anisotropy can be avoided, and the curvature (or the second derivative) of the brightness distribution that is easy to visually react is calculated. Image data corresponding to the approximated value is obtained, and the inspection result is close to the visual inspection.

Further, in FIGS. 4A and 4B, the distance R between the center point P ₀ and its periphery indicates the movement distance of the shadow mask. When the distance R is set to a small value, it becomes easy to detect a minute defect, and when the distance R is set to a large value, it is easy to detect a spot having a long cycle and caused by a change in aperture ratio. is there. Therefore, the distance R
The value of is determined in consideration of the properties of defects and spots to be detected.

By the way, although the description has been centered on the method of moving the shadow mask 6, the image data obtained by imaging at each position includes the above-described random noise component, shading component, fixed noise component, and the like. A method for reducing these unnecessary components will be described below. First, the random noise component can be suppressed by adding a plurality of frames at each moving position shown in FIG. 4A in the same manner as the above-mentioned method. Further, the shading component and the fixed noise component can be erased by calculating the image data so that the total number of frames of the image data becomes "0".

For example 32 frames at a position P ₀ of 4 (a), at P ₁ 8
If the image data at P ₀ is calculated from the image data obtained by multiplying the image data at P ₁ by four by adding the frames, the image data corresponding to 32 frames will be added to both image data. The sum of the number of frames of the image data subjected to the arithmetic processing, which is obtained by subtracting between the two image data, becomes "0", and the shading component and the fixed noise component are erased.

The addition / subtraction multiplication is performed for each pixel of each frame. For example, with respect to image data in frame units imaged at the position P ₀ and each position P ₁ , each pixel of image data in frame imaged has a value corresponding to the signal amount in a memory of several bits. It is recorded and digitally added and subtracted for each pixel. As another example, when screen addition for 4 frames is performed at each position of P ₁ to P ₈ in FIG. 4A, the addition result of the image data of P ₁ to P ₈ is 32. Since it corresponds to the addition result of the image data of the frame, if the subtraction is performed from the addition result of the image data of 32 frames at the position of P ₀ , the shading component and the fixed noise component are erased and the brightness is increased as in the above example. The second derivative of the distribution is obtained.

Furthermore, when smoothing processing is applied to image data with reduced shading components and fixed noise components by the above processing, random noise components are further reduced, making it possible to detect extremely small spot components. Further, it is also possible to suppress a change in image data due to a minute defect or a spot having a short period and select and detect a spot component having a long period.

If the above-described processing is performed on the entire area of the inspection object 6 and the obtained image data is observed on the image display 4, only the portion where the spots or defects appear appears as a change in the brightness level. Spots and defects can be easily recognized.

Next, a method of automatically determining whether the product is good or bad based on the image data subjected to the above image processing will be described.

FIGS. 3 (f) and 3 (g) show image data obtained by removing the DC component from the image data of FIG. 3 (e), and FIG. 3 (f) shows the image shown in FIG. 3 (e). Image data obtained by subtracting the average value of image data in a sufficiently wide area of data,
FIG. 3 (g) shows image data obtained by differentiating the image data of FIG. 3 (e). Then, the spots are automatically detected by setting a predetermined threshold value (S ₁ , S ₂ ) according to the nature of the spots to be detected.

In FIG. 3 (h), thresholds S ₁ and S ₂ are set for the image data of FIG. 3 (g), and those exceeding the threshold are shown as “1”, and those not exceeding the threshold are shown as “0”. It is binary data.
To further explain the relationship between the threshold value and spots, first, in the case of detecting an isolated spot as shown by C in FIG. A threshold value such as S ₁ may be set for the image data. As another example, when a synchronously varying spot as shown by B in FIG. 3 (a) is detected and the product is defective, the images of FIGS. 3 (f) and (g) are displayed. After setting a threshold value such as S _{2 for} the data, it is converted into the binarized data as shown in FIG. 3 (h), and the predetermined value is converted from the binarized data as shown in FIG. 3 (i). Convert the number of spots in the area, that is, density data,
To said seal of data, by performing a comparison with a predetermined threshold value S _3, detect only plaques that changes periodically, it is possible to good or bad determination of product from the result, close to the visual inspection The test result is obtained.

Then, the defective portion in the aperture ratio distribution shown in FIG.
For the defect opening corresponding to E ₁ , the moving distance of the shadow mask is reduced so that the change in the image data due to the spots is suppressed, and the third opening is obtained from the image data obtained by taking the images at two adjacent image pickup positions. When the image data corresponding to FIG. 3F or FIG. 3G is converted, only the defect portion E ₁ has a large value. Therefore, it can be easily detected by comparing the predetermined value with the value. . Further, if the image pickup positions of the above-mentioned two points are determined so as to be an integral multiple of the pixel pitch with respect to the arrangement direction of the pixels of the image data, the defect signal E ₂ shown in FIG. , Above the average value of the signal level near E ₃ ,
It is also possible to discriminate the size of the opening area and remove false defects based on the lower symmetry. When the defect signal is observed using the image display 4, the type of defect (white dot / black dot) is identified in the order of light and dark inversion with respect to the surroundings at the defect portion.

Next, a description will be given of an example in which the above-mentioned image pickup means is configured to take an image at each image pickup point of the shadow mask at a shooting angle close to the incident angle of the electron beam with respect to the shadow mask installed in the cathode ray tube. FIG. 5 is an explanatory view showing the structure of the cathode ray tube, and FIG. 6 is an explanatory view showing the relationship between the TV camera 1 and the shadow mask 6 in the present invention. As shown in FIG. 5, the shadow mask is formed on a curved surface such as a part of a cylindrical surface or a part of a spherical surface according to the shape of the fluorescent surface of the cathode ray tube 15 or is held by a supporting member in most cases. .

Therefore, as shown in FIGS. 5 and 6, when the angle of view is set by the TV camera 1, the angle of incidence of the electron beam on the shadow mask in the cathode ray tube and the angle of the illumination light that contributes to the photographing are the same. Alternatively, if the angle of view is set to be the closest, the cause of the defective aperture shape or spots seen from the electron beam passing direction at each point on the shadow mask, that is, the defects or spots in the image displayed on the color TV CRT. It is possible to most appropriately detect the defect opening of the shadow mask and the unevenness of the aperture ratio.

Next, an example of automatically inspecting the defects and the spots caused by the periodical change of the aperture ratio of the shadow mask 6 according to the above-described embodiment will be described. The unit pattern 11 of the inspection object 6 has a diameter of 100 μm and an arrangement pitch of 300 μm, and a periodic pattern having an arrangement as shown in FIG. 2 is illuminated with transmitted light as shown in FIG. 300m with TV camera 1
A region of m × 220 mm is photographed, and as shown in FIG. 4 (b), at each photographing position of P _{0 to} P ₅ , R is set to 5 mm and Y is set to twice the pixel pitch, and P ₀ and P ₅ from each image data obtained by moving the shadow mask to the shooting position
As a result of processing based on the difference in the image data in, the defects having unit apertures having different diameters of 10 μm could be detected. Also, as a result of processing based on the image data obtained by subtracting the image data of P _{1 to} P ₄ from the image data of P ₀ , the change in brightness when observed with transmitted light was about 0.5% and visual inspection Detects changes in aperture ratio that are close to the detection limit of
It was possible to accurately determine the defect.

Furthermore, it was possible to determine the magnitude of the opening ratio with respect to the surrounding openings. The imaging method shown in the present invention is
Any video signal can be used as long as a video signal including information about spots and defects can be obtained. For example, a method such as a TV camera using an image pickup tube or a solid-state image pickup device (area sensor or line sensor), an image pickup apparatus using a photodetector and a flying spot tube, and the like can be given.

Further, the method according to the present invention is not limited to the inspection of a shadow mask, but an industrial product including a repeating arrangement of unit patterns, for example, a color stripe filter for a TV camera, a projection screen for an image, a color for a liquid crystal display device. It can also be applied to the inspection of spots and defects such as filters.

〔The invention's effect〕

As described above, according to the present invention, a minute defect or spot of a shadow mask is imaged with a wide field of view so that the unit aperture of the shadow mask is not resolved, and the image data is processed to obtain one type. It is possible to detect the defects and spots at the same time by the inspection apparatus and automatically determine the type of the defect (white dot / black dot).

Further, by displaying the processing result of the image data on the image display, by displaying the processing result of the image data, it is possible to easily visually recognize the defect or spot.

Furthermore, according to the present invention, since the sensitivity of the detection sensitivity to the resolution of the image pickup system is low, it can be easily applied to the inspection of a shadow mask that is molded or held in a three-dimensional shape such as a spherical shape or a cylindrical surface shape. This makes it possible to easily automate the inspection of spots and defects on the shadow mask over a wide range, and the effects of improving the inspection accuracy, reliability and efficiency can be obtained.

[Brief description of drawings]

FIG. 1 is a block diagram showing an example of an apparatus for carrying out the method according to the present invention, FIG. 2 is an explanatory view showing an example of a pattern shape of a shadow mask, and FIGS. 3 (a) to (i) are books. Waveform diagram showing the operation of the invention, FIGS. 4 (a) and 4 (b) are explanatory diagrams showing the operation of the present invention, FIG. 5 is an explanatory diagram showing the state of the shadow mask in the cathode ray tube, and FIG. 6 is a TV. It is explanatory drawing of the angle of view at the time of photographing a shadow mask with a camera. 1 ... TV camera 2 ... Image processing device 3 ... Control unit 4 ... Image display 5 ... Driving mechanism 6 ... Inspected object 7 ... Diffusion plate 8 ... Incandescent lamp 9 ... DC power supply 10 ...... XY stage 11 …… Unit pattern 12,13 …… Defective unit pattern 15 …… CRT 16 …… Shooting lens E ₁ …… Aperture change due to defect E ₂ , E ₃ …… Defect waveform S _{1 to} S ₃ ... Threshold

Claims (6)

[Claims] 1. A method for inspecting spots and local defects in a shadow mask, which are caused by irregularities in uniformity of optical properties in a shadow mask consisting of a repetitive array of unit patterns, wherein the shadow mask is imaged and decomposed into pixels. Image capturing means for obtaining image data in units of frames, moving means for moving the shadow mask to a predetermined position, and the shadow based on image data obtained by moving the shadow mask to a plurality of positions. A structure provided with a detection means for detecting irregularity of mask uniformity and local defects, wherein the image data is image data obtained by adding image data of a plurality of frames, and, The image data was obtained by performing arithmetic processing on each image data obtained at each position of the shadow mask so that the total number of frames becomes "0". Inspection method of a shadow mask, characterized in that an image data. 2. The image data obtained by moving the shadow mask to a plurality of positions and processing the image data so that the image data has a value according to a curvature of a distribution of optical properties of the shadow mask. Claim 1 characterized by
The method for inspecting a shadow mask according to the item. 3. The image data obtained by moving the image data so as to obtain a distribution of differences in optical properties between two points having a predetermined positional relationship on the shadow mask and processing the image data. The shadow mask inspection method according to claim 1. 4. The process described above is a process for recognizing a portion where a density of pixels in which a change in optical property of the shadow mask is a predetermined level or more as a predetermined value or more as a defect. Claims 1 and 2,
The method for inspecting a shadow mask according to item 3. 5. The method for inspecting a shadow mask according to claim 1, wherein the predetermined position has a distance that is an integral multiple of an arrangement pitch of pixels. 6. The image pickup means is capable of picking up an image at an image pickup angle close to an incident angle of an electron beam with respect to the shadow mask in a cathode ray tube at each image pickup point of the shadow mask. A method for inspecting a shadow mask according to claim 1.