JP2000088563A - Method and apparatus for visual inspection - Google Patents

Method and apparatus for visual inspection

Info

Publication number
JP2000088563A
JP2000088563A JP25393498A JP25393498A JP2000088563A JP 2000088563 A JP2000088563 A JP 2000088563A JP 25393498 A JP25393498 A JP 25393498A JP 25393498 A JP25393498 A JP 25393498A JP 2000088563 A JP2000088563 A JP 2000088563A
Authority
JP
Japan
Prior art keywords
defect
image data
detection
image
means
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
JP25393498A
Other languages
Japanese (ja)
Other versions
JP4105809B2 (en
Inventor
Yukio Kenbo
Shunji Maeda
Minoru Noguchi
Kenji Oka
俊二 前田
健次 岡
行雄 見坊
稔 野口
Original Assignee
Hitachi Ltd
株式会社日立製作所
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Hitachi Ltd, 株式会社日立製作所 filed Critical Hitachi Ltd
Priority to JP25393498A priority Critical patent/JP4105809B2/en
Publication of JP2000088563A publication Critical patent/JP2000088563A/en
Application granted granted Critical
Publication of JP4105809B2 publication Critical patent/JP4105809B2/en
Anticipated expiration legal-status Critical
Expired - Fee Related legal-status Critical Current

Links

Abstract

(57) [Summary] [PROBLEMS] To provide a technique capable of shortening a defect classification time in a visual inspection. SOLUTION: In a method for detecting an image using stage scanning, a configuration is adopted in which a low-magnification image required for defect classification can be detected at the same time as a low-magnification image detection for performing an inspection process. Efficient inspection can be performed without redetecting an image of a defective portion.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

TECHNICAL FIELD The present invention relates to a semiconductor wafer,
BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a visual inspection method and a visual inspection apparatus for a photomask, a magnetic disk, and the like, and in particular, detects a pattern that should be the same as the inspection target and inspects for defects such as pattern abnormalities and foreign matter adhesion. In addition, the present invention relates to a visual inspection technique suitable for use in a device that needs to be classified by analyzing a defect.

[0002]

2. Description of the Related Art Conventionally, as a visual inspection technique of this type, a method shown in FIGS.

The configuration shown in FIG. 5 is called a design data comparison method. As shown in FIG. 5, a semiconductor wafer 3 as an inspection object (sample) is mounted on a Zθ stage 2 installed on an XY stage 1. Above the semiconductor wafer 3, there is provided a half mirror 6 for directing illumination light from the illumination light source 4 toward the semiconductor wafer 3, and the illumination light reflected by the half mirror 6 is:
The semiconductor wafer 3 is illuminated via the objective lens 5. The reflected light from the semiconductor wafer 3 passes through an objective lens 5 and a half mirror 6 and is detected as a detection light by a detector (for example, a CCD).
The light is received by an image sensor 7.

The detection light received by the detector 7 is
The data is converted into a digital image signal by the A / D converter 8 and is generated by the design data pattern generating circuit 9, and is compared by the signal comparing means 10. At this time, if there is a mismatch between the two signals, it is determined that there is a defect.

[0005] The configuration shown in FIG. 6 is called a binocular two-chip comparison system. In FIG. 6, the same reference numerals are given to components equivalent to those described above (having the same functions). (This is the same in the following description).

The two-lens two-chip comparison system has two sets of a series of optical systems from illumination to detection described in FIG. 5, and the signals received by both detectors 7 and 7 are converted by an A / D converter 8 , 8 are converted into digital image signals, respectively, and then compared by the signal comparing means 10 to determine a defect.

[0007] The configuration shown in FIG. 7 is called a single-lens two-chip comparison system. This method has a series of optical systems from illumination to detection described with reference to FIG. 5, stores a detection signal detected in the first scanning area in the image storage circuit 11, and then stores the stored detection signal and the next detection signal. The detection signal obtained in the scanning area is compared with the signal comparing means 10 to detect the coincidence / mismatch of the detection signals, and the defect is determined.

[0008] In any of the above three methods, in order to perform inspection at high speed, two stages are scanned by a continuous stage.
A method of detecting a two-dimensional image is adopted, and a method of detecting an image by a so-called step & repeat method is not adopted.

As the classification and analysis sequence of the results of the appearance inspection as described above, those of the type shown in FIG. 8 or 9 are known.

FIG. 8 shows a classification sequence based on visual confirmation of a person. First, an inspection is performed by a visual inspection device.
An image of each defective portion is displayed on the apparatus based on the obtained coordinate information of the defect. Generally, this display is performed at a resolution higher than the resolution of the processed image at the time of inspection. Next, a person looks at the image and, based on the color, shape and background information of the defect,
Defect categorization is performed.

FIG. 9 shows a classification sequence by introducing an automatic defect classification function. First, an inspection is performed by a visual inspection device, and an image of each defective portion is detected on the device based on the obtained coordinate information of the defect. Also in the automatic classification, this detection is performed at a resolution higher than the resolution of the processed image at the time of inspection.
Next, with the automatic classification function, the color, shape,
Based on the information on the background and the coordinates, the defect is classified into categories. With the introduction of the automatic classification function,
Improvement of defect review efficiency and standardization of classification are being attempted.

[0012]

However, the above-mentioned prior art has the following problems. The inspection methods of FIGS. 5 to 7 described above and the classifications of FIGS. 8 and 9 described above,
What is common to the combination with the analysis sequence is that at the time of inspection for the presence or absence of a defect, an inspection image is detected at a low magnification in order to secure a practical inspection time, and classification is performed after completion of the inspection.
In order to perform the analysis, the image of the defective portion is re-detected at a high magnification based on the defect coordinate information based on the inspection result. The reason why the image of the defective portion is re-detected in this way is that it is difficult to detect images of different magnifications by one stage scan because the inspection apparatus performs image detection by stage scan to improve inspection efficiency. This is because
This is a factor that increases the total inspection time including defect classification.

For example, in an example of a semiconductor wafer appearance inspection, a defect inspection time (a defect detection time) per inspection object is about 15 minutes. On the other hand, in the classification process, the inspection result is thinned out and about 100 defects are targeted. If the time required for automatic classification is 3 seconds / point, 300 seconds (5
Minutes), which is actually one of the defect inspection times.
/ 3. During this time, the wafer to be inspected is restrained on the inspection apparatus and cannot proceed to the next process.

The re-detection of an image of a defective portion for the above classification is performed because a high-resolution image whose pixel size is about 2 to 8 times as large as that at the time of inspection is required. For this reason, when the processed image at the time of inspection is used, defect classification with sufficient accuracy is difficult. Conversely, if the inspection pixel size is the same as when the image for classification is detected, the number of pixels to be inspected is 16 to 64 times, which leads to a significant increase in the circuit scale of the apparatus and the inspection time. Becomes impractical.

In recent years, the diameter of wafers has been increasing, and φ
It is about to move from 200 to φ300. Therefore, it is clear that the number of objects to be classified per wafer increases, and the inspection method according to the related art has a problem that the time for the increase in the number of objects to be classified increases.

The present invention has been made in view of the above-mentioned problem, and an object of the present invention is to provide a technique capable of shortening a defect classification time in a visual inspection.

[0017]

As described above, in the prior art, an image of a defective portion to be classified is re-detected after the inspection based on the inspection result of the appearance inspection.
According to the present invention, in a method of detecting an image using stage scanning, an image at a high magnification (high resolution) required for defect classification can be detected at the same time as image detection at a low magnification (low resolution) for performing inspection processing. With such a configuration, an efficient inspection can be performed without redetecting an image of a defective portion after the inspection is completed.

[0018]

Embodiments of the present invention will be described below. FIG. 1 is a diagram showing a configuration of a visual inspection device according to a first embodiment of the present invention. As shown in FIG. 1, a semiconductor wafer 3 as an inspection object (sample) is mounted on a Zθ stage 2 installed on an XY stage 1. Above the semiconductor wafer 3, there is provided a half mirror 6 for directing illumination light from the illumination light source 4 toward the semiconductor wafer 3. The illumination light reflected by the half mirror 6 passes through the objective lens 5, The wafer 3 is illuminated.

The reflected light from the semiconductor wafer 3 passes through the objective lens 5 and the half mirror 6, passes through the half mirror 6A, and is received by the detector (CCD image sensor) 7A as detection light in the low magnification detection system 20. What is done,
After being reflected by the half mirror 6A, the high-magnification detection system 21
, A detector (CCD image sensor) 7B which receives light as detection light through the zoom lens 22;
It has a configuration that separates. Note that the low magnification detection system 20
Although the magnification is sufficient to guarantee the accuracy of defect detection, the detection optical system has a lower resolution than the high magnification detection system 21, and the high magnification detection system 21 has a higher resolution than the low magnification detection system 20. (For example, the resolution is about 2 to 8 times higher than that of the low magnification detection system 20), and the detection optical system has a high resolution.

Here, in order to simultaneously detect an image in the low-magnification detection system 20 and the high-magnification detection system 21, the detection pixel size P1 by the detector 7A, the detection pixel size P2 by the detector 7B, The following relationship is established between the scanning time T1 per line in the stage traveling direction of the detector 7A, the scanning time T2 per line in the stage traveling direction of the detector 7B, the stage moving speed V, and the magnification Z of the zoom lens 22. Must be established. V = P1 / T1 = P2 / T1 P2 = Z × P1 In practice, from P1, P2 and T1, T satisfying the above equation
When 2 is calculated, a high-speed detector that is difficult to realize is required.
This can be dealt with by increasing the pixel readout time for each channel.

The detection light received by the detector 7A is A / D
It is converted into a digital image signal by the converter 8,
It is input to the defect detection unit 23. In the defect detection unit 23, A
The presence / absence of a defect is determined by comparing the input data from the / D converter 8 with data for comparison with the input data. That is, although omitted in FIG.
For example, similarly to the configuration of FIG. 5, the data generated by the design data pattern generation circuit based on the design data is compared with the input data from the A / D converter 8, or the data of FIG. Similarly to the configuration, data captured in the previous scanning area and stored in the image storage circuit,
The defect is determined by comparing the input data from the A / D converter 8 with the input data. Then, when a defect is found, the defect detection unit 23 outputs defect information 24 representing feature amounts such as the size, area, shape, color, and background of the defect, and coordinate information 25 of the defect. The defect image database 26 stores the defect information 24 and the coordinate information 25 output by the defect detection unit 23.

On the other hand, a detection signal obtained from the high-magnification detection light in the detector 7B is converted into a digital image signal by the A / D converter 8, and sent to the delay memory 27 as a temporary memory, where the high-magnification signal is output. (High resolution) image data is stored. Delay memory read circuit 28
Receives the defect coordinate information 25 output from the defect detection unit 23, extracts the corresponding image data in the delay memory 27 centering on the defective part, transfers the extracted image data to the image memory 29, and temporarily stores it. The delay memory 27 has a sufficient capacity to extract image data of a defective portion with a predetermined time lag. However, the delay memory 27 does not need to hold the image data of the entire region of the sample at all, and only needs to guarantee the extraction of the image data having the above-mentioned predetermined time lag. No need to configure.

The image data (defect image) of the defective portion stored in the image memory 29 is stored in the defect information editing computer 3.
By 0, it is stored in the defect image database 31 in association with the defect information 24 and the coordinate information 25 stored in the defect image database 26. And viewing defect images,
At the time of the search, the contents stored in the defect image database 31 are appropriately read out by the defect information editing computer 30, and the defect information and the coordinate information are added to the image data (defect image) of the defective portion, and the CRT 32 is added. To be displayed on the screen.

As described above, the defect image database 31
The defect image, defect information, and coordinate information stored in the CRT 32 are displayed on the CRT 32 by the defect information editing computer 30 so that an operator can perform defect classification using the computer. The visually classified data is also stored in the defect image database 31 in association with the defect image, the defect information, and the coordinate information. The content stored in the defect image database 31 can be browsed and searched on the CRT 32 by the defect information editing computer 30 as well as various display processes such as enlargement, reduction, movement, superposition, color change, and the like. Various editing processes such as rearranging, transferring, copying, and deleting data are possible.

FIG. 2 shows a CRT 32 according to this embodiment.
It is a figure which shows an example of the operation screen for visual classification of the defect displayed above. In the example shown in FIG. 2, a list display column 42 in which the defect images are reduced is provided below the display columns of the product name, the process, the wafer, and the inspection date and time on the display screen 41. By doing so, each defect image (image data of each defective portion) 43a, 43b, 4
3c... Can be visually recognized. Then, the operator specifies the defect image for which the classification is to be specified, and enlarges and displays the specified reduced defect image as necessary, whereby the operator sequentially specifies the classification for the selected image, and By sequentially writing the classification designation in the classification name input field 44, the operator performs visual defect classification processing. Here, CRT32
Since the defect image displayed above is high-magnification image data, in other words, high-resolution image data, as described above, it is needless to say that the display is clear and detailed. No.

The data such as the defect image, defect information, coordinate information, and classification information stored in the defect image database 31 can be transferred to an external device via a network or a large-capacity medium such as an MO drive. By doing so, offline review or connection to an automatic defect classification device is also possible.

FIG. 3 is a diagram showing a configuration of a visual inspection apparatus according to a second embodiment of the present invention. As shown in FIG.
A semiconductor wafer 3 as an inspection object (sample) is mounted on a Zθ stage 2 provided on a Y stage 1. Above the semiconductor wafer 3, two optical systems,
That is, although the magnification is sufficient to guarantee the accuracy of defect detection, the low magnification detection system 20A, which is a detection optical system having a relatively low resolution, and a higher resolution than the low magnification detection system 20A (for example, low magnification). And a high-magnification detection system 21A, which is a high-resolution detection optical system.

Low magnification detection system 20A and high magnification detection system 2
1A is provided with half mirrors 6, 6 for directing illumination light from the respective illumination light sources 4, 4 toward the semiconductor wafer 3, and the illumination light reflected by the half mirrors 6, 6 is:
The semiconductor wafer 3 is illuminated through the objective lenses 5 and 5, respectively.

In the low-magnification detection system 20A, the reflected light from the semiconductor wafer 3 passes through the objective lens 5 and the half mirror 6, is received by the detector 7A as detection light, and is converted into a digital image signal by the A / D converter 8. It is converted and input to the defect detection unit 23. The defect detection unit 23 compares the input data from the A / D converter 8 with the data for comparison with the input data to determine the presence or absence of a defect. That is, although omitted in FIG. 3, the defect detection unit 23 includes, for example, the data generated by the design data pattern generation circuit based on the design data and the data from the A / D converter 8 as in the configuration of FIG. The input data is compared with the data, or, similarly to the configuration shown in FIG.
The defect is determined by comparing the input data from the D converter 8 with the input data. When a defect is found, the defect detection unit 23 determines the size, area, shape,
It outputs defect information 24 representing feature amounts such as color and background, and defect coordinate information 25. Defect image database 26
Then, the defect information 24 and the coordinate information 25 output by the defect detection unit 23 are stored.

On the other hand, in the high-magnification detection system 21A, the reflected light from the semiconductor wafer 3 passes through the objective lens 5, the half mirror 6, and the zoom lens 22, and is received by the detector 7B as high-magnification detection light. The detection signal obtained from the high-magnification detection light in the detector 7B is converted into a digital image signal by the A / D converter 8 and sent to the delay memory 27 as a temporary memory, where the high-magnification (high-resolution) signal is output. Stored as image data. Delay memory read circuit 2
8 receives the defect coordinate information 25 output from the defect detection unit 23, extracts the corresponding image data in the delay memory 27 centering on the defective part, transfers it to the image memory 29, and temporarily stores it. . The delay memory 27 has a sufficient capacity to extract image data of a defective portion with a predetermined time lag.

Also in this embodiment, the low magnification detection system 20
In order to simultaneously detect an image by the A and the high-magnification detection system 21A, the detection pixel size P1 by the detector 7A, the detection pixel size P2 by the detector 7B, and the line per line in the stage advancing direction of the detector 7A. Scan time T1, detector 7
Scanning time T2 per line in the stage advancing direction of B,
The following relationship must be established between the stage moving speed V and the magnification Z of the zoom lens 22. V = P1 / T1 = P2 / T1 P2 = Z × P1 In practice, from P1, P2 and T1, T satisfying the above equation
When 2 is calculated, a high-speed detector that is difficult to realize is required.
This can be dealt with by increasing the pixel readout time for each channel.

However, in the present embodiment, the first
Unlike the embodiment, the distance between the two detection systems requires extra scanning of the stage, which leads to an increase in the inspection time. However, since two independent detection systems are provided, one detection system cannot be used. It is also possible to realize two optical conditions that are difficult to realize, such as an illumination wavelength region, a focal position, and polarization, and to use an SEM (scanning electron microscope) as the high-magnification (high-resolution) detection system 21A. There is a feature.

As described above, the image data (defect image) of the defective portion stored in the image memory 29 is converted by the defect information editing computer 30 into the defect information 24 and the coordinate information 25 stored in the defect image database 26. And stored in the defect image database 31. When browsing and retrieving a defect image, the contents stored in the defect image database 31 are appropriately read out by the defect information editing computer 30, and the defect information and coordinates are stored in the image data (defect image) of the defect part. Add information and C
The information is output to the RT 32 and displayed.

The defect image, defect information and coordinate information stored in the defect image database 31 are stored in the first image.
As in the embodiment, the defect information is displayed on the CRT 32 by the defect information editing computer 30, and the operator can use the defect information editing computer 30 to classify the defect. The image database 31 is stored in association with a defect image, defect information, and coordinate information. The content stored in the defect image database 31 can be browsed and searched on the CRT 32 by the defect information editing computer 30 as well as various display processes such as enlargement, reduction, movement, superposition, color change, and the like. Sort, transfer,
Various editing processes such as copying and deleting are possible. In addition, data such as defect images, defect information, coordinate information, and classification information stored in the defect image database 31 may be transferred to an external device via a network or a large-capacity medium such as an MO drive. It also enables offline review and connection to an automatic defect classification device.

In the first and second embodiments, the low-magnification detection system may be a detection system for obtaining grayscale image data, and the high-magnification detection system may be a detection system for obtaining color image data. What is necessary is that defect detection is possible if there is brightness information, which simplifies the configuration of the low-magnification detection system and enables cost reduction, and also allows the operator to visually classify defects. This is because, for automatic defect classification, it is possible to make a more detailed and reliable judgment if there is color information. Further, in the second embodiment, as described above, an SEM (scanning electron microscope) can be used as the high-magnification detection system. Data can be obtained.

FIG. 4 is a diagram showing a configuration of a visual inspection apparatus according to a third embodiment of the present invention. As shown in FIG.
A semiconductor wafer 3 as an inspection object (sample) is mounted on a Zθ stage 2 provided on a Y stage 1. Above the semiconductor wafer 3, a half mirror 6 for directing illumination light from the illumination light source 4 toward the semiconductor wafer 3
The illumination light reflected by the half mirror 6 illuminates the semiconductor wafer 3 via the objective lens 5.

The reflected light from the semiconductor wafer 3 passes through an objective lens 5 and a half mirror 6 and is detected as detector light by a detector 7.
A (the detection optical system of this embodiment corresponds to the low magnification detection system 20A of the second embodiment). The detection light received by the detector 7A is A /
It is converted into a digital image signal by the D converter 8,
It is input to the delay memory 33 and the defect determination unit 23. As in the configuration of FIG. 7, the defect determination unit 23 stores data captured in the previous scanning region and stored in the delay memory 33,
The defect is determined by comparing the input data from the A / D converter 8 with the input data. Then, when a defect is found, the defect detection unit 23 outputs defect information 24 representing feature amounts such as the size, area, shape, color, and background of the defect, and coordinate information 25 of the defect. The defect image database 26 stores the defect information 24 and the coordinate information 25 output by the defect detection unit 23.

The delay memory readout circuit 28 receives the defect coordinate information 25 output from the defect detection section 23, extracts corresponding image data on the delay memory 27 centering on the defective portion, and extracts it from the image memory 29. And temporarily store it.

The image data (defective image) of the defective portion stored in the image memory 29 is stored in the defect information editing computer 3.
By 0, it is stored in the defect image database 31 in association with the defect information 24 and the coordinate information 25 stored in the defect image database 26.

When browsing or searching for a defect image, the contents stored in the defect image database 31 are appropriately read out by the defect information editing computer 30, and the read image data of the defective portion (defect image ) Are subjected to pixel interpolation processing in the image interpolation circuit 34 and output to the CRT 32 as high magnification (high resolution) image data.
Defect information and coordinate information are added to the high-magnification (high-resolution) image data and displayed on the CRT 32. When the image data (defective image) of the defective portion stored in the image memory 29 is stored in the defective image database 31, a pixel interpolation process is performed by an image interpolation circuit in advance, and the image data after the pixel interpolation process is performed. May be stored in the defect image database 31.

As described above, also in the present embodiment, the operator can perform the classification of defects by using the data displayed on the CRT 32 by the computer 30 for editing the defect information. The divided data is also stored in the defective image database 31 as image data of the defective portion subjected to pixel interpolation processing as necessary, and
It is stored together with defect information and coordinate information.

Also in this embodiment, as in the first and second embodiments, the contents stored in the defect image database 31 are processed by the defect information editing computer 30.
You can browse and search on CRT32, of course,
Various display processes such as reduction, movement, superposition, and color change, and various edit processes such as data rearrangement, transfer, copy, and deletion can be performed. In addition, data such as defect images, defect information, coordinate information, and classification information stored in the defect image database 31 may be transferred to an external device via a network or a large-capacity medium such as an MO drive. It also enables offline review and connection to an automatic defect classification device.

As described above, in each of the above-described embodiments of the present invention, before the inspection for the presence / absence of a defect is completed, confirmation of the detected defect (defect candidate) is performed using high-magnification (high-resolution) image data. Analysis (classification of defects, etc.) can be started, and the total inspection time can be reduced as compared with the related art.

In each of the embodiments described above, if image data (defective image) of a defective portion is stored by compressing and storing the image data, it goes without saying that the memory utilization efficiency is improved. No.

In the appearance inspection apparatus of each of the above-described embodiments, the appearance inspection apparatus is provided with a function of automatically performing classification based on the feature amount and coordinates of the image data of the defective portion, and the classification is automatically performed. The CRT3 results for each classification
2 can be displayed in a list.

Further, when the above-described embodiment of the present invention is constructed on the basis of a two-chip comparison inspection apparatus, the image data is fetched twice in the memory. One is an image of an actual defective part, and the other is an image of a normal part corresponding to the defective part. If this image is compared with the defect information, it is needless to say that it is possible to determine which is the actual defective portion.

[0047]

As described above, according to the present invention, before the inspection for the presence or absence of a defect is completed, the detected defect (defect candidate) is confirmed and analyzed (defect candidate) by using high magnification (high resolution) image data. Classification, etc.) can be started, and the total inspection time can be reduced as compared with the related art.

[Brief description of the drawings]

FIG. 1 is a configuration diagram of a visual inspection device according to a first embodiment of the present invention.

FIG. 2 is an explanatory diagram showing an example of an operation screen for visually classifying defects displayed on a CRT in the appearance inspection device according to the first embodiment of the present invention.

FIG. 3 is a configuration diagram of a visual inspection device according to a second embodiment of the present invention.

FIG. 4 is a configuration diagram of a visual inspection device according to a third embodiment of the present invention.

FIG. 5 is a configuration diagram of a visual inspection device according to a conventional technique.

FIG. 6 is a configuration diagram of a visual inspection device according to a conventional technique.

FIG. 7 is a configuration diagram of a visual inspection device according to a conventional technique.

FIG. 8 is an explanatory diagram showing a sequence of classifying defects by visual confirmation in the related art.

FIG. 9 is an explanatory diagram showing a sequence of automatic defect classification in the related art.

[Explanation of symbols]

 Reference Signs List 1 XY stage 2 Zθ stage 3 Semiconductor wafer 4 Illumination light source 5 Objective lens 6, 6A Half mirror 7, 7A, 7B Detector 8 A / D converter 9 Design data pattern generation circuit 10 Signal comparison means 11 Image storage circuit 20, 20A Low Magnification detection system (low resolution detection system) 21, 21A High magnification detection system (high resolution detection system) 22 Zoom lens 23 Defect detection unit 24 Defect information 25 Coordinate information 26 Defect information database 27 Delay memory 28 Delay memory read circuit 29 Image memory Reference Signs List 30 Defect information editing computer 31 Defect image database 32 CRT 33 Delay memory 34 Image interpolation circuit

──────────────────────────────────────────────────続 き Continued on the front page (51) Int.Cl. 7 Identification symbol FI Theme coat ゛ (Reference) H01J 37/22 502 H01L 21/66 Z H01L 21/66 G01N 21/88 630A 645Z G06F 15/62 400 (72 Inventor Minoru Noguchi 292, Yoshida-cho, Totsuka-ku, Yokohama-shi, Kanagawa Prefecture Inside the Hitachi, Ltd.Production Technology Research Laboratories (72) Inventor Yukio Mibo 292, Yoshida-cho, Totsuka-ku, Yokohama-shi, Kanagawa Prefecture Production Technology Research, Hitachi, Ltd. Inside

Claims (13)

    [Claims]
  1. A defect is detected by processing a detection signal obtained under a first detection condition while relatively scanning a sample, and is simultaneously obtained under a second detection condition different from the first detection condition. An appearance inspection method, wherein a detection signal of a defective portion is extracted from the detection signal and stored.
  2. 2. The scanning electron microscope (SEM) according to claim 1, wherein a detection signal obtained under the first detection condition is used as image data obtained from an optical system, and a detection signal obtained under the second detection condition is used as a scanning electron microscope (SEM). A) visual inspection method characterized by using image data obtained from
  3. 3. The method according to claim 1, wherein the detection signal obtained under the first detection condition is grayscale image data obtained from an optical system, and the detection signal obtained under the second detection condition is output from the optical system. An appearance inspection method characterized by obtaining obtained color image data.
  4. 4. A method for detecting a defect by detecting a first detection signal while relatively scanning a sample, and detecting defects in the same scan as the above-described scan for detecting the first detection signal under different detection conditions. 2. A visual inspection method characterized by detecting the detection signal of No. 2 and temporarily storing the same, and extracting and storing the image data of the defective portion from the temporarily stored detection data.
  5. 5. A defect is detected by image data detected while relatively scanning the sample, and at the same time, image data is detected and temporarily stored at a higher magnification (higher resolution) than the image data for defect inspection. An appearance inspection method, wherein an image of a defective portion is extracted from the temporarily stored high-magnification (high-resolution) image data and stored based on the detection result of the defect.
  6. 6. The detection pixel size of the high magnification (high resolution) according to claim 5, wherein a detection pixel size of the defect inspection is P1, an accumulation time per line of the defect inspection detector is T1, and P2, the accumulation time per line of the high magnification (high resolution) detector is T2,
    An appearance inspection method, wherein a relation of V = P1 / T1 = P2 / T2 is satisfied when the moving speed of the stage is V.
  7. 7. A defect is detected by image data detected while relatively scanning the sample, and an image of the defective portion is converted to a high-level image obtained by performing pixel interpolation processing on the image data for defect inspection based on the detection result of the defect. A visual inspection method characterized by displaying or storing image data of a resolution.
  8. 8. A defect detection means for detecting a defect by processing a detection signal obtained under a first detection condition while relatively scanning a sample, and a second detection condition different from the first detection condition Defect image data extracting means for extracting the image data of the defective portion from the detection signals obtained at the same time, defect image data memory means for storing the image data of the defective portion extracted by the defect image data extracting means, and defect image data Display means for displaying image data stored in the memory means,
    A visual inspection device characterized by comprising:
  9. 9. A defect detecting means for processing a first detection signal obtained while relatively scanning a sample to detect a defect, and wherein the defect detection means detects the defect in the same scan as the scan for detecting the first detection signal.
    Image data temporary memory means for temporarily storing second detection signals obtained under different detection conditions; defective image data extraction means for extracting image data of a defective portion from the contents of the image data temporary memory means; A visual inspection apparatus comprising: a defect image data memory means for storing image data of a defective portion extracted by the extraction means; and a display means capable of displaying the image data stored in the defect image data memory means. .
  10. 10. A defect detecting means for detecting a defect based on image data detected while relatively scanning a sample, and a defect detecting means for detecting a defect based on the image data for the defect inspection obtained simultaneously with the detection of the image data for the defect inspection. Image data temporary memory means for temporarily storing high magnification (high resolution) image data; defective image data extracting means for extracting defective section image data from the contents of the image data temporary memory means; and defective image data extracting means 1. An appearance inspection apparatus comprising: a defect image data memory means for storing image data of a defective portion extracted by the method; and a display means capable of displaying the image data stored in the defect image data memory means.
  11. 11. The detection pixel size of the high magnification (high resolution) according to claim 10, wherein the detection pixel size of the defect inspection is P1, the accumulation time per line of the defect inspection detector is T1. P2, when the accumulation time per line of the detector for high magnification (high resolution) is T2 and the moving speed of the stage is V, the following relationship holds: V = P1 / T1 = P2 / T2 Appearance inspection device.
  12. 12. A defect detecting means for detecting a defect based on image data detected while relatively scanning a sample, and an image of a defective portion is converted into a pixel based on the defect inspection image data based on the defect detection result. Means for displaying on the display means as high-resolution image data subjected to interpolation processing.
  13. 13. The method according to claim 8, wherein the classification of the defects is automatically performed based on the feature amount of the image of the defective portion, and a list is displayed on a screen for each classification. A visual inspection device characterized by the following.
JP25393498A 1998-09-08 1998-09-08 Appearance inspection method and appearance inspection apparatus Expired - Fee Related JP4105809B2 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
JP25393498A JP4105809B2 (en) 1998-09-08 1998-09-08 Appearance inspection method and appearance inspection apparatus

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
JP25393498A JP4105809B2 (en) 1998-09-08 1998-09-08 Appearance inspection method and appearance inspection apparatus

Publications (2)

Publication Number Publication Date
JP2000088563A true JP2000088563A (en) 2000-03-31
JP4105809B2 JP4105809B2 (en) 2008-06-25

Family

ID=17258056

Family Applications (1)

Application Number Title Priority Date Filing Date
JP25393498A Expired - Fee Related JP4105809B2 (en) 1998-09-08 1998-09-08 Appearance inspection method and appearance inspection apparatus

Country Status (1)

Country Link
JP (1) JP4105809B2 (en)

Cited By (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2001266125A (en) * 2000-03-15 2001-09-28 Olympus Optical Co Ltd Substrate inspecting device
JP2002195956A (en) * 2000-12-25 2002-07-10 Nikon Corp Failure inspecting device
JP2002277412A (en) * 2001-03-21 2002-09-25 Olympus Optical Co Ltd Inspection screen displaying method and substrate inspection system
JP2002350320A (en) * 2001-05-25 2002-12-04 Olympus Optical Co Ltd Scanning probe microscope
JP2003004653A (en) * 2001-06-19 2003-01-08 Seiko Instruments Inc Automatic ccd camera changeover system in scanning electron microscope with laser defect detecting function
JP2005062148A (en) * 2002-11-01 2005-03-10 Photon Dynamics Inc Method and apparatus for inspecting medium having formed flat pattern
JP2005166991A (en) * 2003-12-03 2005-06-23 Disco Abrasive Syst Ltd Alignment apparatus and processing apparatus
JP2006507539A (en) * 2002-11-21 2006-03-02 トッパン、フォウタマスクス、インク System and method for automatically transmitting defect images from an inspection system to a database
JP2006266943A (en) * 2005-03-24 2006-10-05 Sony Corp Apparatus and method for inspecting defect
WO2008062651A1 (en) * 2006-11-22 2008-05-29 Nikon Corporation Image measuring device
JP2010096690A (en) * 2008-10-20 2010-04-30 Nuflare Technology Inc Method and apparatus for reviewing mask defect
JP2010117285A (en) * 2008-11-14 2010-05-27 Omron Corp Defect inspection device for substrate
JP2010539481A (en) * 2007-09-17 2010-12-16 クオリティー ヴィジョン インターナショナル インコーポレイテッドQuality Vision International, Inc. Dual resolution, two distance sensor system and method

Cited By (21)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2001266125A (en) * 2000-03-15 2001-09-28 Olympus Optical Co Ltd Substrate inspecting device
JP4529108B2 (en) * 2000-12-25 2010-08-25 株式会社ニコン Defect inspection equipment
JP2002195956A (en) * 2000-12-25 2002-07-10 Nikon Corp Failure inspecting device
JP2002277412A (en) * 2001-03-21 2002-09-25 Olympus Optical Co Ltd Inspection screen displaying method and substrate inspection system
JP4649051B2 (en) * 2001-03-21 2011-03-09 オリンパス株式会社 Inspection screen display method and substrate inspection system
JP2002350320A (en) * 2001-05-25 2002-12-04 Olympus Optical Co Ltd Scanning probe microscope
JP2003004653A (en) * 2001-06-19 2003-01-08 Seiko Instruments Inc Automatic ccd camera changeover system in scanning electron microscope with laser defect detecting function
JP4681153B2 (en) * 2001-06-19 2011-05-11 エスアイアイ・ナノテクノロジー株式会社 CCD camera automatic switching method and system in scanning electron microscope with laser defect detection function
KR100997355B1 (en) 2002-11-01 2010-11-29 포톤 다이나믹스, 인코포레이티드 Method and apparatus for flat patterned media inspection
JP2005062148A (en) * 2002-11-01 2005-03-10 Photon Dynamics Inc Method and apparatus for inspecting medium having formed flat pattern
JP2006507539A (en) * 2002-11-21 2006-03-02 トッパン、フォウタマスクス、インク System and method for automatically transmitting defect images from an inspection system to a database
JP4697843B2 (en) * 2003-12-03 2011-06-08 株式会社ディスコ Alignment device and processing device
JP2005166991A (en) * 2003-12-03 2005-06-23 Disco Abrasive Syst Ltd Alignment apparatus and processing apparatus
JP2006266943A (en) * 2005-03-24 2006-10-05 Sony Corp Apparatus and method for inspecting defect
KR101376632B1 (en) 2006-11-22 2014-03-19 가부시키가이샤 니콘 Image measuring device
US8120844B2 (en) 2006-11-22 2012-02-21 Nikon Corporation Image measuring apparatus
JP5012810B2 (en) * 2006-11-22 2012-08-29 株式会社ニコン Image measuring instrument
WO2008062651A1 (en) * 2006-11-22 2008-05-29 Nikon Corporation Image measuring device
JP2010539481A (en) * 2007-09-17 2010-12-16 クオリティー ヴィジョン インターナショナル インコーポレイテッドQuality Vision International, Inc. Dual resolution, two distance sensor system and method
JP2010096690A (en) * 2008-10-20 2010-04-30 Nuflare Technology Inc Method and apparatus for reviewing mask defect
JP2010117285A (en) * 2008-11-14 2010-05-27 Omron Corp Defect inspection device for substrate

Also Published As

Publication number Publication date
JP4105809B2 (en) 2008-06-25

Similar Documents

Publication Publication Date Title
US9552636B2 (en) Detecting defects on a wafer using defect-specific and multi-channel information
JP5974037B2 (en) System and method for creating persistent data for wafers and using the persistent data for inspection related functions
US8639019B2 (en) Method and apparatus for inspecting pattern defects
US20170357895A1 (en) Method of deep learining-based examination of a semiconductor specimen and system thereof
US9355208B2 (en) Detecting defects on a wafer
US8731275B2 (en) Method and apparatus for reviewing defects
US7848563B2 (en) Method and apparatus for inspecting a defect of a pattern
US9684960B2 (en) Automated histological diagnosis of bacterial infection using image analysis
US6777677B2 (en) Method of inspecting pattern and inspecting instrument
JP4310090B2 (en) Defect data analysis method and apparatus, and review system
JP4644613B2 (en) Defect observation method and apparatus
JP4095860B2 (en) Defect inspection method and apparatus
US6104835A (en) Automatic knowledge database generation for classifying objects and systems therefor
JP4014379B2 (en) Defect review apparatus and method
US7409081B2 (en) Apparatus and computer-readable medium for assisting image classification
JP4616864B2 (en) Appearance inspection method and apparatus, and image processing evaluation system
US5987159A (en) System or method for detecting defect within a semi-opaque enclosure
EP0374694B1 (en) Defect detection system and method for pattern to be inspected
US7415149B2 (en) Pattern inspection apparatus
US7869966B2 (en) Inspection method and its apparatus, inspection system
US4589140A (en) Method of and apparatus for real-time high-speed inspection of objects for identifying or recognizing known and unknown portions thereof, including defects and the like
JP4558047B2 (en) Microscope system, image generation method, and program
US4659220A (en) Optical inspection system for semiconductor wafers
US4928313A (en) Method and system for automatically visually inspecting an article
US5777327A (en) Pattern shape inspection apparatus for forming specimen image on display apparatus

Legal Events

Date Code Title Description
A621 Written request for application examination

Free format text: JAPANESE INTERMEDIATE CODE: A621

Effective date: 20050812

A977 Report on retrieval

Free format text: JAPANESE INTERMEDIATE CODE: A971007

Effective date: 20071015

A131 Notification of reasons for refusal

Free format text: JAPANESE INTERMEDIATE CODE: A131

Effective date: 20071218

A521 Written amendment

Free format text: JAPANESE INTERMEDIATE CODE: A523

Effective date: 20080214

TRDD Decision of grant or rejection written
A01 Written decision to grant a patent or to grant a registration (utility model)

Free format text: JAPANESE INTERMEDIATE CODE: A01

Effective date: 20080318

A61 First payment of annual fees (during grant procedure)

Free format text: JAPANESE INTERMEDIATE CODE: A61

Effective date: 20080328

R150 Certificate of patent or registration of utility model

Free format text: JAPANESE INTERMEDIATE CODE: R150

FPAY Renewal fee payment (event date is renewal date of database)

Free format text: PAYMENT UNTIL: 20110404

Year of fee payment: 3

FPAY Renewal fee payment (event date is renewal date of database)

Free format text: PAYMENT UNTIL: 20110404

Year of fee payment: 3

S111 Request for change of ownership or part of ownership

Free format text: JAPANESE INTERMEDIATE CODE: R313111

FPAY Renewal fee payment (event date is renewal date of database)

Free format text: PAYMENT UNTIL: 20110404

Year of fee payment: 3

R350 Written notification of registration of transfer

Free format text: JAPANESE INTERMEDIATE CODE: R350

LAPS Cancellation because of no payment of annual fees