JP2003098113A - Defect inspection method and apparatus - Google Patents

Abstract

(57) [Summary] (Corrected) [PROBLEMS] To provide a defect inspection method and apparatus which can easily adjust the sensitivity in a comparative inspection for comparing an inspection target image with a reference image and detecting a defect from a difference between the reference image and the reference image. . Kind Code: A1 A correction is performed in accordance with the contrast of an image to reduce a difference between an image to be inspected and a reference image. In particular, even in the case of a small displacement, the difference becomes large, and in a high contrast portion where erroneous detection (false alarm) is likely to occur, the brightness of the image to be inspected can be particularly strongly adjusted as necessary. It realizes reduction of false alarm occurrence and high sensitivity inspection with only a low threshold value for the whole. Also, when the inspection target is a semiconductor wafer, by means of previously adjusting the difference in brightness between images caused by the difference in film thickness in the wafer, to avoid the occurrence of false alarms due to uneven brightness without lowering the sensitivity, In addition, the sensitivity can be easily adjusted with only one threshold value.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention compares an image of an object such as a semiconductor wafer, a TFT, or a photomask obtained by using light or a laser with a reference image stored in advance, and based on the difference, a fine image is obtained. The present invention relates to a defect inspection method and apparatus for inspecting pattern defects, foreign matters, and the like. In particular, the present invention relates to a defect inspection method and apparatus suitable for performing visual inspection of semiconductor wafers.

[0002]

2. Description of the Related Art As a conventional technique for detecting a defect by comparing an image to be inspected with a reference image, there is Japanese Patent Laid-Open No. 05-264.
The method described in Japanese Patent No. 467 is known.

In this method, a sample to be inspected in which repetitive patterns are regularly arranged is sequentially picked up by a line sensor, compared with an image with a time delay of the repetitive pattern pitch, and the non-matching portion is detected as a pattern defect. It is a thing. However, in reality, there are vibrations of the stage, inclination of the target object, and the like, and the positions of the two images are not necessarily aligned. Therefore, the image captured by the sensor and the image delayed by the repeated pattern pitch It is necessary to find the amount of displacement. Then, after aligning the two images based on the obtained positional deviation amount, the difference between the images is taken, and when the difference is larger than a specified threshold value, it is a defect, and when the difference is smaller than a non-defect. judge.

[0004]

As described above, according to the conventional technique, the steps of detecting the positional deviation between the image to be inspected and the reference image → aligning → comparing the images, that is, calculating the difference between the two images → extracting the defect are performed. Although the defect inspection is performed, if the correct positional deviation amount is not obtained at the time of detecting the positional deviation, the positioning at the wrong position is performed. In this case, in the aligned image, the difference between the aligned images does not become large in the region where the amount of change in brightness is small, but the difference becomes large in the region where the amount of change in brightness is large. For example, in FIG.
Reference numeral 11 in (a) is an image to be inspected, reference numeral 12 is an example of a reference image, 1a is a uniformly bright background area, and 1b is an area where a bright background has a dark pattern. Further, the inspection target image 11 has a defect 1c. In the image of this example, position 1
The waveform of the brightness value at D-1D 'is as shown in FIG.

Here, when the positional shift amounts of 11 and 12 are correctly obtained, the difference image after the positioning of 11 and 12 is shown in FIG.
become that way. The difference image is an image that is displayed as a shade difference according to the difference value at each corresponding position of the inspection target image and the reference image. If the portion where the difference value is greater than or equal to the specific threshold value TH is a defect, only the defect 1c of 11 in FIG. 2 is detected. However, when the misregistration amounts of 11 and 12 are calculated incorrectly, the difference image after alignment is shown in FIG.
As shown in (a), in the region where the change in the luminance value is large, such as the edge of the pattern in the region 1b, the difference value becomes large even with a slight positional deviation, and it is detected as a defect. This should not be originally detected as a defect. In other words, it is false information.

Conventionally, as one method for avoiding the occurrence of false information as shown in FIG. 3A, as shown in FIG.
The threshold value TH is increased to be TH2. This lowers the sensitivity, and a defect having a difference value equal to or less than the edge portion cannot be detected. As another method, as shown in FIG. 3C, the threshold value is set high such as TH2 in the high contrast portion where false information is likely to occur, and the threshold TH is set in the low contrast portion where false information is unlikely to occur. Although it is set lower than TH2, a plurality of threshold values are handled, and sensitivity adjustment becomes complicated.

Further, in the case where the inspection object is a semiconductor wafer, even if the position shift amount is correctly obtained, if there is a difference in film thickness within the wafer, 4a in FIG. 4A and FIG.
As shown in 4b of (b), a difference in brightness occurs in the same pattern of the inspection target image and the reference image, and the difference value is shown in FIG.
It becomes large like 4c shown in (c). This is also a false alarm, and in order to prevent the detection, the threshold TH must be increased to TH2 as shown in FIG. 4 (d). Alternatively, there is no choice but to set separate threshold values for the area with uneven brightness and the area without uneven brightness.

In order to solve the problem of the conventional inspection technique, an object of the present invention is to perform a comparative inspection in which an image to be inspected is compared with a reference image and a defect is detected from the difference.
By performing the inspection by adjusting the brightness so that the difference is small in the edge portion of the high-contrast pattern in the target image, false alarm due to the alignment error is reduced without increasing the threshold TH. , To provide a highly sensitive defect inspection method and apparatus. Further, in the inspection for the semiconductor wafer, the unevenness in the brightness of the pattern caused by the difference in the film thickness and the like is inspected by adjusting the brightness between the images to obtain the threshold value T.
It is to realize a highly sensitive defect inspection by reducing false alarm due to uneven brightness without increasing H.

[0009]

In order to achieve the above object, the present invention changes the inspection sensitivity according to the contrast of an image in an inspection for detecting a defect from the difference between two images by comparison. Means for detecting defects are provided. As one of its effective examples, a means for detecting defects is provided with high sensitivity in a high-contrast area where the difference is large even if there is a slight positional deviation, and with high sensitivity in a low-contrast area where the difference is small. There is.

Further, in an inspection for detecting a portion where a difference in brightness between two images is equal to or more than a specific threshold as a defect,
A means for changing the threshold according to the contrast of the image is provided. As one of its effective examples, a means for setting the threshold value high in the high contrast portion and setting the threshold value low in the low contrast portion is provided.

Further, there is provided means for performing correction so as to reduce the difference between the image to be inspected and the reference image according to the contrast of the image. As an effective example, even in the case of a minute positional deviation, the difference becomes large, and in the high-contrast portion where false detection (false alarm) is likely to occur, the brightness between images is adjusted so that the difference becomes small in advance. Therefore, in the final defect detection processing, a means for performing defect inspection with one low threshold value, that is, high sensitivity, for all contrasts is provided. Furthermore, a means is provided for monitoring the positional deviation accuracy and adjusting the brightness between the images so as to reduce the difference in the high-contrast area where erroneous detection due to positional deviation is likely to occur only when a misregistration occurs. There is.

Further, when the inspection target is a semiconductor wafer, when the difference in the film thickness within the wafer causes a difference in brightness in the same pattern between images, the brightness is adjusted in advance to adjust the brightness. Regardless of whether or not there is unevenness, a means for performing defect inspection with one low threshold value is provided.

By providing these means, it is possible to provide a defect inspection method and a defect inspection apparatus in which sensitivity can be adjusted with a unique threshold value for all inspection target regions.

[0014]

BEST MODE FOR CARRYING OUT THE INVENTION An embodiment of the present invention will be described in detail below with reference to the drawings.

As an example, taking a defect inspection method in an optical appearance inspection apparatus for semiconductor wafers as an example, FIG. 5 shows an example of the configuration of the apparatus. 51
Is a sample (inspection object such as a semiconductor wafer), 52 is a sample 5
1, a stage that is movable in at least an XY plane, a detection unit 53, a light source 501 that irradiates a sample 51,
Illumination optical system 50 that collects the light emitted from the light source 501
2. The objective lens 503 that illuminates the sample 51 with the illumination light condensed by the illumination optical system 502 and forms an optical image obtained by reflection, receives the formed optical image, and adjusts the brightness according to the brightness. The image sensor 504 is configured to convert the image signal. An image processing unit 55 processes the image detected by the detection unit 53 to calculate defect candidates in the wafer that is the sample.

The image processing section 55 is an AD conversion section 54 for converting the input signal from the detection section 53 into a digital signal, a preprocessing section 505 for performing image correction such as shading correction and dark level correction from the digital signal, and a comparison target. A delay memory 506 that stores a digital signal as a reference image signal, a position shift detection unit 507 that detects a position shift amount between the digital signal (detected image signal) detected by the detection unit 53 and the reference image signal of the delay memory 506. An image comparison unit 508 that compares the image signals of the detected image and the reference image using the calculated positional deviation amount, and outputs a portion having a difference value larger than a specific threshold value as a defect candidate, coordinates of the defect candidate. And a feature extraction unit 509 that calculates a feature amount and the like.

Reference numeral 56 denotes an overall control unit, which has a display unit and an input unit for receiving a change in inspection parameters (threshold value used in image comparison) from the user and displaying the detected defect information. Interface part 5
10, a storage device 511 that stores the feature amount and image of the detected defect candidate, and a CPU that performs various controls. Reference numeral 512 is a mechanical controller that drives the stage 52 based on a control command from the overall control unit.
The image processing unit 55, the detection unit 53 and the like are also driven by a command from the overall control unit 56.

The semiconductor wafer 51 to be inspected is shown in FIG.
As shown in, a large number of chips having the same pattern are regularly arranged. The inspection apparatus of FIG. 5 compares images at the same positions of two adjacent chips, for example, the area 61 and the area 62 of FIG. 6, and detects the difference as a defect. The operation will be described. In the overall control unit 56, the semiconductor wafer 51 as a sample is continuously moved by the stage 52. In synchronization with this, the images of the chips are sequentially captured by the detection unit 53. The image sensor 504 of the detection unit 53 outputs the input signal to the image processing unit 55. Image processing unit 55
Then, first, the input analog signal is converted into a digital signal by the AD conversion unit 54, and the preprocessing unit 505 performs shading correction, dark level correction, and the like. Displacement detection unit 50
7, an image signal (detected image signal) of the inspection target chip output from the preprocessing unit 505, and an image signal output from the delay memory 506, which is delayed by the time during which the stage 1 moves by the chip interval, that is, , One of the chips to be inspected
The image signal of the previous chip (reference image signal) is input as a set.

The image signals of these two chips, which are sequentially input in synchronization with the movement of the stage, are exactly the same when the movement speed of the stage is uneven, there is vibration of the stage, and the wafer set on the stage is tilted. It will not be a signal at a location. Therefore, the positional deviation detection unit 507 calculates the positional deviation amount between two images that are continuously input. At this time, the detected image signal and the reference image signal are continuously input, but the positional deviation amount is calculated sequentially for each processing unit with a specific length as one processing unit. The following processing is also performed for each processing unit. The image comparison unit 508 aligns the images using the calculated displacement amount, compares the detected image with the reference image, and outputs a region having a difference value larger than a specific threshold value as a defect candidate. Feature extraction unit 5
In 09, editing is performed such that small defects are deleted as noise, or neighboring defect candidates are merged as one defect, for each of the plurality of defect candidates, and feature amounts such as position, area, and size in the wafer are calculated. Is calculated and output as a final defect. These pieces of information are stored in the storage device 511. In addition, for example, it is displayed on the screen of the display unit and presented to the user via the user interface unit 510.

Here, when the image comparison unit 508 obtains defect candidates from simple difference values, they are not all true defects. An example will be described below. Figure 1 (a)
11 and 12 are a detection image and a reference image, and both images have a dark cross pattern in a uniformly bright background. Also,
Only the detected image 11 has the defect 1c. The graph of FIG. 1B is a waveform of the luminance value at positions 1D-1D ′ of the detected image 11. As shown in this graph, the image has high brightness and little change in brightness, that is, a low-contrast region 1a,
There is a large contrast change in the edge portion of the pattern, that is, a high-contrast region 1b. FIG. 2A shows an image of the difference value at each corresponding position when the positional deviation detection unit 507 calculates the correct positional deviation amount for these images and the positional adjustment is performed, that is, the difference is It is an image in which a small area is displayed dark and a large area is displayed brightly. FIG. 2B is a waveform of the difference value at the positions 1D-1D '.
If a region having a difference value equal to or larger than the threshold value TH is a defect,
In this case, only the area of the defect 1c is detected.

On the other hand, FIGS. 3A and 3B show an image of the difference value and a waveform of the difference value when the misregistration amount is erroneously calculated and misalignment is performed. FIG. 3 (a) is shown in FIG.
In the low contrast area where the amount of change in brightness is small like the area 1a shown in (a), the detected image 11 and the reference image 12
Even if the position of is slightly shifted, the difference value does not increase,
In the high-contrast region where the amount of change in brightness is large like the region 1b, it is shown that the difference value becomes large even with a slight positional deviation. In this case, as shown in FIG. 3B, when a region having a threshold value TH or more is set as a defect candidate, a portion having a large difference value due to such positional displacement is also detected as a defect. These should not be detected by nature. In the following, what is not such a true defect is described as a false alarm. Conventionally, in order to avoid detection of a false alarm due to displacement, one method is to increase the threshold value from TH to TH2 as shown in FIG. 3B, but this makes it impossible to detect a defect with a small difference value. Will end up. That is,
By using TH2 as a threshold in order to avoid the occurrence of false information, the sensitivity is lowered and the inspection is performed. As another conventional method, as shown in FIG. 3C, the threshold value is set to TH2 in the high contrast area and the threshold value is set to TH in the low contrast area. Since it has a value, the sensitivity adjustment is complicated for the user.

When the film thickness of the semiconductor wafer 51 is not uniform, the inspection target image and the reference image have a difference in brightness. For example, 4a in FIG. 4A and 4 in FIG.
The three crosses of b are the inspection target image 11 and the reference image 12
However, the brightness is significantly different due to the difference in film thickness (hereinafter referred to as uneven brightness). Further, only the detected image 11 has the defect 1c. Figure 4
(A) to (c) are images of the difference value at each corresponding position when the correct positional deviation amount is calculated by the positional deviation detection unit 507 for these images and alignment is performed. Even in the same pattern, the difference value becomes large in a portion with uneven brightness. FIG. 4D shows positions 1D-1D '.
FIG. 4C is a waveform on the 1D-1D ′ line in FIG. 4C, which is a difference value image in FIG. If an area having a difference value equal to or greater than the threshold value TH is a defect, in addition to the defect 1c shown in FIG. 4A, a difference between the cross patterns 4a and 4b having a large difference value due to uneven brightness is also detected. It However, these are false reports. In order to avoid detection of a false alarm due to such uneven brightness, the threshold value T
Increase from H to TH2 and perform inspection with low sensitivity overall,
Alternatively, the threshold may be set to TH2 in the area where the brightness is uneven.
In addition, in a portion where there is no unevenness in brightness, a method has been adopted in which the sensitivity is adjusted with a plurality of threshold values such as setting the threshold value to TH and the inspection is performed.

On the other hand, in the present invention, the image comparison unit 508
Then, before the difference between the detected image and the reference image is calculated, the brightness between the images is adjusted in advance. FIG. 7 is an example of a processing flow according to the present invention. First, from the inspection image and the reference image, the target area is a portion where the brightness is uniform (low contrast area) like the area 1a in FIG. 1 and a portion where the brightness changes abruptly like the pattern edge portion of the area 1b ( High contrast area) (step 71). As an example of the contrast decomposition method, for the contrast at the position (i, j) in the target area, the brightness values A to I of the nine neighboring pixels are used as shown in FIG. 8, and the differential values Dx, Y in the X direction are used. The differential value Dy in the direction is calculated by the following formula, and the larger one is defined as the contrast C (i, j).

Dx = B + H-2 × E Dy = D + F-2 × E C (i, j) = max (Dx, Dy) As another example, as shown in FIG. About the luminance values A to D of the four neighboring pixels, and the maximum value −
The minimum value is the contrast C (i, j) at that pixel.

C (i, j) = max (A, B, C, D) -m
in (A, B, C, D) In addition to the above two methods, the contrast calculation method for the pixel of interest may be various calculation methods for obtaining the luminance change amount in the vicinity. In this way, the contrast of each pixel is calculated in the detected image and the reference image, and the contrast is determined by taking the average of the corresponding pixels in the detected image and the reference image. In this way, the contrast at each position in the inspection target area is calculated, and is decomposed into several stages according to the contrast value. Hereinafter, what is decomposed into several stages is referred to as a contrast category.

In this way, after the inspection target area is decomposed into several contrast categories, a correction coefficient for adjusting the brightness for each category is calculated (step 72 in FIG. 7). An example of this will be described with reference to FIG. 10. First, with respect to pixels belonging to the same contrast category, the horizontal axis represents the brightness value in the detected image and the vertical axis represents the brightness value in the corresponding reference image. Make a figure. Then, an approximate straight line is obtained from the scatter plot. 1 of FIG.
01 is an approximate straight line obtained from a scatter diagram of pixels belonging to a certain category. There are various methods for calculating the approximate straight line, and as an example thereof, there is a least-squares approximation (a method for obtaining a straight line that minimizes the total sum of distances from each point). Then, the calculated inclination a of the approximate straight line and the Y intercept b become the correction coefficient for the contrast category. The correction coefficient calculated in this way is used to perform correction by adjusting the brightness (73 in FIG. 7). In reality, assuming that the luminance value is F (i, j) for each pixel of the detected image, the corrected luminance value D
(I, j) is corrected using the following formula.

D (i, j) = F (i, j) × a + b Then, the difference between the corrected brightness value D (i, j) of the detected image and the brightness value G (i, j) of the reference image is obtained. (Step 74 in FIG. 7), a portion having a difference value larger than the set threshold value TH is set as a defect candidate (step 75 in FIG. 7).

Here, the corrected brightness value D (i, j) is
The closer the pixel is to the approximate straight line in the scatter diagram, the closer to the brightness value G (i, j) of the reference image. That is, strong correction is performed. Therefore, the method of creating the scatter plot may be changed according to the contrast. For example, as described above, in the high-contrast region, the difference value becomes large even if there is a slight positional deviation. Therefore, the high contrast area is strongly corrected to adjust the brightness so that the difference value becomes small. For example, as shown in FIG. 11A, in a low contrast area, linear approximation is performed from a distribution area of a wide scatter plot, and as shown in FIG. 11B or 11C, a high contrast area is classified into categories. It may be finely performed and linear approximation may be performed in a narrower scatter plot area. Further, since uneven brightness is likely to occur in the low contrast area, conversely, it is within the scope of the present invention to finely categorize the area having a lower contrast and strongly adjust the brightness. Moreover, of course,
The same correction may be performed on all contrasts.
Further, it is possible to constantly monitor the accuracy of misregistration detection and make the brightness adjustment stronger than usual in a high-contrast area only when the correct misregistration amount is not calculated.

The subdivision of categories may be performed according to the contrast value, or may be performed using another feature amount.
For example, the difference between defect and brightness unevenness is evaluated from a certain feature, and in the area having the feature as the brightness unevenness, the brightness is strongly adjusted by obtaining an approximate straight line from the pixels in the vicinity of the scatter plot. , In the area having the feature quantity that seems to be a defect, the approximation of the brightness is weakened by obtaining the approximate straight line from the distant pixels in the scatter diagram.

As described above, according to the present invention, in the inspection for comparing two images and detecting the defect from the difference value, the brightness of the high contrast area is easily adjusted as necessary in the high contrast area due to the misregistration due to the displacement. Do a strong fit,
Brightness is strongly adjusted in areas with uneven brightness. In addition, the brightness adjustment is weakened in a region having a feature as a defect. FIG. 12 (c) shows FIG. 12 (a).
4 is a waveform of a difference value after brightness adjustment according to the present invention when a correct positional deviation amount as shown in (corresponding to FIG. 3A) is not detected. As shown in FIG. 12 (b) (corresponding to FIG. 3 (b)), the level of the false alarm is reduced as compared with the case where the brightness adjustment is not performed, and one threshold TH is set.
The defect can be detected in 3. FIG. 13 (d) corresponds to FIG. 13 (c) (FIG. 4 (c)) when there is uneven brightness in FIG. 13 (a), (b) (corresponding to FIG. 4 (a), (b)). 7 is a waveform of a difference value after the brightness matching according to the present invention with respect to the (corresponding) difference image.

In both cases of FIG. 12 (c) and FIG. 13 (d), the difference value can be reduced by adjusting the brightness to the area that should not be detected as a defect. . On the other hand, since the brightness adjustment is weakened in the defective portion, the difference value does not become so small. Therefore, conventionally, the threshold value is set to TH for all areas.
Although it is set to 2 or two thresholds of TH and TH2 are set to avoid the occurrence of false information, according to the present invention,
It is possible to avoid the occurrence of false alarms due to displacement and uneven brightness without lowering the sensitivity, and to enable high-sensitivity inspection and easy sensitivity adjustment only at the low threshold TH3.

Although one embodiment of the present invention has been described with reference to the comparative inspection image in the optical appearance inspection apparatus for the semiconductor wafer, the electron beam pattern inspection and the DUV inspection are performed.
It can also be applied to a comparison image in a system inspection. Also, the inspection target is not limited to the semiconductor wafer,
If the defect detection is performed by comparing the images, for example, a TFT substrate, a photomask, a printed board, or the like can be applied.

[0033]

As described above, according to the present invention,
Brightness is adjusted according to the contrast. In particular, the occurrence of false information is reduced by performing strong matching as necessary in a high-contrast area where false information is likely to occur due to displacement. In addition, the occurrence of false alarms is reduced by adjusting the brightness to the uneven brightness. As a result, it becomes possible to set a low threshold value, and a highly sensitive inspection can be realized. In addition, by setting only one threshold value, both the occurrence of false alarms and the detection of defects are compatible, and the sensitivity can be easily adjusted.

[Brief description of drawings]

FIG. 1 is a diagram showing luminance waveforms on a 1D-1D ′ line of (a) an inspection target image and (B) a difference image between inspection target images 11 and 12.

2A is a diagram showing a difference image between the inspection symmetric images 11 and 12 in FIG. 1A and FIG. 2B is a diagram showing a luminance waveform on a 1D-1D ′ line of the difference image.

3A shows a relationship between a luminance image on the 1D-1D ′ line of the difference image between the inspection symmetrical images 11 and 12 in FIG. 1A and a threshold value TH and TH2. Figure, (c)
7 is a diagram showing the relationship between the luminance waveform on the 1D-1D ′ line of the difference image and the threshold values TH and TH2.

4A and 4B are images to be inspected when there is uneven brightness between comparison chips, FIG. 4C is a difference image between FIGS. 4A and 4B, and FIG. , (C) are diagrams showing luminance waveforms on the 1D-1D ′ line and threshold values TH and TH2.

FIG. 5 is a block diagram showing a schematic configuration of an inspection device according to the present invention.

FIG. 6 is a plan view of a semiconductor wafer to be inspected.

FIG. 7 is a flowchart showing a processing flow of an image comparison unit of the present invention.

FIG. 8 is an image diagram of a pixel showing an example of a contrast calculation method for a pixel of interest.

FIG. 9 is an image diagram of a pixel showing an example of a contrast calculation method for a pixel of interest.

FIG. 10 is a scatter diagram showing a relationship between respective luminance values of the inspection image and the comparison image.

11 (a) to 11 (c) are scatter diagrams showing a relationship between respective luminance values of an inspection image and a comparison image.

12A is a difference image corresponding to FIG. 3A,
FIG. 3B is a luminance waveform on the 1D-1D ′ line corresponding to FIG. 3B, and FIG. 3C is a luminance waveform diagram on the 1D-1D ′ line after the brightness adjustment according to the present invention. .

13 (a) and (b) are FIG. 4 (a) and (b).
4C is a difference image between (a) and (b) corresponding to FIG. 4C, and (d) is a book. FIG. 6 is a luminance waveform diagram on a 1D-1D ′ line after performing brightness matching according to the invention.

[Explanation of Codes] 11 ... Detection image 12 ... Reference image 51 ... Sample
52 ... Stage 53 ... Detector 501 ... Light source
502 ... Illumination optical system 503 ... Objective lens 504 ... Image sensor 55 ... Image processing unit 54
AD conversion unit 505 Preprocessing unit 506 Delay memory 507 Position shift detection unit 508 Image comparison unit 509 Feature extraction unit 56 Overall control unit
Reference numeral 510 ... User interface unit 511 ... Storage device 512 ... Mechanical controller 101 ... Approximate straight line

   ─────────────────────────────────────────────────── ─── Continued front page    (72) Inventor Takashi Okabe             292 Yoshida-cho, Totsuka-ku, Yokohama-shi, Kanagawa             Inside the Hitachi, Ltd. production technology laboratory F term (reference) 2F065 AA49 BB01 CC20 FF04 JJ03                       JJ26 MM02 QQ03 QQ31 RR08                 2G051 AA51 AA56 AB01 AB07 BB03                       CA03 CB01 DA07 EA11 EA12                       EA14 EA24 EB01 ED07 FA01                 5B057 AA03 BA02 CA12 CA16 DA03                       DB02 DC02 DC32                 5L096 BA03 CA02 FA06 FA14 FA69                       GA08

Claims (14)

[Claims] 1. A defect inspection method for detecting a defect by comparing an image of a sample to be inspected with a reference image, wherein a displacement amount between an inspection target image and a reference image is calculated, and the calculated displacement amount is calculated. A defect inspection method characterized by comparing an inspection target image with a reference image by using 2. The defect inspection method according to claim 1, wherein when detecting a defect from the difference between the inspection images, the inspection sensitivity is changed according to the contrast of the image to detect the defect. Defect inspection method 3. The defect inspection method according to claim 1, wherein when detecting a defect from the difference between the inspection images, the defect is detected with high sensitivity in a high contrast portion of the image and with high sensitivity in a low contrast portion. Defect inspection method characterized by 4. The defect inspection method according to claim 1, wherein the pattern edge portion of the sample to be inspected is inspected with low sensitivity. 5. The defect inspection method according to claim 1, wherein, when a defect is detected from the difference between the inspection images, the difference in brightness between the inspection target image and the reference image is equal to or more than a specific threshold value. Defect inspection method characterized by determining a defect 6. The defect inspection method according to claim 1, wherein the defect determination threshold value according to claim 5 is made variable according to the contrast of an image to detect the defect. 7. The defect inspection method according to claim 1, wherein the defect determination threshold value according to claim 5 or 6,
A defect inspection method characterized in that a defect is detected by setting a high value in a high contrast part of an image and a low value in a low contrast part. 8. The defect inspection method according to claim 1, wherein the brightness is adjusted so that the difference between the inspection target image and the reference image is reduced. 9. The defect inspection method according to claim 1, wherein the brightness is adjusted according to the contrast of the images so that the difference between the inspection target image and the reference image is reduced. Method 10. The defect inspection method according to claim 1, wherein brightness is adjusted in a region where uneven brightness occurs between the inspection target image and the reference image. 11. The defect inspection method according to claim 1, wherein when calculating the positional deviation amount between the inspection target image and the reference image, the calculation accuracy of the positional deviation amount is monitored, and the calculation error is large. The defect inspection method is characterized in that the brightness is adjusted so that the difference between the image to be inspected and the reference image in the position shift portion becomes small. 12. The defect inspection method according to claim 1, wherein the inspection sensitivity can be adjusted with one parameter. 13. A defect inspection apparatus for detecting a defect by comparing an image of a sample to be inspected with a reference image, the stage mounting the sample to be inspected, and an illumination for irradiating the sample. An imaging optical system that forms an image of reflected light from the sample on an image sensor, a circuit that converts an output signal of the image sensor into a digital image, a memory that stores the circuit, and the sample using the digital image. Defect inspection apparatus including an image processing unit for detecting a defect of the substrate and an output monitor for displaying a defect detection result 14. The image processing unit according to claim 12, wherein a position shift amount between the inspection target image and the reference image to be compared is calculated, and the position where the inspection target image and the reference image are compared using the calculated position shift amount. From the difference detection unit, the brightness correction unit that adjusts the difference in brightness between the inspection target image and the reference image according to the contrast, and the difference between the inspection target image and the reference image after the brightness is adjusted. Defect inspection device and defect inspection method characterized by including a defect extraction unit for detecting a defect