JP4013510B2 - Defect inspection method and apparatus - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention compares images of objects such as semiconductor wafers, TFTs, photomasks, etc. obtained using light or laser with reference images stored in advance, and inspects fine pattern defects and foreign materials from the differences. The present invention relates to a defect inspection method and apparatus therefor. In particular, the present invention relates to a defect inspection method and apparatus suitable for visual inspection of a semiconductor wafer.
[0002]
[Prior art]
As a conventional technique for detecting a defect by comparing an inspection object image with a reference image, a method described in Japanese Patent Laid-Open No. 05-264467 is known.
[0003]
In this method, a sample to be inspected in which repetitive patterns are regularly arranged is sequentially imaged by a line sensor, compared with an image with a time delay corresponding to the repetitive pattern pitch, and the mismatched portion is detected as a pattern defect. . However, in reality, there are stage vibrations, tilt of the target, etc., 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 determine the amount of displacement. Then, after aligning the two images based on the obtained misregistration amount, the difference between the images is taken, and when the difference is larger than a prescribed threshold value, it is determined as a defect, and when it is smaller, it is determined as a non-defect. judge.
[0004]
[Problems to be solved by the invention]
As described above, in the conventional technique, detection of misalignment between the inspection target image and the reference image → alignment → image comparison, that is, defect inspection is performed by the procedure of calculating the difference between two images → defect extraction. If the correct amount of misalignment is not found sometimes, alignment at the wrong position is performed. In this case, in the aligned image, the difference in the aligned image does not increase in a region where the brightness change amount is small, but the difference increases in a region where the brightness change amount is large. For example, 11 in FIG. 1A is an image to be inspected, 12 is an example of a reference image, 1a is a uniformly bright background region, and 1b is a region having a dark pattern on a bright background. Further, the inspection target image 11 has a defect 1c. In the image of this example, the waveform of the luminance value at the position 1D-1D ′ is as shown in FIG.
[0005]
Here, when the misalignment amounts of 11 and 12 are obtained correctly, the difference image after the alignment of 11 and 12 is as shown in FIG. The difference image is an image displayed as a difference in density according to a difference value at each corresponding position between the inspection target image and the reference image. If a portion where the difference value is equal to or greater than a specific threshold value TH is defined as a defect, only 11 defects 1c in FIG. 2 are detected. However, when the misregistration amounts of 11 and 12 are calculated incorrectly, the difference image after the alignment is as shown in FIG. 3A, and the luminance value changes greatly like the edge of the pattern in the region 1b. In the region, the difference value becomes large even if the positional deviation is minute, and is detected as a defect. This should not be detected as a defect. In other words, it is a false report.
[0006]
Conventionally, as one method for avoiding the generation of a false alarm as shown in FIG. 3A, the threshold value TH is increased to TH2 as shown in FIG. 3B. This lowers the sensitivity, and a defect having a difference value less than or equal to the edge portion cannot be detected. As another method, as shown in FIG. 3 (c), the threshold value is set high as TH2 in a high-contrast portion where false information is likely to occur, and the threshold value TH is set in a low-contrast portion where false information is difficult to occur. Although set to be lower than TH2, a plurality of threshold values are handled, and sensitivity adjustment becomes complicated.
[0007]
Further, when the inspection object is a semiconductor wafer, even if the positional deviation amount is correctly obtained, if there is a difference in film thickness within the wafer, 4a in FIG. 4A and 4B in FIG. As shown in 4b, a difference in brightness occurs in the same pattern of the inspection target image and the reference image, and the difference value becomes large as shown in 4c in FIG. 4C. This is also false information, and in order not to detect it, the threshold value TH must be increased to TH2 as shown in FIG. 4 (d). Alternatively, threshold values must be set separately for areas with uneven brightness and areas without brightness.
[0008]
In order to solve such problems of the conventional inspection technique, an object of the present invention is to compare a target image with a reference image and detect a defect from the difference in a high contrast pattern in the target image. The inspection is performed by adjusting the brightness so that the difference is reduced at the edge portion, so that the false alarm due to the alignment error is reduced without increasing the threshold value TH, and the highly sensitive defect inspection method and apparatus. Is to provide. Further, in the inspection for semiconductor wafers, the brightness unevenness of the pattern caused by the difference in film thickness is inspected by adjusting the brightness between images, so that the brightness can be increased without increasing the threshold value TH. The purpose is to realize high-sensitivity defect inspection by reducing false information caused by Samurai.
[0009]
[Means for Solving the Problems]
In order to achieve the above object, the present invention includes means for detecting defects by changing inspection sensitivity in accordance with the contrast of an image in an inspection for detecting defects from the difference between two images by comparison. . As an effective example, there is a means to detect defects with low sensitivity in high contrast areas where the difference is large even if there is a slight misalignment, and high sensitivity in low contrast areas where the difference is small. Yes.
[0010]
Further, in an inspection for detecting a portion where the difference in brightness between two images is equal to or greater than a specific threshold value as a defect, there is provided means for changing the threshold value according to the contrast of the image. As one effective example, there is provided means for setting a threshold value high in a high contrast portion and low in a low contrast portion.
[0011]
Further, there is provided means for performing correction so as to reduce the difference between the inspection target image and the reference image according to the contrast of the image. As an effective example of this, even if there is a slight misalignment, the difference is large, and in high-contrast areas where false detections (false reports) are likely to occur, the brightness between images is adjusted in advance so that the difference is small. Therefore, in the final defect detection process, there is provided means for performing defect inspection with one low threshold value, that is, with high sensitivity for all contrasts. Furthermore, there is provided means for monitoring the positional deviation accuracy and adjusting the brightness between images so that the difference is reduced in a high contrast portion where misdetection due to the positional deviation is likely to occur only when a misalignment occurs. Yes.
[0012]
In addition, when the inspection target is a semiconductor wafer, if there is a difference in brightness in the same pattern between images due to a difference in film thickness within the wafer, the brightness is unevenly adjusted by adjusting the brightness in advance. Regardless of this, there is provided a means for performing defect inspection at one low threshold.
[0013]
By providing these means, a defect inspection method and a defect inspection apparatus capable of adjusting sensitivity with a single threshold value for all inspection target areas are provided.
[0014]
DETAILED DESCRIPTION OF THE INVENTION
Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings.
[0015]
As an example, taking a defect inspection method in an optical appearance inspection apparatus for a semiconductor wafer 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 stage on which the sample 51 is mounted and can move at least in the XY plane, 53 is a detection unit, and is emitted from the light source 501 and the light source 501 that irradiate the sample 51 An illumination optical system 502 that condenses light, an objective lens 503 that forms an optical image obtained by illuminating the sample 51 with the illumination light collected by the illumination optical system 502 and reflecting it, and an optical image formed The image sensor 504 receives light and converts it into an image signal corresponding to brightness. An image processing unit 55 processes the image detected by the detection unit 53 and calculates defect candidates in the wafer as a sample.
[0016]
The image processing unit 55 includes an AD conversion unit 54 that converts an input signal from the detection unit 53 into a digital signal, a preprocessing unit 505 that performs image correction such as shading correction and dark level correction from the digital signal, and a digital signal to be compared. A delay memory 506 that is stored as a reference image signal, a displacement detection unit 507 that detects the amount of displacement between the digital signal (detected image signal) detected by the detection unit 53 and the reference image signal of the delay memory 506, and is calculated. An image comparison unit 508 that compares the image signals of the detected image and the reference image using the misregistration amount and outputs a portion where the difference value is larger than a specific threshold value as a defect candidate; The feature extraction unit 509 calculates the above.
[0017]
A general control unit 56 is a user interface unit 510 having a display unit and an input unit for accepting changes in inspection parameters (threshold values used in image comparison, etc.) from the user and displaying detected defect information. The storage device 511 stores the feature amount and image of the detected defect candidate, and the CPU performs various controls. A mechanical controller 512 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 commands from the overall control unit 56.
[0018]
As shown in FIG. 6, the semiconductor wafer 51 to be inspected is regularly arranged with a large number of chips having the same pattern. In the inspection apparatus of FIG. 5, the images at the same position of two adjacent chips, for example, the region 61 and the region 62 of FIG. 6 are compared, and the difference is detected as a defect. Explaining the operation, the overall control unit 56 continuously moves the semiconductor wafer 51 as a sample by the stage 52. In synchronization with this, the image of the chip is taken in from the detection unit 53 sequentially. The image sensor 504 of the detection unit 53 outputs the input signal to the image processing unit 55. In the image processing unit 55, 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. The positional deviation detection unit 507 is delayed by an amount of time that the stage 1 is moved by the chip interval, which is output from the image signal (detection image signal) of the inspection target chip output from the preprocessing unit 505 and the delay memory 506. An image signal, that is, an image signal (reference image signal) of a chip immediately before the inspection target chip is input as a set.
[0019]
The image signals of these two chips that are sequentially input in synchronization with the movement of the stage are the same at the same location if the stage movement speed is uneven, the stage vibrates, or the wafer set on the stage is tilted. It is not a signal. For this reason, the misregistration detection unit 507 calculates the misregistration 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 calculation of the positional shift amount is sequentially performed 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 performs image alignment using the calculated misregistration amount, compares the detected image with the reference image, and outputs a region whose difference value is larger than a specific threshold value as a defect candidate. The feature extraction unit 509 edits each of a plurality of defect candidates, such as deleting a small one as noise or merging neighboring defect candidates as one defect, so that the position, area, size, etc. in the wafer Is calculated and output as the final defect. These pieces of information are stored in the storage device 511. Further, for example, it is displayed on the screen of the display means via the user interface unit 510 and presented to the user.
[0020]
Here, when the image comparison unit 508 obtains defect candidates from simple difference values, they are not all true defects. An example of this will be described below. Reference numerals 11 and 12 in FIG. 1A are detected images and reference images, and both images have a dark cross pattern in a uniformly bright background. Further, only the detected image 11 has the defect 1c. The graph of FIG. 1B is a waveform of the luminance value at the position 1D-1D ′ of the detected image 11. As shown in this graph, the image has a region 1a having a high luminance and little change in luminance, that is, a low contrast region 1a, and a region 1b having a large luminance change in the edge portion of the pattern, that is, a high contrast region 1b. FIG. 2A shows an image of a difference value at each corresponding position when a correct misregistration amount is calculated by the misregistration detection unit 507 and alignment is performed on these images, that is, the difference is calculated. This is an image in which a small portion is dark and a large portion is brightly displayed. FIG. 2B shows a waveform of the difference value at the position 1D-1D ′. If a region having a difference value equal to or greater than the threshold value TH is defined as a defect, only the region of the defect 1c is detected in this case.
[0021]
On the other hand, FIGS. 3A and 3B are an image of a difference value and a waveform of the difference value when the misregistration amount is erroneously calculated and incorrect alignment is performed. FIG. 3A shows a large difference value even if the positions of the detection image 11 and the reference image 12 are slightly deviated in a low contrast region where the amount of change in brightness is small as in the region 1a shown in FIG. Although not shown, in the high contrast region where the amount of change in brightness is large as in the region 1b, the difference value becomes large even with a slight positional deviation. In this case, as shown in FIG. 3B, if a region having a threshold value TH or higher is set as a defect candidate, a portion where the difference value becomes large due to such a positional deviation is also detected as a defect. These should not be detected by nature. Hereinafter, what is not a true defect is described as false information. Conventionally, in order to avoid detection of false information due to misalignment, as one method, the threshold value is increased from TH to TH2 as shown in FIG. 3B, but this makes it impossible to detect a defect with a small difference value. End up. That is, by using TH2 as a threshold value in order to avoid the generation of false information, the inspection is performed with reduced sensitivity. Further, as another conventional method, as shown in FIG. 3C, the threshold value is set to TH2 in the high contrast region and the threshold value is set to TH in the low contrast region. Therefore, the sensitivity adjustment is complicated for the user.
[0022]
Further, when the film thickness of the semiconductor wafer 51 is not uniform, a difference in brightness occurs between the inspection target image and the reference image. For example, the three crosses arranged in 4a in FIG. 4A and 4b in FIG. 4B are corresponding patterns in the inspection object image 11 and the reference image 12, but the brightness varies depending on the difference in film thickness. Are greatly different (hereinafter referred to as uneven brightness). Further, only the detected image 11 has the defect 1c. 4A to 4C are images of the difference values at the corresponding positions when the correct misregistration amount is calculated by the misregistration detection unit 507 and alignment is performed on these images. However, even in the same pattern, the difference value becomes large in the portion where the brightness is uneven. FIG. 4D is a waveform on the 1D-1D ′ line in FIG. 4C, which is a difference value image at the position 1D-1D ′. If a region having a difference value equal to or greater than the threshold value TH is determined as a defect, in addition to the defect 1c in FIG. 4A, a difference between the cross patterns 4a and 4b in which the difference value increases due to uneven brightness is also detected. The But these are false reports. In order to avoid detection of false information due to such uneven brightness, the threshold value is increased from TH to TH2 and inspection is performed with low sensitivity as in the case of occurrence of false information due to positional deviation, or uneven brightness is detected. Some methods have been used to adjust the sensitivity with multiple thresholds, such as setting the threshold value to TH2 in certain areas and setting the threshold value to TH in non-uniform brightness areas. .
[0023]
On the other hand, in the present invention, the image comparison unit 508 performs brightness adjustment between images before calculating the difference between the detected image and the reference image. 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 region is a portion where the brightness is uniform (low contrast region) like the region 1a in FIG. 1 and a portion where the brightness changes sharply like the pattern edge portion of the region 1b ( (High contrast region) (step 71). As an example of the contrast decomposing method, the contrast at the position (i, j) in the target region is obtained by using the luminance values A to I of the pixels near 9 as shown in FIG. The direction differential value Dy is calculated by the following equation, and the larger one is defined as contrast C (i, j).
[0024]
Dx = B + H-2 × E
Dy = D + F-2 × E
C (i, j) = max (Dx, Dy)
As another example, as shown in FIG. 9, the luminance values A to D of four neighboring pixels are used for each pixel of interest, and the maximum value-minimum value is used as the contrast C (i, j) at that pixel. .
[0025]
C (i, j) = max (A, B, C, D) −min (A, B, C, D)
In addition to the two methods described above, various calculation methods can be used to calculate the luminance change amount in the vicinity of the pixel of interest. Thus, the contrast of each pixel may be calculated from the detected image and the reference image, and the contrast may be determined by taking the average of the corresponding pixels of the detected image and the reference image. In this way, the contrast at each position in the inspection target area is calculated and decomposed into several stages according to the contrast value. Hereinafter, what was decomposed in several stages is described as a contrast category.
[0026]
In this way, after the inspection target region 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, for pixels belonging to the same contrast category, the horizontal axis represents the luminance value in the detected image, and the vertical axis represents the luminance value in the corresponding reference image. Make a figure. Then, an approximate straight line is obtained from the scatter diagram. 101 in FIG. 10 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. As an example, there is a least square approximation (a method for obtaining a straight line that minimizes the sum of the distances from each point). Then, the calculated slope a and Y intercept b of the approximate straight line are correction coefficients for the contrast category. Using the correction coefficient calculated in this way, correction by matching brightness is performed (73 in FIG. 7). Actually, assuming that the luminance value of each pixel of the detected image is F (i, j), the corrected luminance value D (i, j) is corrected using the following equation.
[0027]
D (i, j) = F (i, j) × a + b
Then, a difference between the corrected luminance value D (i, j) of the detected image and the luminance value G (i, j) of the reference image is obtained (step 74 in FIG. 7), and the threshold value TH set by the difference value is obtained. The larger part is set as a defect candidate (step 75 in FIG. 7).
[0028]
Here, the corrected luminance value D (i, j) is closer to the luminance value G (i, j) of the reference image as the pixel is closer to the approximate line in the scatter diagram. That is, strong correction is performed. Therefore, how to create a scatter diagram may be changed according to the contrast. For example, as described above, in a region with high contrast, even if there is a slight positional shift, the difference value becomes large. Therefore, the region with high contrast is subjected to strong correction to adjust the brightness so that the difference value becomes small. For example, as shown in FIG. 11A, linear approximation is performed from a wide scatter diagram distribution region in a low contrast region, and categorization is performed in a high contrast region as shown in FIG. 11B or 11C. It is only necessary to perform finely and perform linear approximation in a narrower scatter diagram area. In addition, since uneven brightness tends to occur in the low contrast region, it is also within the scope of the present invention to finely categorize the lower contrast region and to strongly adjust the brightness. Furthermore, as a matter of course, the same correction may be performed for the entire contrast. In addition, the accuracy of misregistration detection is constantly monitored, and only when the correct misregistration amount is not calculated, the brightness adjustment can be made stronger than usual in a high contrast region.
[0029]
The category subdivision may be performed according to the contrast value, or may be performed using another feature amount. For example, the difference between defects and uneven brightness is evaluated from certain features, and in areas with uneven brightness features, brightness adjustment is performed strongly by obtaining an approximate line from neighboring pixels in the scatter diagram. In a region having a feature amount that appears to be a defect, brightness adjustment is weakened by obtaining an approximate straight line from distant pixels in the scatter diagram.
[0030]
As described above, in the present invention, two images are compared, and in an inspection for detecting a defect from the difference value, brightness adjustment is performed as necessary in a high-contrast region where misinformation is likely to occur due to misalignment. Strongly adjust the brightness in areas with uneven brightness. Further, the adjustment of brightness is weakened in an area having a feature as a defect. FIG. 12C shows a waveform of a difference value after brightness adjustment according to the present invention when a correct positional deviation amount as shown in FIG. 12A (corresponding to FIG. 3A) is not detected. is there. 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 the defect can be detected with one threshold value TH3. it can.
FIG. 13 (d) is a diagram in FIG. 13 (c) (FIG. 4 (c)) when there is uneven brightness in FIGS. 13 (a) and 13 (b) (corresponding to FIGS. 4 (a) and (b)). 5 is a waveform of a difference value after brightness adjustment according to the present invention with respect to a difference image.
[0031]
In both the cases of FIG. 12C and FIG. 13D, the difference value can be reduced by performing brightness adjustment on an area that is not originally detected as a defect. On the other hand, since the brightness adjustment is weakened in the defective portion, the difference value is not so small. For this reason, conventionally, the threshold value is set to TH2 for the entire region, or two threshold values of TH and TH2 are set to avoid the generation of false alarms. However, according to the present invention, the sensitivity is not lowered. The generation of false information due to misalignment or unevenness of brightness is avoided, and high sensitivity inspection with a low threshold TH3 and easy sensitivity adjustment are possible.
[0032]
As described above, the embodiment of the present invention has been described by taking the comparative inspection image in the optical appearance inspection apparatus for the semiconductor wafer as an example, but it can also be applied to the comparative image in the electron beam pattern inspection and the DUV inspection. . Further, the inspection object is not limited to a semiconductor wafer, and a TFT substrate, a photomask, a printed board, or the like can be applied as long as defect detection is performed by comparing images.
[0033]
【The invention's effect】
As described above, according to the present invention, the brightness is adjusted according to the contrast. In particular, the occurrence of false information is reduced by performing strong alignment as necessary in a high-contrast portion where false information is likely to be generated due to misalignment. Moreover, the occurrence of false information is reduced by adjusting the brightness to the uneven brightness. As a result, a low threshold value can be set, and a highly sensitive inspection can be realized. In addition, the only threshold setting enables both the generation of false alarms and the detection of defects, and the sensitivity can be easily adjusted.
[Brief description of the drawings]
1A and 1B are diagrams showing luminance waveforms on a 1D-1D ′ line of a difference image between (a) an inspection target image and (B) inspection target images 11 and 12, respectively.
2A is a diagram showing a luminance image on a 1D-1D ′ line of a difference image between the inspection symmetrical images 11 and 12 of FIG. 1A and FIG.
3A is a difference image between the inspection symmetrical images 11 and 12 of FIG. 1A, and FIG. 3B is a relationship between a luminance waveform on the 1D-1D ′ line of the difference image and threshold values TH and TH2. FIG. 3C shows 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 (a) and (b), and FIG. FIG. 6B is a diagram showing a luminance waveform and threshold values TH and TH2 on the 1D-1D ′ line in FIG.
FIG. 5 is a block diagram showing a schematic configuration of an inspection apparatus 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 a pixel image diagram illustrating an example of a contrast calculation method for a pixel of interest.
FIG. 9 is a pixel image diagram illustrating an example of a contrast calculation method for a pixel of interest.
FIG. 10 is a scatter diagram showing a relationship between luminance values of an inspection image and a comparative image.
FIGS. 11A to 11C are scatter diagrams showing the relationship between the luminance values of the inspection image and the comparison image. FIGS.
12A is a difference image corresponding to FIG. 3A, FIG. 12B is a luminance waveform on the 1D-1D ′ line corresponding to FIG. 3B, and FIG. 12C is brightness according to the present invention. It is a luminance waveform figure on 1D-1D 'line after performing adjustment.
FIGS. 13A and 13B are images to be inspected when there is uneven brightness between the comparison chips corresponding to FIGS. 4A and 4B, and FIG. (D) is a luminance waveform diagram on the 1D-1D ′ line after performing brightness matching according to the present invention.
[Explanation of symbols]
DESCRIPTION OF SYMBOLS 11 ... Detection image 12 ... Reference image 51 ... Sample 52 ... Stage 53 ... Detection part 501 ... Light source 502 ... Illumination optical system 503 ... Objective lens 504 ... Image sensor 55 ... Image processing part 54 ... AD conversion part 505 ... Pre-processing part 506 ... delay memory 507 ... position shift detection unit 508 ... image comparison unit 509 ... feature extraction unit 56 ... overall control unit 510 ... user interface unit 511 ... storage device 512 ... mechanical controller 101 ... approximate straight line

Claims (13)

A defect inspection method for detecting defects by imaging a sample to be inspected,
Correcting the positional deviation between the inspection target image obtained by imaging the inspection target sample having a pattern formed on the surface and the stored reference image,
Obtaining a difference image between the image to be inspected and the reference image corrected for the positional deviation;
A defect inspection method, wherein a defect is detected with a low sensitivity in a high contrast portion and with a high sensitivity in a low contrast portion according to the contrast between the inspection object image and the reference image using the obtained difference image 2. The defect inspection method according to claim 1, wherein a portion corresponding to an edge of a pattern formed on the surface corresponding to the high contrast portion is inspected with lower sensitivity than other portions. A defect inspection method for detecting defects by imaging a sample to be inspected,
Correct the misalignment between the inspection target image obtained by imaging the inspection target sample and the stored reference image,
Brightness is adjusted according to the contrast between the inspection target image and the reference image so that the difference between the inspection target image with the misalignment corrected and the reference image becomes small, and the brightness is adjusted according to the contrast. Obtaining a difference image between the inspection target image and the reference image that has been adjusted,
A defect inspection method characterized by detecting a defect by processing the obtained difference image A defect inspection method for detecting defects by imaging a sample to be inspected,
Correct the misalignment between the inspection target image obtained by imaging the inspection target sample and the stored reference image,
The brightness is adjusted in a region where unevenness in brightness occurs between the inspection target image and the reference image in which the positional deviation is corrected,
Obtaining a difference image between the image to be inspected and the reference image subjected to the brightness adjustment,
A defect inspection method, wherein a defect is detected by processing the obtained difference image using a single threshold value input from an input means. Obtain an inspection target image of the sample by imaging the inspection target region of the sample with a pattern formed on the surface to be inspected,
Correcting the positional deviation between the acquired image to be inspected and the stored reference image;
The contrast between the inspection target image and the reference image obtained by determining the contrast between the inspection target image and the reference image at each position in the inspection target region and correcting the positional deviation by dividing the obtained contrast into several stages. The brightness is adjusted according to the divided contrast level corresponding to the corresponding area so that the difference in brightness of the corresponding area is reduced,
Find the difference between the inspection target image and the reference image combined with the brightness,
A defect inspection method, wherein a defect candidate is detected using the same threshold value over the entire area of the inspection object image with respect to the obtained difference.   Creating a scatter diagram of the luminance values of the inspection target image and the reference image, adjusting the brightness so that the difference in brightness of the corresponding portions of the inspection target image and the reference image is reduced, A correction coefficient of an approximate line for correcting the brightness is obtained from the created scatter diagram, and correction is performed using the obtained approximate line so that a difference in brightness between the inspection target image and the reference image is reduced. The defect inspection method according to claim 5, wherein: 6. The contrast between the inspection target image and the reference image is divided into several stages by dividing the higher contrast side finer than the lower contrast side. Defect inspection method.   When calculating the misregistration amount between the inspection target image and the reference image, the calculation accuracy of the misregistration amount is monitored, and if the calculation error is large, the difference between the inspection target image and the reference image at the misalignment portion becomes small. 6. The defect inspection method according to claim 5, wherein brightness adjustment is performed as described above. An image acquisition means for acquiring an inspection target image of the sample by imaging an inspection target region of the sample in which a pattern is formed on the surface to be inspected;
A positional deviation correction means for obtaining a positional deviation between the inspection target image acquired by the image acquisition means and the stored reference image and correcting the positional deviation;
The brightness adjustment is performed according to the brightness of the corresponding area so that the brightness difference of the corresponding area between the inspection target image and the reference image whose position shift is corrected by the position shift correction unit is reduced. Brightness correction means for performing
A high contrast portion between the inspection object image and the reference image with respect to the obtained difference by comparing the inspection object image with the brightness adjusted by the brightness correction unit and the reference image to obtain a difference. In the low sensitivity, image comparison means to detect defect candidates with high sensitivity in the low contrast part,
A defect inspection apparatus comprising: An image acquisition means for acquiring an inspection target image of the sample by imaging an inspection target region of the sample in which a pattern is formed on the surface to be inspected;
A positional deviation correction means for obtaining a positional deviation between the inspection target image acquired by the image acquisition means and the stored reference image and correcting the positional deviation;
Brightness according to the contrast between the inspection target image and the reference image so that the difference in brightness of the corresponding region between the inspection target image and the reference image whose positional deviation has been corrected by the positional shift correction means is reduced. Brightness correction means for adjusting the thickness,
Image comparison means for detecting defect candidates by comparing the inspection target image and the reference image that have been adjusted in brightness by the brightness correction means to obtain a difference;
A defect inspection apparatus comprising: An image acquisition means for acquiring an inspection target image of the sample by imaging an inspection target region of the sample in which a pattern is formed on the surface to be inspected;
A positional deviation correction means for obtaining a positional deviation between the inspection target image acquired by the image acquisition means and the stored reference image and correcting the positional deviation;
The contrast between the inspection target image acquired by the image acquisition unit and the reference image is obtained at each position in the inspection target region, and the obtained contrast is divided into several stages, and the positional deviation correction unit corrects the positional deviation. The brightness for which the brightness is adjusted according to the divided contrast level corresponding to the corresponding area so that the brightness difference of the corresponding area between the inspection target image and the reference image is reduced. Correction means;
The inspection target image corrected for the difference in brightness by the brightness correction means is compared with the reference image to obtain a difference, and the same threshold is applied to the obtained difference over the entire region of the inspection target image. Image comparison means for detecting defect candidates using values;
A defect inspection apparatus comprising:   The brightness correction means corrects the difference in brightness between the inspection object image and the reference image, creates a scatter diagram of luminance values of the inspection object image and the reference image, and creates the scatter diagram from the created scatter diagram. 12. A defect inspection apparatus according to claim 11, wherein a correction coefficient of an approximate line for correcting brightness is obtained, and a difference in brightness between the inspection object image and the reference image is corrected using the obtained approximate line. . The brightness correction unit divides the contrast between the inspection target image acquired by the image acquisition unit and the reference image into several stages, and the higher contrast side is set to be lower than the lower contrast side. The defect inspection apparatus according to claim 11, wherein the inspection is performed by finely dividing the defect inspection apparatus.

Images