JP5549364B2 - Wafer defect inspection apparatus and wafer defect inspection method - Google Patents

Description

  The present invention relates to a wafer defect inspection apparatus that inspects a defect of a wafer based on an image obtained by imaging a wafer.

  A wafer defect inspection apparatus for inspecting defects on the front and back surfaces and inside of a wafer is known. In such a wafer defect inspection apparatus, for example, infrared light is irradiated from one side of the main surface of the wafer, an image of the wafer is taken from the other side, and an image is obtained with respect to the taken image. By performing analysis processing, defects in the wafer are inspected.

  In defect inspection of such wafers, for example, by sampling a part of wafers for each lot in which a plurality of wafers are combined and performing actual imaging, the average luminance of the wafer image is appropriately corrected. An imaging condition (recipe) to be included within a detectable range (defect detectable range) is determined, and defect inspection is performed on all wafers of the lot using the recipe.

  As a technique related to image capturing when detecting defects on the front and back surfaces and inside of the wafer by transmitted light illumination, the value of the specific resistance of the wafer is acquired in advance, and the infrared illumination means is used according to the value of the specific resistance. There is known a technique for adjusting the illuminance and adjusting the sensitivity of an imaging unit to infrared light (see, for example, Patent Document 1).

Japanese Patent No. 4358889

  As described above, conventionally, an image of a wafer is taken according to the same recipe for each wafer of the same lot.

In recent years, low resistivity silicon wafers (for example, P ⁺⁺ wafers (0.005 to 0.01 Ω · cm)) have been manufactured as substrate wafers for epitaxial silicon wafers. On the other hand, when the same recipe is applied, there is a problem that the average luminance in the defect detectable range cannot be obtained in some wafer images.

  FIG. 1 is a diagram showing the relationship between the average luminance of each wafer for each lot to be measured and the defect detectable range.

As shown in FIG. 1, when determining the recipe to be applied to each lot was an image of the wafer by applying the recipe for each wafer in the lot, the lot (figure P ⁺⁺ wafer In the first lot of P ⁺⁺ wafers in 1), the average brightness of the wafer image may fall outside the defect detectable range. For this reason, there exists a possibility that a defect cannot be detected appropriately from the image of the imaged wafer.

  By the way, whether or not the defect of the wafer can be properly detected is greatly related to how to process the image of the captured wafer.

  The present invention has been made in view of the above problems, and an object of the present invention is to provide a technique capable of appropriately detecting a defect from an image of a wafer.

A wafer defect inspection apparatus according to a first aspect of the present invention includes a wafer mounting unit for mounting a wafer to be inspected, an irradiation unit for irradiating infrared light onto the wafer, and the infrared light irradiation. An image pickup means for picking up an image of the wafer, and a wafer defect inspection apparatus for inspecting a defect of the wafer based on the image of the wafer picked up by the image pickup means, each in the range of the inspection target of the wafer in the image A reference average luminance calculating means for calculating a luminance obtained by averaging the luminance of a plurality of pixels within a predetermined range including the pixel among a plurality of pixels arranged in a predetermined linear direction as a reference average luminance for each pixel; By comparing the difference value calculation means for calculating a difference value between the reference average luminance in each pixel and the luminance of each pixel, the difference value for each pixel and a predetermined threshold value, Determination means for determining whether a candidate pixel Recessed, based on the defective pixel candidate, and a test unit for testing the defects in the wafer. According to the wafer defect inspection apparatus, since the difference value between the reference average luminance in each pixel and the luminance of each pixel is compared with a threshold value to determine whether or not it is a defect candidate pixel, Thus, the influence of the difference in brightness level can be reduced, and defect candidate pixels can be detected more appropriately.

  The wafer defect inspection apparatus further includes a threshold value determining unit that determines a predetermined threshold value for each pixel based on a reference average luminance in each pixel. According to such a wafer defect inspection apparatus, since the threshold value is determined based on the reference average luminance, it is possible to determine an appropriate threshold value for each image and detect a defect appropriately.

  In the wafer defect inspection apparatus, the threshold value determining means determines a value obtained by multiplying the reference average luminance by a predetermined value as the predetermined threshold value. According to such a wafer defect inspection apparatus, the threshold value can be easily and appropriately determined from the reference average luminance.

Further, in the wafer defect inspection apparatus, the reference average luminance calculating means may be configured to check the inspection target when a pixel within a predetermined range in a predetermined linear direction corresponds to a pixel in a non-inspection area near the outer periphery of the wafer. The reference average luminance is calculated assuming that the luminance of the pixels in the outer region is the luminance of the pixels at the boundary with the region to be inspected. According to such a wafer defect inspection apparatus, it is possible to reduce the influence on the reference average luminance due to the luminance of the pixels outside the inspection target range, and it is possible to detect defect candidate pixels more appropriately.

Further, in the wafer defect inspection apparatus, the reference average luminance calculating means may be configured to check the inspection target when a pixel within a predetermined range in a predetermined linear direction corresponds to a pixel in a non-inspection area near the outer periphery of the wafer. The reference average luminance is calculated on the assumption that the luminance of the pixels in the outer region is the luminance of the pixels in a symmetric position with respect to the boundary with the non-inspection region on a straight line in a predetermined linear direction. According to such a wafer defect inspection apparatus, it is possible to reduce the influence on the reference average luminance due to the luminance of the pixels outside the inspection target range, and it is possible to detect defect candidate pixels more appropriately.

Further, in the wafer defect inspection apparatus, the inspection means includes defect candidate area specifying means for specifying a defect candidate area based on the defect candidate pixels, unevenness of a luminance profile in the defect candidate area, luminance in the defect candidate area and a reference average Based on the luminance ratio, which is the ratio of the maximum difference with the luminance and the reference average luminance, the average luminance change rate in the defect candidate region, the area of the defect candidate region, the circularity of the defect candidate region, or the center of gravity of the defect candidate region Defect type determination means for determining whether or not a predetermined defect type is satisfied based on at least one of the ratio of the long width to the short width. According to such a wafer defect inspection apparatus, it is possible to appropriately determine a defect candidate area corresponding to a predetermined defect type.

  In the wafer defect inspection apparatus, the inspection unit further includes a pass / fail determination unit that determines whether the wafer passes the product based on the number of defect areas corresponding to a predetermined defect type. According to the wafer defect inspection apparatus, it is possible to appropriately determine whether or not the wafer is acceptable as a product.

  A wafer defect inspection method according to a second aspect of the present invention is a wafer defect inspection method for inspecting a wafer for defects based on an image of a wafer to be inspected. Calculating a luminance obtained by averaging the luminance of a plurality of pixels within a predetermined range including the pixel among a plurality of pixels arranged in a predetermined linear direction as a reference average luminance for each pixel, Whether or not each pixel is a defective candidate pixel by calculating a difference value between the reference average luminance of the pixel and the luminance of each pixel, and comparing the difference value for each pixel with a predetermined threshold value And a step of inspecting the wafer for defects based on the defect candidate pixels. According to the wafer defect inspection method, since the difference value between the reference average luminance in each pixel and the luminance of each pixel is compared with a threshold value to determine whether the pixel is a defect candidate pixel, The influence of the difference in the gray level of the brightness can be reduced, and defect candidate pixels can be detected more appropriately.

It is a figure which shows the relationship between the average brightness | luminance of each wafer for every lot of a measuring object, and a defect detectable range. It is a block diagram of the wafer defect inspection apparatus which concerns on one Embodiment of this invention. It is a figure which shows the brightness | luminance profile example detected by the defect inspection which concerns on one Embodiment of this invention. It is a figure which shows the defect determination table which concerns on one Embodiment of this invention. It is a flowchart of the defect inspection process which concerns on one Embodiment of this invention. It is a figure explaining the relationship between the resistivity of a wafer with respect to several image acquisition conditions which concern on one Embodiment of this invention, and the average brightness | luminance in the image of a wafer. It is a flowchart of the defect detection image analysis process which concerns on one Embodiment of this invention. It is a figure explaining the binarization process which concerns on one Embodiment of this invention. It is a figure explaining the binarization process which concerns on one Embodiment of this invention. It is a figure explaining the binarization process which changed the brightness | luminance threshold value which concerns on one Embodiment of this invention. It is a figure explaining the calculation method of the moving average brightness | luminance which concerns on the modification of this invention.

  Embodiments of the present invention will be described with reference to the drawings. The embodiments described below do not limit the invention according to the claims, and all the elements and combinations described in the embodiments are essential for the solution of the invention. Is not limited.

  A wafer defect inspection apparatus according to an embodiment of the present invention will be described.

  FIG. 2 is a configuration diagram of a wafer defect inspection apparatus according to an embodiment of the present invention. FIG. 2A is a configuration diagram of the wafer defect inspection apparatus observed from the side, and FIG. 2B is a configuration diagram of the inspection stage of the wafer defect inspection apparatus observed from above.

  The wafer defect inspection apparatus 1 includes an inspection stage 3 on which a wafer W to be inspected is placed, one or more illumination units 4 that irradiate infrared light, and infrared light emitted from the illumination unit 4 with substantially the same amount of light. A light guide 5 that is shaped into a line-shaped light and projected onto the wafer W, a light receiving unit 2 as an example of one or more imaging means for capturing an image of the wafer W, and a processing device 6.

  The light receiving unit 2 includes an image line sensor having sensitivity to infrared light, and is disposed so that the light receiving surface of the image line sensor faces the inspection stage 3 side, that is, the lower side. In the present embodiment, each light receiving portion 2 is a half surface of the wafer W (the light receiving portion 2 on the left side in FIG. 2A is the half surface on the left side of the wafer W, and the light receiving portion 2 on the right side in FIG. Used to capture an image of a half wafer).

  In the wafer defect inspection apparatus 1, the line guide 5 and the image line sensor of each light receiving unit 2 are disposed so as to face each other with the inspection stage 3 interposed therebetween. That is, the line-shaped light projected by the line guide 5 is directed to the line of the image line sensor of the light receiving unit 2.

  The inspection stage 3 can move linearly in the Y direction (vertical direction in FIG. 2A, vertical direction in FIG. 2B).

  The processing device 6 is an example of a control processing unit 6a, a reference average luminance calculating unit, a difference calculating unit, a determining unit, a threshold determining unit, an inspecting unit, a defect candidate area specifying unit, a defect type determining unit, and a pass / fail determining unit. It has an image processing unit 6b and a defect determination table 6c.

The control processing unit 6a controls the sensitivity (gain) to the light amount by the image line sensor of the light receiving unit 2. Further, the control processing unit 6 a controls the image capturing speed by the image line sensor of the light receiving unit 2. In this embodiment, the control processing unit 6a controls the light receiving unit 2 by transmitting the light receiving unit setting information including the light receiving condition (sensitivity) and a part of the exposure condition (image capturing speed) to the light receiving unit 2. doing. In addition, the control processing unit 6a receives the captured image data (luminance data of each pixel) of the wafer W imaged by the light receiving unit 2, and passes it to the image processing unit 6b. In addition, the control processing unit 6 a controls the amount of infrared light emitted by the illumination unit 4. In the present embodiment, the control processing unit 6 a controls the illumination unit 4 by transmitting light source setting information including an irradiation condition (light quantity) to the illumination unit 4. The control processing unit 6a controls the moving speed of the inspection stage 3. In the present embodiment, the control processing unit 6a controls the moving speed of the inspection stage 3 by transmitting speed setting information including a part of the exposure conditions (designation of moving speed) to a driving unit (not shown) of the inspection stage 3. doing.

  The image processing unit 6b executes defect detection image analysis processing for inspecting defects on the wafer W based on the image data transferred from the control processing unit 6a. In the defect detection image analysis process, the image processing unit 6b determines a condition (defect classification condition) that defines the type of defect and a condition (pass / fail judgment condition) that determines pass / fail of the wafer (pass or fail as a product). ) Is stored in the defect determination table 6c (see FIG. 4). Detailed processing of the image processing unit 6b will be described later.

  FIG. 3 is a diagram showing an example of a luminance profile detected by defect inspection according to an embodiment of the present invention.

  As the types of defects in the wafer W, there are various types of defects such as voids (bubbles), film pinholes, dirt / stains, foreign matter, scratches / cracks, and the like. Therefore, for example, as shown in FIG. 3, depending on the defect type, the luminance of the defect area is lower than the moving average luminance described later, and the shape of the luminance profile is detected as a concave shape (defects A to E). The brightness of the region exceeds the moving average brightness, and the shape of the brightness profile is detected as a convex shape (defect F), so that the detected brightness profile differs for each defect type. If the detected brightness profile has a similar concave shape (for example, defects A to E), the defect type may not be clearly determined only by the brightness profile, but the circularity described later or The defect type can be determined based on the ratio of the longest straight line (maximum width) passing through the center of gravity G of the defect area to the shortest straight line (minimum width).

  FIG. 4 is a diagram showing a defect determination table according to an embodiment of the present invention.

  The defect determination table 6c can store a plurality of records having a classification name field 60, a defect classification condition field 61, and a pass / fail determination condition field 62. Each setting in the defect determination table 6c may be fixedly determined, or may be appropriately determined by the user using an input device (not shown).

  The classification name field 60 stores defect classification names.

  The defect classification condition field 61 stores conditions (defect classification conditions) for classifying defects for defect candidate areas described later. In the present embodiment, the defect classification condition field 61 includes a concavo-convex field 61a, a luminance ratio field 61b, a luminance change rate field 61c, an area field 61d, a circularity field 61e, and a long / short ratio field 61f. In the present embodiment, in the defect classification condition field 61, at least one of the conditions indicated by the fields 61a to 61f is set. The conditions used for classification are as follows. A value for the condition is set, and for a condition that is not used for classification, an unset symbol (“-” in the present embodiment) indicating unset is set.

  In the unevenness field 61a, the unevenness of the brightness profile, which is a condition for determining that the defect candidate area is a defect of the corresponding classification, that is, the brightness profile of the area is concave (low) with respect to the moving average brightness of the area. Condition) or convex (high state). In the luminance ratio field 61b, a luminance ratio which is a condition for determining a defect of a corresponding classification with respect to a ratio (luminance ratio) between the maximum value of the difference between the luminance in the defect candidate area and the moving average luminance and the moving average luminance (luminance ratio). The minimum value (Min) and / or the maximum value (Max) are set. In the luminance change rate field 61c, a minimum value (Min) and / or a maximum value (Max) of the luminance change rate, which is a condition for determining that the defect is a corresponding classification, is set. Here, the luminance change rate indicates the maximum value of the luminance change (absolute value of the inclination of the luminance profile) in the range designated in advance at the defect candidate region boundary passing through the center of gravity G. In the area field 61d, a minimum value (Min) and / or a maximum value (Max) of the area S, which is a condition for determining a defect of the corresponding classification, is set. In the circularity field 61e, a minimum value (Min) and / or a maximum value (Max) of circularity, which is a condition for determining that the defect is a corresponding classification, is set. In the long / short ratio field 61f, a minimum value (Min) and / or a maximum value (Max) of the long / short ratio, which is a condition for determining a defect of the corresponding classification, is set. Here, the long / short ratio indicates the ratio of a short straight line (minimum width) passing through the center of gravity G to a long straight line (maximum width) for the target region.

  The pass / fail judgment condition field 62 has a length field 62a and a number field 62b.

  The length field 62a stores a length allowed as a wafer product for a defect area classified into a corresponding defect classification that is a condition used for pass / fail judgment. That is, if the length of the defect determined to be the corresponding defect classification is within the allowable length, the wafer product is acceptable, and if the length exceeds the allowable length, the wafer is Indicates a failure. The number field 62b stores the number (allowable number) allowed as the defect area classified into the corresponding defect classification, which is a condition used for the pass / fail judgment. In other words, if the number of defects determined to be the corresponding defect classification exceeds the allowable number, it indicates that the wafer is rejected as a product. In these fields 62a and 62b, numerical values are set for the conditions used for the pass / fail judgment, and non-set symbols (“-” in the present embodiment) indicating that they are not set are set otherwise. Is done.

  For example, in FIG. 4, as a condition to be classified into the defect B which is the second record from the top, the luminance profile is concave, the luminance ratio is 0.70 to 1.00, and the area S is 30 (pixels). ) Or more, the degree of circularity e is 0.60 to 0.90, and the length-to-short ratio is 1.50 to 2.00, and the number of defect regions classified into this defect B is within three. If this is the case, this indicates that the wafer is acceptable as a product.

  FIG. 5 is a flowchart of defect inspection processing according to an embodiment of the present invention.

First, the control processing unit 6a sets an initial value as a setting condition (image acquisition condition) when an image of the wafer W is acquired (step S1). That is, the initial values I ₀ to irradiation conditions I _n the illumination unit 4, the initial values G ₀ to the light receiving condition G _n in the photodetecting section 2, the exposure time (image capture speed and inspection stage of the light receiving section 2 The initial value SS ₀ is set to the exposure condition SS _n corresponding to the movement speed 3). In the present embodiment, the initial value I ₀ is the smallest light amount value in the light amount range used during image acquisition, and the initial value G ₀ is the smallest gain value in the gain range used during image acquisition. The initial value SS ₀ is a value corresponding to the shortest exposure time in the exposure conditions used at the time of image acquisition (in this embodiment, the fastest moving speed in the moving speed range used at the time of image acquisition, and The fastest image capture speed in the range of image capture speeds used for image acquisition).

  Next, the control processing unit 6a sets the setting conditions at the time of image acquisition of the wafer W to the light receiving unit 2, the inspection stage 3, and the illumination unit 4 (step S2), and operates the wafer W from the light receiving unit 2 to operate. Is acquired (step S3).

Next, the control processing unit 6a determines whether or not the average luminance of the acquired image (for example, the average luminance on the wafer W) is within an allowable luminance range (allowable range: defect detectable range) (step S1). S4). For example, the control processing unit 6a determines whether or not | A _n −A _t | ≦ δA _t is satisfied. Here, A _n is the average luminance of the wafer W in the image, A _t is the center luminance of the permissible range, .delta.A _t is the acceptable amount of deviation from the center luminance tolerance. Incidentally, the allowable range can be expressed as _{A t} ± _{δA t.} As the allowable range, for example, when the luminance is set to a value of 0 to 255, a range of 70 to 170 may be used.

  As a result, if it is determined that the average luminance is within the allowable range (step S4: YES), the control processing unit 6a indicates that the image has appropriate luminance for defect detection. Then, the image data is transferred to the image processing unit 6b to execute the defect detection image analysis process (step S5).

On the other hand, when it is determined that the average luminance is not within the allowable range (step S4: NO), this image indicates that the image does not have appropriate luminance for defect detection. Then, an irradiation condition candidate I _x for obtaining an image with a more appropriate luminance is determined (step S6). In the present embodiment, the control processing unit 6a, the irradiation condition candidate _{I x} is calculated by _{I x = k * A t /} A n * I n. Here, k is a predetermined coefficient.

Then, the control processing unit 6a determines whether the irradiation condition candidate I _x is within a settable range, that is, I _min ≦ I _x ≦ I _max (I _min : minimum settable value of I, I _max : I determines a whether setting maximum possible value) (step S7), and if it is determined that the settable range (step S7: YES), the irradiation conditions I _n the irradiation condition candidate I _x Determine (step S8) and proceed to step S2. Thereby, irradiation conditions (light quantity of the illumination part 4) can be changed so that the average brightness | luminance of the image of the wafer W may approach an allowable range.

On the other hand, if it is determined not to be within the range that can be set: (step S7 NO), the control processing unit 6a determines the light receiving condition candidate G _x for obtaining images of better brightness (step S9). In the present embodiment, the control processing unit 6a calculates the light reception condition candidate G _x by G _x = l * A _t / A _n * G _n . Here, l is a predetermined coefficient.

Then, the control processing unit 6a, it is within the range receiving condition candidate _{G x} is configurable, _{i.e., G min ≦ G x ≦ G} max (G min: settable minimum value of _{G, G max:} the G It is determined whether or not it is within the settable range (step S10: YES), the light reception condition candidate _Gx is set as the light reception condition _Gn . Determine (step S11) and proceed to step S2. Thereby, the light receiving condition (gain of the light receiving unit 2) can be changed so that the average luminance of the image of the wafer W approaches the allowable range.

On the other hand, if it is determined not to be within the range that can be set: (step S10 NO), the control processing unit 6a determines the exposure condition candidate SS _x for obtaining images of better brightness (step S12). In the present embodiment, the control processing unit 6a uses the exposure condition candidate SS _x as an exposure time longer than SS _n (condition that slows the moving speed of the inspection stage 3 and slows the image capture speed of the light receiving unit 2). ).

Then, the control processing unit 6a determines whether or not the exposure condition candidate SS _x is within a settable range (step S13), and if it is determined that it is within the settable range (step S13: YES), The exposure condition candidate SS _x is determined as the exposure condition SS _n (step S14), and the process proceeds to step S2. Thereby, the exposure conditions (the moving speed of the inspection stage 3 and the image capturing speed of the light receiving unit 2) can be changed so that the average luminance of the image of the wafer W approaches the allowable range.

  If it is determined that it is not within the settable range (step S13: NO), it means that the exposure condition cannot be changed, and the condition for obtaining an image with appropriate luminance cannot be set. Therefore, the control processing unit 6a displays an error on a display device (not shown) (step S15).

  By such processing, it is possible to adjust the image acquisition conditions at the time of image acquisition of the wafer W, and it is possible to appropriately acquire an image of the wafer W having a luminance suitable for defect detection.

  FIG. 6 is a diagram for explaining the relationship between the resistivity of the wafer and the average luminance in the image of the wafer with respect to a plurality of image acquisition conditions according to an embodiment of the present invention. 6A is a diagram illustrating a relationship between the resistivity of the wafer W and the average luminance of the wafer W with respect to a plurality of image acquisition conditions, and FIG. 6B illustrates the image acquisition conditions (1) to (6). FIG.

  For example, when only the gain of the light receiving unit 2 is increased as in the case of changing from the condition (1) to the condition (2), as shown in the graph corresponding to the condition (1) and the condition (2) in FIG. 6A. Thus, the average luminance in the image of the lower resistivity wafer W can be included in the defect detectable range. That is, an image of the wafer W having a lower resistivity can be appropriately captured.

  Further, for example, when the gain of the light receiving unit 2 is increased and the light amount of the illumination unit 4 is increased as in the case of changing from the condition (2) to the condition (3), the condition (2) and the condition of FIG. As shown in the graph corresponding to (3), the average luminance in the image of the lower resistivity wafer W can be included in the defect detectable range. That is, an image of the wafer W having a lower resistivity can be appropriately captured.

  Further, for example, as in the case of changing from the condition (2) to the condition (4), the moving speed of the inspection stage 3 is decreased and the image capturing speed of the light receiving unit 2 is also decreased, that is, the exposure time. As shown in the graph corresponding to the condition (2) and the condition (4) in FIG. 6A, the average luminance in the image of the lower resistivity wafer W can be included in the defect detectable range. . That is, an image of the wafer W having a lower resistivity can be appropriately captured.

  Accordingly, as shown in condition (6), when the gain of the light receiving unit 2 is maximized, the light amount of the illumination unit 4 is maximized, and the moving speed of the inspection stage 3 is reduced, the condition (6) of FIG. As described above, the average luminance in the image of the wafer W having a lower resistivity can be included in the defect detectable range.

As described above, by adjusting at least one of the gain of the light receiving unit 2, the light amount of the illumination unit 4, and the moving speed of the inspection stage 3 (and the image capturing speed of the light receiving unit 2), an image of the wafer W to be inspected. The average luminance of the image can be adjusted, and the average luminance of the image can be appropriately set within the defect detectable range.

  FIG. 7 is a flowchart of defect detection image analysis processing according to an embodiment of the present invention.

  In the defect detection image analysis process, the image processing unit 6b performs the smoothing process on each pixel using the image data (original image data) of the wafer W received from the control processing unit 6a (step S21). In this smoothing process, the luminance of the target pixel is set to the average value of the luminances of n × n (for example, 3 × 3) pixels centered on the pixel. In the present embodiment, the smoothing process is executed for all the pixels of the image data, and this is executed a plurality of times. Thereby, the error factor in image data can be reduced.

  Next, the image processing unit 6b performs predetermined differential filter processing on the image data (step S22). Here, as the differential filter processing, for example, a differential filter may be applied in the X direction (direction perpendicular to the moving direction of the inspection stage 3; see FIG. 2), or in the Y direction (moving direction of the inspection stage 3). It may be applied, or Laplacian may be applied.

  The image processing unit 6b calculates the moving average luminance (reference average luminance) in each pixel using the image data after the differential filter processing (step S23). In the present embodiment, as the moving average luminance for each pixel, the luminance of a predetermined number of pixels before and after the X direction (for example, 100 pixels before and after the pixel) is averaged with respect to the pixel. Note that, as the moving average luminance for each pixel, the luminance of a predetermined number of pixels (for example, 100 pixels before and after) in the Y direction with respect to the pixel may be averaged.

  Next, the image processing unit 6b calculates a luminance threshold used for determining whether or not the pixel is a defect candidate pixel based on the moving average luminance of each pixel (step S24). In the present embodiment, for example, a value obtained by multiplying the moving average luminance for each pixel by a predetermined coefficient (for example, 0.3) is used as the luminance threshold value for each pixel. A fixed value may be used as the luminance threshold value.

  Next, the image processing unit 6b calculates a difference value (absolute value of the difference) between the luminance of each pixel of the image data and the moving average luminance of each pixel, and calculates the difference value for each pixel and each pixel. A binarization process for generating binary image data (binarized image data) indicating whether or not the pixel is a defect candidate pixel is performed by comparing the calculated luminance threshold (step S25). In this binarization processing, when the difference value for a pixel exceeds the luminance threshold value, it is converted into data indicating that it is a defect candidate pixel (for example, 0: black), and in other cases, the defect candidate pixel Is converted to data (for example, 1: white).

  Next, the image processing unit 6b performs white expansion processing on the binarized image data obtained in step S25 (step S26). In this expansion processing, the image processing unit 6b, for each pixel, within a range of n × n (n is a predetermined integer) including the pixel, for example, when there are many white pixels, Perform the process. By this expansion processing, for example, a pixel that is considered to be miscellaneous data such as a white pixel but only one black pixel can be changed to a white pixel. The expansion process may be performed a plurality of times.

  Next, the image processing unit 6b performs a contraction process on white pixels (data having a value of “1”) on the image data subjected to the expansion process (step S26). In this contraction process, the image processing unit 6b performs a process of setting each pixel to black when there are few white pixels within an n × n (n is a predetermined integer) range including the pixel. I do. By this shrinking process, the black area that has become narrowed due to the influence of the expansion process performed earlier can be widened, that is, close to the original area. The contraction process may be performed a plurality of times.

  Next, the image processing unit 6b performs a labeling process for associating numbers in order to treat the connected defect candidate pixels (black pixels) in the image data as one unit (defect candidate area) (step S28).

Next, the image processing unit 6b executes shape feature extraction processing for extracting various shape parameters for each defect candidate region associated with the number (step S29). In the present embodiment, the image processing unit 6b includes the area S that is the total number of pixels of the defect candidate region, the peripheral length l that is the length of the boundary line of the defect candidate region, and the circularity e (e of the defect candidate region. = 4πS / l ² ), and the center-of-gravity position G of the defect candidate area, and the length ratio of the short straight line passing through the center-of-gravity position G of the defect candidate area and the long straight line are extracted.

  Next, the image processing unit 6b acquires partial image data including the defect candidate area and its surroundings (for example, an area including a predetermined number of pixels in the vertical and horizontal directions of each pixel) from the original image data (step S30).

Next, luminance feature extraction processing for extracting various luminance parameters for each defect candidate region is executed (step S31). In the present embodiment, the image processing unit 6b uses the partial image data to determine the unevenness of the luminance profile of the defect candidate region depending on whether the luminance profile is positive or negative with respect to the moving average luminance. Then, the ratio of the maximum difference between the luminance of the defect candidate area and the reference average luminance and the reference average luminance is obtained. In addition, the maximum luminance change rate (absolute value of the inclination of the luminance profile) in a predetermined range of each boundary region in the X direction and Y direction of the luminance profile passing through the gravity center position G is obtained, and these four points are obtained. The average luminance change rate | a | _ave is calculated by averaging the luminance change rates of. Note that the unevenness of the luminance profile, the luminance ratio, and the average luminance change rate are also characteristic parameters regarding the defect candidate region.

  Next, the image processing unit 6b uses the various feature parameters (shape parameters, luminance parameters) calculated for each defect candidate region and the defect determination table 6c to determine whether the wafer W is a product or not. Determination is made (step S32). Specifically, the image processing unit 6b extracts the first record from the defect determination table 6c, and determines the type of defect depending on whether the feature parameter of each defect candidate area satisfies the defect classification condition set in the record. Further, it is determined whether the wafer W is acceptable or unacceptable as a product depending on whether or not a record pass / fail condition is satisfied. Then, the image processing unit 6b extracts all the records from the defect determination table 6c and executes the same process as described above. By such processing, the type of defect of the wafer W can be specified, and it can be appropriately determined whether the wafer passes or fails as a product.

  FIG. 8 is a diagram for explaining binarization processing according to an embodiment of the present invention.

  In this embodiment, as shown in step S25, a binarization process is performed by calculating a difference value between the moving average luminance and the image luminance for each pixel and comparing the difference value with a luminance threshold value. Thus, by using the difference value between the moving average luminance and the image luminance, it is possible to reduce the influence of image unevenness and the difference in luminance for each wafer, and to detect a defective portion more appropriately.

  FIG. 9 is a diagram for explaining binarization processing according to an embodiment of the present invention.

  Specifically, FIG. 9A shows an image in which image unevenness has occurred and its luminance profile. FIG. 9B and FIG. 9C show the results when the binarization process is performed in a state where image unevenness occurs. As shown in FIG. 9B, when the threshold value is applied to the image luminance in a state where the image unevenness occurs, the image unevenness region other than the defective portion is subject to binarization, but as shown in FIG. 9C. In addition, by applying a threshold value to the difference value, it is possible to appropriately detect a defective portion without being affected by image unevenness.

  FIG. 10 is a diagram illustrating a binarization process in which the luminance threshold value is changed according to an embodiment of the present invention.

  Specifically, FIG. 10 shows the result of detecting defects by acquiring images with different average luminance for 100 μm defects existing in the plane of the wafer W, and FIG. FIG. 10B shows a defect detection result in a high-luminance image.

  As shown in FIGS. 10A and 10B, the defect existing in the wafer W can be appropriately detected by changing the luminance threshold according to the gray level of the image. In the present embodiment, the luminance threshold is determined by multiplying the moving average luminance by a predetermined coefficient, and the luminance threshold is increased as the moving average luminance is higher. Defects can be detected.

  As mentioned above, although preferred embodiment of this invention was described, this is an illustration for description of this invention, and is not the meaning which limits the scope of the present invention only to this embodiment. The present invention can be implemented in various modes different from the above-described embodiments without departing from the gist thereof.

  Next, first and second modified examples which are modified examples of the present invention will be described.

  FIG. 11 is a diagram for explaining a moving average luminance calculation method according to a modification of the present invention.

  First, in the wafer defect inspection apparatus 1 of the above-described embodiment, the amount of transmitted light is small at the outer peripheral portion of the wafer W due to illumination unevenness, sagging of the wafer outer peripheral portion, and the like. Therefore, as shown in FIG. 11A, a region in the vicinity of the outer peripheral portion of the wafer W is set as a region not to be inspected (mask region).

  For example, in the above embodiment, as shown in FIG. 11 (2), as the moving average luminance of each pixel, the luminance of 100 pixels before and after the pixel in a predetermined direction (for example, the X direction) is averaged. In the pixels in the inspection area close to the mask area of the wafer W, the moving average luminance is lowered due to the influence of the luminance of the pixels in the mask area, and may be erroneously detected as a defect candidate pixel. For example, as shown in FIG. 11 (1), when there is image unevenness in the inspection region close to the mask region, as shown in FIG. 11 (2), the luminance in the image unevenness portion and the moving average of the portion are displayed. In some cases, the difference value with the luminance exceeds a threshold value, and the pixel in the uneven image portion is erroneously detected as a defect candidate pixel.

  On the other hand, in the first modification, assuming that the luminance of the pixels in the mask area is the same as the luminance of the pixels at the boundary between the mask area and the inspection area, the moving average luminance of each pixel is I am trying to calculate. Thus, even when there is an image unevenness as shown in FIG. 11 (1), as shown in FIG. 11 (3), the luminance in the image unevenness portion and the moving average luminance of the portion are calculated. The difference value does not exceed the threshold value, and the image unevenness portion is not erroneously detected as a defect candidate pixel.

  Further, in the second modification, it is assumed that the luminance of each pixel in the mask area is the same as the luminance of each pixel in a symmetric position with respect to the boundary portion between the mask area and the inspection area. The moving average luminance is calculated. In this way, even when there is image unevenness as shown in FIG. 11 (1), as shown in FIG. 11 (4), the difference between the luminance in the image unevenness portion and the moving average luminance of the portion. The value does not exceed the threshold value, and the image unevenness portion is not erroneously detected as a defect candidate pixel. Therefore, it is possible to reduce erroneous detection of defects.

  Further, the present invention can also be performed as follows. For example, in the above-described embodiment, the entire image of the wafer W is acquired by moving the inspection stage 3, but for example, without moving the inspection stage 3, the light receiving unit 2, the illumination unit 4, and The entire image of the wafer W may be acquired by moving the light guide 5. In short, the inspection stage 3, the light receiving unit 2, the illumination unit 4, and the light guide 5 are relatively moved. In this way, an entire image of the wafer W may be acquired.

  In the above embodiment, the average brightness of the image of the wafer W is used as the reference brightness of the image of the wafer. However, the present invention is not limited to this. For example, the darkest brightness of the image of the wafer W is used. Alternatively, the average luminance in the inspection area of the wafer W may be used.

In the above embodiment, when the irradiation condition of the illumination unit 4 is changed and the irradiation condition cannot be changed, the light reception condition of the light receiving unit 2 is changed, and when the light reception condition cannot be changed, the exposure condition is changed. However, the present invention is not limited to this, and the order of changing the irradiation condition, the light receiving condition, and the exposure condition may be a different order, or a plurality of conditions of the irradiation condition, the light receiving condition, and the exposure condition may be set once. In addition, for example, a plurality of sets of irradiation conditions, light receiving conditions, and exposure conditions may be prepared, and a change target to be used may be selected from them.

  In the above embodiment, the moving average luminance is calculated using the image data obtained by performing the smoothing process and the differential filter process on the original image data. However, the smoothing process and the differential filter process are performed. Instead, the moving average luminance may be calculated using the original image data.

DESCRIPTION OF SYMBOLS 1 Wafer defect inspection apparatus, 2 light-receiving part, 3 inspection stage, 4 illumination part, 5 light guide, 6 processing apparatus, 6a control processing part, 6b image processing part, 6c defect determination table, W wafer.

Claims (7)

A wafer placing means for placing a wafer to be inspected; an irradiating means for irradiating the wafer with infrared light; an imaging means for taking an image of the wafer irradiated with the infrared light; and the imaging means. A wafer defect inspection apparatus that inspects defects of the wafer based on an image of the imaged wafer,
For each pixel in the inspection target area of the wafer in the image, the luminance obtained by averaging the luminance of a plurality of pixels within a predetermined range including the pixel among a plurality of pixels arranged in a predetermined linear direction, A reference average luminance calculating means for calculating as a reference average luminance in the pixel;
Difference value calculating means for calculating a difference value between the reference average luminance in each pixel and the luminance of each pixel;
Determining means for determining whether each pixel is a defect candidate pixel by comparing the difference value for each pixel with a predetermined threshold;
Inspection means for inspecting defects in the wafer based on the defect candidate pixels ;
Threshold determination means for determining the predetermined threshold for each pixel based on the reference average luminance in each pixel;
Wafer defect inspection apparatus. 2. The wafer defect inspection apparatus according to claim 1 , wherein the threshold value determination unit determines a value obtained by multiplying the reference average luminance by a predetermined value as the predetermined threshold value. When the pixels within the predetermined range in the predetermined linear direction correspond to the pixels in the non-inspection area near the outer periphery of the wafer, the reference average luminance calculation unit calculates the pixels in the non-inspection area. brightness, assuming the luminance of the boundary pixels of said inspection object areas, wafer defect inspection device according to claim 1 or claim 2 calculates the reference average brightness. When the pixels within the predetermined range in the predetermined linear direction correspond to the pixels in the non-inspection area near the outer periphery of the wafer, the reference average luminance calculation unit calculates the pixels in the non-inspection area. brightness, assuming the luminance of the pixels in symmetrical positions with respect to a boundary between the inspected area on a straight line in the predetermined linear direction, according to claim 1 or claim calculates the reference average brightness 2. The wafer defect inspection apparatus according to 2. The inspection means includes
Defect candidate area specifying means for specifying a defect candidate area based on the defect candidate pixels;
The unevenness of the brightness profile in the defect candidate area, the brightness ratio that is the ratio of the maximum difference between the brightness in the defect candidate area and the reference average brightness and the reference average brightness, the average brightness change rate in the defect candidate area, the defect candidate area Whether the defect candidate area falls under a predetermined defect type based on at least one of the area of the defect candidate area, the circularity of the defect candidate area, or the ratio of the long width to the short width based on the center of gravity of the defect candidate area wafer defect inspection apparatus according to any one of claims 1 to 4 and a defect type determination means for determining whether. The inspection means includes
Based on the number of defect candidate area corresponding to the predetermined defect type, said wafer according to any one of claims 1 to 5 further comprising a acceptance determination means for determining whether passed as a product Wafer defect inspection equipment. A wafer defect inspection method for inspecting a defect of the wafer based on an image of a wafer to be inspected,
For each pixel in the range of the wafer to be inspected in the image, the luminance obtained by averaging the luminance of a plurality of pixels in a predetermined range including the pixel in a plurality of pixels arranged in a predetermined linear direction, Calculating as a reference average luminance in the pixel;
Calculating a difference value between the reference average luminance in each pixel and the luminance of each pixel;
Determining whether each pixel is a defective candidate pixel by comparing the difference value for each pixel with a predetermined threshold;
Inspecting the wafer for defects based on the defect candidate pixels ;
Determining the predetermined threshold for each pixel based on the reference average luminance at each pixel;
A wafer defect inspection method.