Source: http://www.google.com/patents/US7440605?dq=6,202,008
Timestamp: 2014-12-19 18:29:06
Document Index: 214324839

Matched Legal Cases: ['art 2', 'art 31', 'art 2', 'art 2', 'art 21', 'art 2', 'art 31', 'art 58', 'art 56', 'art 31', 'art 2', 'art 2', 'art 501', 'art 501', 'art 501', 'art 56', 'art 504', 'art 504', 'art 504', 'art 504', 'art 504', 'art 505', 'art 502', 'art 502', 'art 504', 'art 503', 'art 502', 'art 502', 'art 504', 'art 504', 'art 504', 'art 507', 'art 504', 'art 504', 'art 503', 'art 503', 'art 503', 'art 507', 'art 504', 'art 507', 'art 507', 'art 505', 'art 503']

Patent US7440605 - Defect inspection apparatus, defect inspection method and program - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign inAdvanced Patent SearchPatentsA reference image and an inspection image indicating pattern on a substrate are acquired and a specified pixel value range (63) is set on the basis of a histogram (62 a) of pixel values of the reference image. Then, a transfer curve (71) having a large inclination in the specified pixel value range (63)...http://www.google.com/patents/US7440605?utm_source=gb-gplus-sharePatent US7440605 - Defect inspection apparatus, defect inspection method and programAdvanced Patent SearchPublication numberUS7440605 B2Publication typeGrantApplication numberUS 10/657,107Publication dateOct 21, 2008Filing dateSep 9, 2003Priority dateOct 8, 2002Fee statusLapsedAlso published asUS20040066962Publication number10657107, 657107, US 7440605 B2, US 7440605B2, US-B2-7440605, US7440605 B2, US7440605B2InventorsYasushi Sasa, Hiroyuki OnishiOriginal AssigneeDainippon Screen Mfg. Co., Ltd.Export CitationBiBTeX, EndNote, RefManPatent Citations (14), Non-Patent Citations (5), Referenced by (3), Classifications (18), Legal Events (4) External Links: USPTO, USPTO Assignment, EspacenetDefect inspection apparatus, defect inspection method and programUS 7440605 B2Abstract A reference image and an inspection image indicating pattern on a substrate are acquired and a specified pixel value range (63) is set on the basis of a histogram (62 a) of pixel values of the reference image. Then, a transfer curve (71) having a large inclination in the specified pixel value range (63) is obtained. The inspection image and the reference image are converted in accordance with an LUT having transfer characteristics indicated by the transfer curve (71), an enhanced differential image between a converted inspection image and a converted reference image is generated and each pixel value of the enhanced differential image is compared with a predetermined threshold value, to thereby perform a detection of defective pixel. With this, a value of pixel in the enhanced differential image which corresponds to a pixel in the reference image (or inspection image) having the pixel value in the specified pixel value range (63) is enhanced, and appropriate inspection is thereby performed.
1. A defect inspection apparatus for inspecting a pattern on an object, comprising:
an operation part for performing the steps of:
setting a specified pixel value range which is positioned between representative pixel values of two regions in said inspection images and/or said reference image, said two regions corresponding to two kinds of regions on said object;
obtaining transfer characteristics to enhance a difference between arbitrary pixel values included in said specified pixel value range relative to a difference between arbitrary pixel values other than said specified pixel value range;
obtaining an enhanced differential image between said inspection image and said reference image on the basis of said transfer characteristics; and
performing an inspection on the basis of said enhanced differential image.
said representative pixel values are average values of values of pixels belonging to said two regions, respectively.
4. A defect inspection apparatus for inspecting a pattern on an object comprising:
an image pickup device for performing an image pickup of an object to acquire data of an inspection image which is multitone
setting a specified pixel value range which is positioned outside a pixel value range corresponding to a specific region in said inspection image and/or said reference image, said specific region corresponding to a specific kind of region on said object;
obtaining an enhanced differential image between said inspection image and said reference image on the basis of said transfer characteristics and
6. The defect inspection apparatus according to claim 1, wherein
7. The defect inspection apparatus according to claim 1, wherein
9. A defect inspection method for inspecting pattern on an object, comprising the steps of:
c) setting a specified pixel value range which is positioned between representative pixel values of two regions in said inspection image and/or said reference image, said two regions corresponding to two kinds of regions on said object;
d) obtaining transfer characteristics to enhance difference between arbitrary pixel values included in said specified pixel value range relatively to difference between arbitrary pixel values other than said specified pixel value range;
e) obtaining an enhanced differential image between said inspection image and said reference image on the basis of said transfer characteristics; and
f) performing inspection on the basis of said enhanced differential image.
10. The defect inspection method according to claim 9, wherein
said inspection image and said reference image are converted on the basis of said transfer characteristics to obtain a differential image between a converted inspection image and a converted reference image as said enhanced differential image in said step e).
11. The defect inspection method according to claim 9, wherein
12. A defect inspection method for inspecting a pattern on an object, comprising the steps of:
a) preparing data of a reference image
c) setting a specified pixel value range which is positioned outside a pixel value range corresponding to a specific region in said inspection image and/or said reference image, said specific region corresponding to a specific kind of region on said object;
d) obtaining transfer characteristics to enhance a difference between arbitrary pixel values included in said specified pixel value range relative to a difference between arbitrary pixel values other than said specified pixel value range;
13. The defect inspection method according to claim 12, wherein
14. The defect inspection method according to claim 9, wherein
15. The defect inspection method according to claim 9, wherein
said step f) comprises the steps of:
16. A computer-readable recording medium carrying a program for executing inspection of pattern, wherein execution of said program by a computer causes said computer to perform the steps of:
17. The defect inspection apparatus according to claim 1, wherein
said transfer characteristics are obtained in the form of two-dimensional lookup table, and said enhanced differential image is obtained by using said two-dimensional lookup table.
18. The defect inspection apparatus according to claim 4 wherein
said transfer characteristics include inspection image transfer characteristics from said inspection image and reference image transfer characteristics obtained from said reference image.
19. The defect inspection apparatus according to claim 4 wherein
20. The defect inspection apparatus according to claim 4 wherein
21. The defect inspection apparatus according to claim 4 wherein
said transfer characteristics are obtained in the form of a two-dimensional lookup table, and said enhanced differential image is obtained by using said two-dimensional lookup table.
22. The defect inspection method according to claim 9 wherein
said transfer characteristics are obtained in the form of a two-dimensional lookup table and said enhanced differential image is obtained by using said two-dimensional lookup table.
23. The defect inspection method according to claim 12 wherein
24. The defect inspection method according to claim 12 wherein
synthesizing a differential image between said inspection image and said reference image and said reference image and enhanced differential image; and
25. The defect inspection method according to claim, 12 wherein
said transfer characteristics are obtained in the form of a two-dimensional lookup table and said enhanced differential image is obtained by using said two-dimensional lookup table. Description
In a case where, for example, dynamic ranges of the inspection image and the reference image are matched with each other in a region consisting of about 100�100 pixels, an effect of variation in pixel value produced entirely on this region can be removed but the variation in pixel value caused by the charge-up phenomenon and the like in the region consisting of several pixels is still incorrectly detected as a defect.
FIG. 1 is a view showing incorrect detection of a defect due to the charge-up phenomenon. In FIG. 1, assuming that ideal values of pixel in a line 911 of an inspection image 91 (e.g., values of an reference image) are shown in graph 921 and actual pixel values are shown in graph 922, pixel values of the differential absolute value image are shown in graph 923.
SUMMARY OF THE INVENTION It is an object of the present invention to provide a technique for more appropriately detecting a defect on an object.
BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a view showing incorrect detection of a defect;
FIG. 2 is a diagram showing a construction of an inspection apparatus;
FIG. 3 is a block diagram showing a structure of a computer;
FIG. 4 is a diagram showing a functional structure of the computer;
FIG. 5 is a flowchart showing an operation flow of the inspection apparatus;
FIG. 9 is a diagram showing another exemplary functional structure of the computer;
FIG. 10 is a flowchart showing another operation flow of the inspection apparatus;
FIGS. 11 and 12 are graphs illustrating histograms and transfer curves;
FIG. 13 is a view illustrating a reference image;
FIG. 14 is a graph illustrating a histogram and a transfer curve;
FIG. 15 is a diagram showing another exemplary functional structure of the computer;
FIG. 16 is a flowchart showing an operation flow of the inspection apparatus;
FIG. 17A is a graph illustrating a transfer curve;
FIG. 17B is a view showing a 2-D (two-dimensional) LUT;
FIG. 18A is a graph illustrating a transfer curve without conversion (i.e., straight line);
FIG. 18B is a view showing a 2-D LUT without enhancement of differential image;
FIG. 19 is a diagram showing another exemplary functional structure of the computer;
FIG. 20A is a graph illustrating transfer curves;
FIG. 20B is a view showing a 2-D LUT;
FIG. 21 is a diagram showing another exemplary functional structure of the computer;
FIG. 22 is a flowchart showing part of an operation flow of the inspection apparatus;
FIG. 23 is a diagram showing another exemplary functional structure of the computer;
FIG. 24 is a view showing a 2-D LUT;
FIGS. 25A to 25D are graphs showing characteristics of the 2-D LUT;
FIG. 26 is a flowchart showing an operation flow of the inspection apparatus; and
FIG. 27 is a view illustrating partial images.
DESCRIPTION OF THE PREFERRED EMBODIMENTS FIG. 2 is a view showing a construction of an inspection apparatus 1 in accordance with the preferred embodiment of the present invention. The inspection apparatus 1 is an apparatus for inspecting pattern on a semiconductor substrate (hereinafter, referred to as �substrate�) 9 and comprises an image pickup part 2 for performing an image pickup of a predetermined region on the substrate 9 to acquire data of a multitone object image, a stage 3 for holding the substrate 9 and a stage driving part 31 for moving the stage 3 relatively to the image pickup part 2.
The image pickup part 2 comprises a lighting part 21 for emitting an illumination light, an optical system 22 for guiding the illumination light to the substrate 9 and receiving the light from the substrate 9 and an image pickup device 23 for converting an image of the substrate 9 formed by the optical system 22 into an electrical signal. This image pickup part 2 may be an image pick-up device using an electron beam. The stage driving part 31 has an X-direction moving mechanism 32 for moving the stage 3 in the X direction of FIG. 2 and a Y-direction moving mechanism 33 for moving the stage 3 in the Y direction. The X-direction moving mechanism 32 has a construction in which a ball screw (not shown) is connected to a motor 321 and moving the Y-direction moving mechanism 33 in the X direction of FIG. 2 along guide rails 322 with rotation of the motor 321. The Y-direction moving mechanism 33 has the same construction as the X-direction moving mechanism 32 and moves the stage 3 in the Y direction along guide rails 332 by its ball screw (not shown) with rotation of its motor 331.
FIG. 3 is a block diagram showing a structure of the computer 5. The computer 5 has a constitution of general computer system where a CPU 51 for performing various computations, a ROM 52 for storing a basic program and a RAM 53 for storing various information are connected to a bus line. To the bus line, a fixed disk 54 for storing information, a display 55 for displaying various information such as images, a keyboard 56 a and a mouse 56 b for receiving an input from a user, a reader 57 for reading information from a computer-readable recording medium 8 such as an optical disk, a magnetic disk or a magneto-optic disk, and a communication part 58 for transmitting and receiving a signal to/from other constituent elements in the inspection apparatus 1 are further connected through an interface (I/F) as appropriate.
FIG. 4 is a diagram showing a functional structure of the computer 5. In FIG. 4, an input part 56 corresponds to the keyboard 56 a or the mouse 56 b of FIG. 3 and an image memory 531 and a memory 532 correspond to the RAM 53 of FIG. 3. The image memory 531 may be a dedicated memory which is additionally provided in the computer 5.
FIG. 5 is a flowchart showing an operation flow of the inspection apparatus 1. In the inspection apparatus 1, first, the computer 5 controls the stage driving part 31 to relatively move an image pickup position corresponding to the image pickup part 2 to a predetermined position over the substrate 9 and the image pickup part 2 acquires data of object image of multitone (e.g., 256 tones if 8 bits). The image pickup (i.e., prescan) is performed for a region which is supposed to have no defect and the acquired data is stored in the image memory 531 and prepared as reference image data 601 (Step S1).
Next, the range setting part 501 sets a range of values of specified pixels in defect detection (hereinafter, referred to as a �specified pixel value range�) (Step S12). The technical meaning of the specified pixel value range will be discussed later. It is selected in advance whether the setting of specified pixel value range is performed manually by a user or automatically.
When the setting of specified pixel value range is performed manually, first, the range setting part 501 acquires the reference image data 601, generates a histogram of pixel values of reference image and displays the histogram on the display 55. FIG. 6 is a graph illustrating a histogram 62 a. When a histogram has two maximum values (this is hereinafter referred to as �bi-modality�), like the histogram 62 a, a range near the center minimum value is set by the user as a specified pixel value range 63. The setting is performed by the range setting part 501 when the input part 56 receives the operation of the user. When the reference image has two kinds of regions (for example, a wiring pattern region and the other background region on the substrate 9), a range between respective ranges of pixel values which are supposed to be obtained from these regions is set as the specified pixel value range 63. In the manual setting, the specified pixel value range 63 is set in accordance with the intention of the user.
When the setting of specified pixel value range is performed automatically, for example, an average value around each of the peaks and a standard deviation σ of distribution around each of the peaks are obtained for the histogram 62 a having bi-modality as shown in FIG. 6 and a range between ranges 641 and 642 each of which covers (�σ) of the corresponding peak centered at the average value of the peak is set as the specified pixel value range 63. The ranges 641 and 642 correspond to ranges of pixel values obtained from both the regions when the reference image has two kinds of regions. By using the standard deviation, it is possible to appropriately set the pixel value ranges corresponding to these regions.
As a method of setting a threshold value TH1, a method of setting a threshold value in binarization of a multivalued image or other various methods may be adopted. For example, a method disclosed in �An Automatic Threshold Selection Method Based on Discriminant and Least Squares Criteria� by Nobuyuki Otsu (IEICE (The Institute of Electronics, Information and Communication Engineers) Transactions, '80/4 vol. J63-D, No. 4, pp. 349-356) may be used. In this method, as a value for evaluation on propriety of a threshold value, measures of class separability based on within-class variance and between-class variance (herein, �class� refers to a group of pixel values which are divided by the threshold value) are adopted, and a threshold value is obtained so that the measures of class separability can be the maximum. By this method, even if a histogram of pixel values has no bi-modality when an image is divided into two regions, it is possible to steadily obtain an optimum threshold value in a non-parametric manner.
At the same time when the pixel value of the converted inspection image is inputted to the subtraction part 504, the pixel value corresponding to the converted reference image is inputted from the image memory 531 and the subtraction part 504 obtains a differential absolute value between these pixel values. With this operation, the subtraction part 504 substantially obtains the differential absolute value image between the converted inspection image and the converted reference image (hereinafter, referred to as an �enhanced differential image�) (Step S17).
FIG. 8 is a graph illustrating another exemplary specified pixel value range. FIG. 8 shows a state where a range of pixel values which is larger than the pixel value range in which there are frequencies to some degrees is set as the specified pixel value range 63. When the reference image has two kinds of regions (for example, a wiring pattern region and the other background region on the substrate 9), a range of pixel values which is larger than each of the pixel value ranges 641 and 642 obtained from these regions is set as the specified pixel value range 63. Also in this case, the specified pixel value range 63 may be set manually by the user or automatically on the basis of the average values or the standard deviations of the peaks.
FIG. 9 is a diagram showing another exemplary functions performed by an operation of the computer 5 in accordance with the program 80. The functional structure lower than the subtraction part 504 is the same as that of FIG. 4 and the functions identical to those of FIG. 4 are represented by the same reference signs. FIG. 10 is a flowchart showing the operation flow of the computer 5 shown in FIG. 9.
FIG. 11 is a graph illustrating another example for setting the specified pixel value range and the transfer characteristics (LUT) on the basis of the histogram in the inspection apparatus 1. The histogram 62 a of FIG. 11 has two peaks like that of FIG. 6 and the pixel value ranges 641 and 642 in two regions on the substrate 9, which correspond to these peaks, are obtained. Then, pixel value ranges other than the pixel value ranges 641 and 642 are set as specified pixel value ranges 63 a, 63 b and 63 c. Therefore, a transfer curve 73 which corresponds to the LUT has inclination which becomes larger in three specified pixel value ranges 63 a, 63 b and 63 c and becomes smaller in the two pixel value ranges 641 and 642. As a result, a value of a pixel in the enhanced differential image which corresponds to the pixel belonging to one of the three specified pixel value ranges in the reference image and (or) the inspection image is enhanced. In other words, all the pixels each of which is uncertain on whether it belongs to a specific region on the substrate 9 or not are enhanced in the enhanced differential image.
FIG. 12 is a graph illustrating the transfer curve 74 in a case where there are three (kinds of) regions on the substrate 9 and a histogram 62 c having three peaks is obtained. For example, as shown in FIG. 13, when a reference image (or inspection image) 700 has a background region 701, a first wiring region 702 and a second wiring region 703 and pixel values on a line 700 a are shown as a graph 700 b, the histogram 62 c illustrated in FIG. 12 is obtained.
FIG. 14 is a graph illustrating setting of a specified pixel value range in a case where it is known in advance that there are three regions on the substrate 9 and a histogram 62 d does not have peaks corresponding to these three regions.
FIG. 15 is a diagram showing still another exemplary functions performed by an operation of the computer 5 in accordance with the program 80. In FIG. 15, the subtraction part 504 is omitted from the structure of FIG. 4 and with the functional structure of FIG. 15, the enhanced differential image is generated without generating the converted reference image data 602. The functional structure lower than the comparison part 505 is the same as that of FIG. 4, and the functions identical to those of FIG. 4 are represented by the same reference signs. FIG. 16 is a flowchart showing the operation flow of the computer 5 of FIG. 15.
FIGS. 17A and 17B are views showing characteristics of an example of the 2-D LUT 61 c generated by the LUT generation part 502, FIG. 17A shows a transfer curve (transfer characteristics) 711 in a case where it is supposed that the converted reference image (and the converted inspection image) should be generated, like in FIG. 4, and FIG. 17B schematically shows a state of the 2-D LUT 61 c for generating the enhanced differential image in accordance with the transfer curve 711 of FIG. 17A. In FIG. 17B, the lower left is the origin (0, 0), and the horizontal axis indicates the pixel values of the inspection image and the vertical axis indicates the pixel values of the reference image. Then, a value of the table in a coordinate determined by these pixel values is specified as a pixel value of the enhanced differential image. The broken lines of FIG. 17B indicate magnitude of values included in the 2-D LUT 61 c as contour lines.
FIGS. 18A and 18B are views showing characteristics of a 2-D LUT illustrated for reference. FIG. 18A shows a transfer curve 712 without transfer of pixel values (i.e., straight line), and FIG. 18B schematically shows the 2-D LUT corresponding to the transfer curve 712 of FIG. 18A. In the 2-D LUT of FIG. 18B, values in the 2-D LUT are in proportion to the distance from a diagonal line 81 so that the difference between the pixel value of the inspection image and the pixel value of the reference image should be an output value.
On the other hand, in the 2-D LUT 61 c of FIG. 17B, a value �0� is stored on the diagonal line 81 but values in coordinates are set so that the contour lines protrude towards the center. As a result, when both the pixel value of the inspection image and the pixel value of the reference image belong to a pixel value range of the FIG. 17A which has a sharp inclination (i.e., in the neighborhood of the center of FIG. 17B), a relatively larger value than the difference between the pixel value of the inspection image and the pixel value of the reference image is specified in accordance with the 2-D LUT 61 c. In contrast to this, when both the pixel value of the inspection image and the pixel value of the reference image belong to a pixel value range of the FIG. 17A which has a gentle inclination (i.e., on a side of the origin or the opposite side of the origin in FIG. 17A), a relatively smaller value than the difference between the pixel value of the inspection image and the pixel value of the reference image is specified in accordance with the 2-D LUT 61 c. Thus, the 2-D LUT 61 c generated by the LUT generation part 502 is a table for obtaining the pixel value of the enhanced differential image directly and efficiently from the pixel value of the inspection image and the pixel value of the reference image without conversion of the reference image and the inspection image in accordance with the transfer characteristics. It is thereby possible to perform inspection in the inspection apparatus 1 at a high speed.
FIG. 19 is a diagram showing another exemplary functional structure of the computer 5 in a case where the same operation as that for generating the enhanced differential image by using the reference image LUT 61 a and the inspection image LUT 61 b of FIG. 9 is performed by using the 2-D LUT. The functional structure of FIG. 19 is different from that of FIG. 9 in only that the subtraction part 504 is omitted and a 2-D LUT 61 d is provided in the image conversion part 503.
FIGS. 20A and 20B are views showing characteristics of an example of the 2-D LUT 61 d. In FIG. 20A, a transfer curve 713 shows transfer characteristics derived from the reference image and a transfer curve 714 shows transfer characteristics derived from the inspection image. Correspondingly to these transfer characteristics, the 2-D LUT 61 d of FIG. 20B are generated by the LUT generation part 502. The LUT generation part 502 may directly generate the 2-D LUT 61 d from the specified pixel value ranges set for the reference image and the inspection image without obtaining the transfer curves of FIG. 20A.
In the 2-D LUT 61 d of FIG. 20B, a value �0� is set approximately on a curve 81 a and the contour lines are distorted as compared with those of the 2-D LUT 61 c of FIG. 17B. This makes it possible to generate the enhanced differential image while reducing an effect due to difference in quality of these images even if the reference image and the inspection image have different quality of image (e.g., brightness or distribution range of pixel values), and therefore the same inspection as that by the structure of FIG. 9 can be performed at a high speed (see Steps S35 to 37).
Though appropriate inspection in accordance with the nature of defect is performed by obtaining the enhanced differential image in the preferred embodiment discussed above, the enhanced differential image may be processed by using the differential absolute value image (hereinafter, referred to as a �simple differential image�) between the original reference image and the original inspection image. FIG. 21 is a diagram showing part of functional structure of the computer 5 in a case where the enhanced differential image and the simple differential image are synthesized in the structure of FIG. 4 or 9. In FIG. 21, the subtraction part 504 of the structure of FIG. 4 or 9 is replaced by a first subtraction part 504 a, a second subtraction part 504 b and a synthesizing part 507. Other constituent elements are identical to those of FIG. 4 or 9, and the elements are represented by the same reference signs in the following description.
Though FIG. 21 shows that the reference image data 601, the converted reference image data 602, the inspection image data 611 and the converted inspection image data 612 are stored in the image memory 531, there may be a case where the data other than the reference image data 601 are not stored in the image memory 531 but are inputted directly to the first subtraction part 504 a and the second subtraction part 504 b. When inspection is performed by the structure of FIG. 21, an operation of FIG. 22 is performed instead of Step S18 of FIG. 5. Also in the structure of FIG. 21, the LUT 61 of FIG. 4, the reference image LUT 61 a and the inspection image LUT 61 b of FIG. 9 are generated, the reference image data 601 and the inspection image data 611 are converted by the image conversion part 503 and the converted reference image data 602 and the converted inspection image data 612 are obtained (Steps S11 to S16 of FIG. 5, or Steps S21 to S27 of FIG. 10).
FIG. 23 is a diagram showing a structure for synthesizing the enhanced differential image and the simple differential image in a case of using the 2-D LUT (see FIG. 15 or 19). In the structure of FIG. 23, a 2-D LUT is provided in the image conversion part 503, and an enhanced differential image is directly generated by the image conversion part 503 from the reference image data 601 and the inspection image data 611 and inputted to the synthesizing part 507. On the other hand, subtraction of the reference image data 601 and the inspection image data 611 is performed by the subtraction part 504 to generate data of a simple differential image and the data of simple differential image is inputted to the synthesizing part 507. Then, the enhanced differential image and the simple differential image are synthesized by the synthesizing part 507 and each pixel value of the synthesized differential image is compared with a predetermined threshold value by the comparison part 505, to perform an inspection. In other words, the same operation as that in the structure of FIG. 21 is performed, except that the data of enhanced differential image is directly generated by the image conversion part 503.
As shown in FIGS., 25A to 25D, in an image converted in accordance with the 2-D LUT of FIG. 24, the degree of enhancement of the enhanced differential image is relieved with the simple differential image. By directly generating the synthesized differential image with the 2-D LUT, it is possible to simplify the computation of the computer 5 in the inspection apparatus 1.
It is not necessary to perform the inspection on each pixel, and for example, a set of pixels (e.g., 2�2 pixels) may be handled as one pixel in the above preferred embodiment. In other words, the pixel in the above preferred embodiment is not needed to strictly correspond to a physical pixel which is a constituent of an image.
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