US20100021041A1 - Pattern defect inspection method and apparatus - Google Patents

Pattern defect inspection method and apparatus Download PDF

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US20100021041A1
US20100021041A1 US12/573,482 US57348209A US2010021041A1 US 20100021041 A1 US20100021041 A1 US 20100021041A1 US 57348209 A US57348209 A US 57348209A US 2010021041 A1 US2010021041 A1 US 2010021041A1
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image
chip
detection
reference image
pattern
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Shigeru Matsui
Katsuya Suzuki
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Hitachi High Tech Corp
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Hitachi High Technologies Corp
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/0002Inspection of images, e.g. flaw detection
    • G06T7/0004Industrial image inspection
    • G06T7/001Industrial image inspection using an image reference approach
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84Systems specially adapted for particular applications
    • G01N21/88Investigating the presence of flaws or contamination
    • G01N21/95Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
    • G01N21/956Inspecting patterns on the surface of objects
    • G01N21/95607Inspecting patterns on the surface of objects using a comparative method
    • GPHYSICS
    • G03PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
    • G03FPHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR
    • G03F7/00Photomechanical, e.g. photolithographic, production of textured or patterned surfaces, e.g. printing surfaces; Materials therefor, e.g. comprising photoresists; Apparatus specially adapted therefor
    • G03F7/70Microphotolithographic exposure; Apparatus therefor
    • G03F7/70483Information management; Active and passive control; Testing; Wafer monitoring, e.g. pattern monitoring
    • G03F7/70605Workpiece metrology
    • G03F7/70616Monitoring the printed patterns
    • G03F7/7065Defects, e.g. optical inspection of patterned layer for defects
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30108Industrial image inspection
    • G06T2207/30148Semiconductor; IC; Wafer

Definitions

  • the present invention relates to a method and apparatus for performing defect inspection while detecting the images of a plurality of patterns as formed on or above an object to be tested, such as a semiconductor wafer, photo-mask, printed circuit board or equivalents thereto.
  • FIG. 4 is a diagram showing an arrangement of such image sensor 8
  • FIG. 5 is a plan view of an inspection area of the object being tested, for indicating the area that is image-detectable by a single time of scanning. Scan the object under test in a direction at right angles to the layout direction of picture elements or “pixels” 81 of the image sensor 8 , thereby acquiring a two-dimensional (2D) image. The length of the direction along which the pixels 81 are queued is called the “height” of the image sensor 8 .
  • the length of a single chip in the same direction as the height of image sensor 8 is called the chip height.
  • the chip height is larger than the height of image sensor 8 , so it is merely possible to detect only an image of part of the chip through one-time scanning of the image sensor 8 .
  • the significance of this chip's partial image is determinable depending upon the height of the image sensor 8 that performs detection and the imaging magnification of an image focussing optical system for projecting the chip image onto this image sensor 8 .
  • This height is called the effective image pickup height of the image sensor 8 .
  • the effective image pickup height is less than the chip height. Accordingly, in order to inspect an overall chip surface, a method is employed for scanning it while offsetting in the height direction for multiple times.
  • FIG. 6 is a plan view diagram showing a sensor scan locus 101 in case a plurality of chips 21 that are formed on a wafer are scanned by an image sensor for several times.
  • the image sensor is fixed while using a stage to move the wafer under test. Firstly, let the test object move in the X direction; then, acquire an image. Information per pixel of one chip 21 is stored in a memory in the order of scanning. After having completed the image detection in a one-time scan cycle, let the test object move in the Y direction by a distance corresponding to the effective image pickup height of the image sensor. The stage is driven to shift in position as indicated by broken line in FIG. 6 so that the scan direction becomes reversed. This will be repeated to thereby achieve sequential image detection.
  • FIG. 7 is a plan view showing the scanning locus of an image sensor in a similar way to FIG. 6 .
  • the effective image pickup height of the image sensor is one-third (1 ⁇ 3) of the chip height.
  • scanning is done while dividing the test area into three strip-like regions.
  • the scanning of the first row in the X direction is the same as that shown in FIG. 6
  • the second row is scanned while causing an object under test to move by a distance corresponding to the height of one chip in the Y direction.
  • the pixel information of the area “c” for use as a reference image is read out in an order reverse to the order at the time of data storage, whereby the comparison inspection is executable while letting the area b and area c be the same pattern image.
  • the image of another area of the same pattern may be prestored as the reference image of the area a upon startup of the inspection. Whereby, it is possible to perform the inspection of the area a also.
  • any one of the pattern defect inspection apparatus for performing inspection based on the scan locus shown in FIG. 6 and the pattern defect inspection apparatus for performing inspection relying upon the scan locus shown in FIG. 7 comparative inspection of the detection image of a chip is performed by comparing it to the reference image of its immediately preceding chip with the same pattern. Using the image of such immediately preceding chip in this way raises problems which follow.
  • An object under test for use as the object being subjected to pattern defect inspection is such that a pattern is typically formed of a material that is transparent with respect to the wavelength of visible light, such as a photo-resist or a dielectric film made of SiO 2 or the like.
  • a thin film is transparent relative to the wavelength of light being used in the defect inspection apparatus, it exhibits certain reflectivity which is determinable by such the light wavelength and the refractivity of a material making up the pattern plus a film thickness. This makes it possible for the defect inspection apparatus to detect its presence as a light-and-shade image.
  • the thickness of the thin film pattern is not perfectly flat on an entire wafer surface but slightly different depending on locations; however, a certain degree of film thickness error is made acceptable because such error does not affect the manufacture of semiconductor chips.
  • a difference in film thickness occurring depending on locations can create a likewise difference in reflectivity of the pattern, resulting in occurrence of an appreciable difference in brightness or luminance of an image to be detected. This phenomenon is called the color shading irregularity. For example, suppose that a neighboring chip “n” and its immediately preceding chip n ⁇ 1 of FIG.
  • the same shaped patterns “p” included therein are different in film thickness from each other, resulting in occurrence of color shading.
  • the comparison inspection is carried out while letting the chip n be a detection image and also regarding the chip n ⁇ 1 as a reference image, then the pattern p must be erroneously detected as a defect. This occurs because the resultant image is different in light-and-shape property even though the pattern p is the same in shape between these two images and no defects are present therein.
  • Such the false defect information raises difficulties in distinction from a true defect and thus is a serious problem relating to the reliability of the inspection apparatus.
  • the advantage of the method (1) does not come without accompanying the following penalties: the inspection apparatus decreases in detection sensitivity; and, its detection ability or “detectability” for true defects decreases simultaneously.
  • this is a method such as shown in JP-A-2000-97869 for example. Estimation of the degree of the color shading at a chip position of the detection image from the reference image of its immediately preceding chip is equivalent in principle to estimating by interpolation unknown information in the future from known information in the past.
  • utilizable information items are as less as two images i.e., a single plane of detection image and a reference image plane.
  • this method is disadvantageously limited in effects for enabling correction and removal of the color shading influenceability.
  • a pattern inspection apparatus is disclosed in JP-A-10-74812, which apparatus detects an image signal from a repeated pattern to be tested, and generates from this detected image signal a statistical image signal of the repeated pattern being tested, and then uses this generated statistical image signal as a reference image signal to compare it to the above-noted detected image signal while applying thereto position alignment, thereby extracting a defect or a defect candidate that is present in the pattern under test.
  • JP-A-3-286383 discloses therein a surface defect inspecting apparatus for detecting defects based on a pattern difference.
  • This apparatus comprises means for sequentially accepting first patterns, pattern generator means for calculating an average value of the first patterns accepted by the accepting means to thereby generate a second pattern, and means for comparing the second pattern thus generated to a newly accepted first pattern and for detecting a pattern difference, if any.
  • JP-A-5-218160 discloses a semiconductor chip appearance inspection apparatus which includes a first image memory that sequentially temporarily stores dark-and-light grayscale information of a plurality of semiconductor chips obtained by dicing a single piece of wafer, a second image memory for storing reference grayscale information used for execution of comparative judgment by comparison with the grayscale information of the first image memory, a defect-free product detector unit for comparing the grayscale information of the first image memory to that of the second image memory to thereby detect non-defective semiconductor chip products, and an image averaging processor unit for performing, when the defect-free product detector unit judges a chip as a good product, computation of the grayscale information of the first and second image memories, for rewriting the grayscale information of the second image memory based on the computation result, and for allowing the rewritten information to become a new reference grayscale information.
  • the invention employs a technique for generating an average reference image from the images of a plurality of more than two patterns of identical shape—these include forth and back ones lying relatively near to a detection image with at least the detection image being interposed therebetween of those patterns having the same shape as continuously laid out on an object being tested at equal intervals in row and column directions.
  • the invention comprises a means for storing therein a detection image and the images of a plurality of more than two identical shape patterns containing the forth and back ones lying next to the detection image with at least the detection image interposed therebetween, an average reference image generator means for generating from such the stored images an average reference image through statistical computation processing, and an image comparator means for performing comparison inspection of the detection image and the average reference image to thereby detect defects, if any.
  • a feature of the invention lies in creation of the average reference image by statistical computation processing from four identical shape patterns on the up-down and right-left sides of the detection image, with two further patterns in the up-down directions being added thereto.
  • an improved pattern defect inspection apparatus capable of removing or suppressing the color shading influenceability to thereby detect defects with high inspection accuracy even in cases where a pattern is formed of a transparent thin film on or above the object under test with the transparent thin film being variable in thickness depending upon locations overlying the object under test.
  • a pattern defect inspection apparatus of the present invention is the one that detects defects by comparing a detection image, which is obtainable by scanning using an image sensor those patterns having the same shape as continuously laid out on an object to be tested at equal intervals in row and column directions, to a reference image obtained by scanning such the identically shaped patterns residing side-by-side in the row and column directions.
  • This apparatus is characterized by comprising means for generating an average reference image through statistical computation processing from the images of identical shape patterns residing next to a detection image, including eight nearest chips that neighbor the detection image on up-down and right-left sides and at oblique or diagonal positions with the detection image interposed therebetween, and means for comparing the detection image to the generated average reference image to thereby detect defects, if any.
  • the reference image is generated from at least the eight, up-down and right-left plus diagonally neighboring nearest images with the detection image intermediately situated.
  • the statistical computation processing for generating the average reference image includes the step of performing simple averaging of the pattern of the nearest same shapes which reside next to the detection image on its up-down and right-left sides and at diagonally neighboring locations.
  • the statistical computation processing for generating the average reference image includes performing calculation of an adaptable quadratic curved plane from eight nearest identical shape patterns which lie relatively near to the detection image on the up-down and right-left sides and also at diagonally neighboring positions.
  • a scheme for calculating the adapted quadratic curved plane is a least-squares method.
  • the apparatus includes a means for calculating a mean square error at the same time during such calculation, means for using the mean square error to determine a threshold value for use during defect detection judgment, and means for judging based on this threshold value the presence or absence of a defect(s).
  • the invention is configurable in the form of a pattern defect inspection apparatus for detecting defects by comparing a detection image obtainable through scanning, by an image sensor, patterns having the identical shape and being continuously laid out on an object to be tested at equal intervals in row and column directions with a reference image obtained by scanning neighboring identical shape patterns in the row and column directions thereof, wherein the apparatus comprises means for generating an average reference image by statistical computation processing from both the detection image and the images of identical shape patterns residing next to the detection image including at least eight nearest chips on up-and-down and right-and-left sides and at diagonally neighboring positions with at least the detection image being intermediately situated, and means for detecting a defect by comparing the detection image to the average reference image thus generated.
  • FIG. 1 is a diagram showing a plan view of a wafer having its surface on which a pattern made of a transparent thin film is formed.
  • FIG. 2 is a plan view of a semiconductor wafer, along with an enlarged partial view of it.
  • FIG. 3 is a diagram representing a quadratic curved plane thus calculated.
  • FIG. 4 is a diagram showing the structure of an image sensor.
  • FIG. 5 is a plan view of an inspection area of an object to be tested.
  • FIG. 6 is a plan view showing a sensor scan locus in case a plurality of chips are scanned by the image sensor for multiple times.
  • FIG. 7 is a plan view showing an image sensor scan locus.
  • FIG. 8 is a diagram schematically showing a configuration of a pattern defect inspection apparatus.
  • FIG. 8 is a diagram schematically showing a configuration of pattern defect inspection apparatus.
  • a wafer 3 that is an object to be tested is fixed onto a rotatable Z ⁇ stage 2 , which is movable in its height direction.
  • the Z ⁇ state 2 is situated on an X-Y stage 1 that is position-slidable in an X direction that is the horizontal direction and also in Y direction.
  • a half mirror 5 is located above the wafer 3 , for directing illumination light from an illumination light source 4 toward the wafer 3 side to thereby illuminate the wafer 3 via an objective lens 6 .
  • Reflection light as given off from a top surface of the wafer 6 is guided to pass through the objective lens 6 and half mirror 5 to reach an image sensor 8 , which receives it as detection light.
  • the light that was split by the half mirror 7 enters an automatic focal point detector means 9 , which calculates the optimum focussing position and then gives a movement instruction to a Z state of the Z ⁇ stage 2 , thereby enabling detection of an image at the optimum focal point.
  • the detection light received by the image sensor 8 is passed through an analog-to-digital (A/D) converter 10 for conversion into a digital signal, which is then stored or recorded in an image storage means 11 .
  • A/D analog-to-digital
  • a process of testing an overall surface of a chip 21 includes the steps of subdividing an area of chip 21 by the effective image pickup height of the image sensor, and performing a multiplicity of scanning operations while shifting it in the height direction every time scan is done.
  • An example is as follows. Suppose that the effective image pickup height of the image sensor is one-third (1 ⁇ 3) of the chip height. Also assume that the scanning is performed while dividing the test area into three regions. If this is the case, the scanning procedure is as follows: as shown in FIG.
  • the embodiment of this invention is arranged so that a reference image which is for use as an object being subjected to comparison inspection with the detection image is created from the images of eight nearest chips lying next to the chip of detection image on its up-down and right-left sides plus at diagonally neighboring positions.
  • the above-noted image detector means 11 is required to have a capacity capable of storing all images corresponding to the effective image pickup height of the image sensor 8 with respect to a queue of three rows of chips.
  • the term “right-left” refers to the front and rear or forth and back of the detection image in the scan direction, whereas “up-down” should be interpreted as the upper and lower portions of the detection image when folded back while the scan direction is changed by the chip height.
  • the language “diagonally neighboring” is intended to mean four neighboring images on the “up-down” sides when folded back while changing the scan direction by the chip height. Details are shown in FIG. 2 . Assume that the wafer under test is 300 mm in diameter, the pixel size at the time of inspection (size on the object under test) is set at 0.2 ⁇ m ⁇ 0.2 ⁇ m, and a total number of pixels in the image sensor height direction is 4,096. Supposing that a 1 byte of memory space is required to store image information per each pixel, the storage capacity required is given as:
  • FIG. 2 is a plan view of a semiconductor wafer along with its enlarged partial view.
  • an image of a region adjacent to the test area is stored for later use as the reference image.
  • This reference image is compared to an image of the test area to thereby extract as a defect a different portion between the both.
  • On the single pierce of wafer 3 shown in FIG. 2 a plurality of chips 21 are laid out, each of which becomes an individual product. These chips 21 are continuously disposed, as patterns of identical shape, at equal intervals in the row and column direction.
  • an explanation will be given of an operation in the case of detecting whether defects are present or absent in a test area “a” within a chip (m, n).
  • the average reference image generator means 12 sequentially calculates a simple mean value (arithmetic average) of the signal intensity values of corresponding pixels of eight images of:
  • an image of chip (m, n) is read out as the detection image, which is passed to the image comparator means 13 together with the above-noted average reference image.
  • This image comparator means sequentially performs comparison of the signal intensity values of pixels corresponding to these two images. Thus, if a pixel is found to have a difference greater than a prespecified threshold value, then such pixel is detected as a defect.
  • the average reference image created in this embodiment is calculated from the eight nearest chips on the up-down and right-left sides and at diagonal positions with the chip of the detection image being interposed therebetween, an image at a central chip position is obtained by interpolation from the images of these eight peripheral chips. Due to this, it is expectable that the status of color shading irregularities to be contained in this average reference image is sufficiently proximate to the color shading state at the chip of the detection image residing at the center of these eight chips, except for a special case where the thickness of a transparent thin film making up the pattern rapidly changes to exhibit appreciable increment and decrement with respect to the chip layout interval.
  • semiconductor wafers are such that the interval or layout pitch of chips is less than or equal to 1/10 of the wafer diameter. Also assume that in those semiconductor wafers with film thickness errors falling into an allowable range, changes in thickness of the pattern-forming transparent thin film exhibit a simple increase or decrease distribution within the chip interval.
  • the defect inspection method of this embodiment obtain ultimate efficacy by simplified calculation processing, when compared to the methodology of estimating and correcting the degree of color shading irregularity at the chip position of the detection image by using only the information of a total of two images of the detection image one surface and the reference image one surface of its immediately preceding chip, as has been discussed in the introductory part of the description for example, such as the one indicated for example in JP-A-2000-97869.
  • the average reference image is obtained by calculation of the simple mean value (arithmetic average) of the eight nearest chips in the periphery of the detection image on a per-pixel basis, similar results are obtainable by a process having the steps of using a least-squares method to obtain, per each pixel corresponding to one of these eight chip images, the best adaptable quadratic curved plane:
  • the statistical computation method for generating the average reference image includes calculating a quadratic curved plane with respect to the signal intensity of the luminance on each corresponding pixel of the eight nearest chip images, obtaining the signal intensity on the quadratic curved plane corresponding to a pixel at the g(x, y) point of the detection image, and then comparing this averaged signal intensity to a signal at the above-noted g(x, y) point.
  • FIG. 3 shows an example of such quadratic curved plane.
  • Black dots as plotted herein represent the signal intensities at positions (x, y) within respective chip images. Eight points of black dots are used to calculate the quadratic curved plane by statistical computation, thereby obtaining the signal intensity at a position corresponding to detection on the quadratic curved plane thus calculated relative to the signal intensity at a position (x, y) within a detection chip image as indicated by a star sign or asterisk. Although an explanation as to its intermediate calculation process is eliminated herein, this calculation resultingly becomes very simple.
  • the signal value of each pixel of the average reference image may be calculated as:
  • Im,n ⁇ 0.25 ⁇ Im ⁇ 1 ,n+ 1+0.5 ⁇ Im,n+ 1 ⁇ 0.25 ⁇ Im+ 1 ,n+ 1+0.5 ⁇ Im ⁇ 1 ,n+ 0.5 ⁇ Im+ 1 ⁇ n ⁇ 0.25 ⁇ Im ⁇ 1 ,n ⁇ 1+0.5 ⁇ Im,n ⁇ 1 ⁇ 0.25 ⁇ Im+ 1 ,n ⁇ 1
  • determining the threshold value is such that appropriate setup accompanies difficulties which follow: if it is too large, then the resultant sensitivity decreases unnecessarily; alternatively, if too small then noise components or the like are picked up even where no defects are present in reality, resulting in unwanted production of false defect information.
  • This mean square error acts as a parameter or index indicative of the exact degree of deviation owned by the identical shape patterns contained in these eight chips even after correction of the color shading influenceability using this quadratic curved plane. Accordingly, when using this value to dynamically determine, during testing, the threshold value upon judgment of whether defects are present or absent, it is possible to determine the threshold value while allowing it to reflect the actual variations. It is also possible to perform inspection while automatically increasing the threshold value at certain locations large in noise components and pattern shape fluctuations and adversely automatically lowering the threshold value at those locations less in such influenceability. Thus it becomes possible to obtain an advantage as to the capability for effectively detecting defects.

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Abstract

The pattern defect inspection apparatus is operable to detect defects by comparing a detection image, which is obtained through scanning by an image sensor those patterns that have the identical shape and are continuously disposed on the object under tested at equal intervals in row and column directions, with a reference image obtained by scanning neighboring identical shape patterns in the row and column directions. This apparatus has a unit for generating an average reference image by statistical computation processing from the images of identical shape patterns lying next to the detection image including at least eight nearest chips on the up-and-down and right-and-left sides and at diagonal positions with the detection image being intermediately situated. The apparatus also includes a unit that detects a defect by comparing the detection image to the average reference image thus generated.

Description

    FIELD OF THE INVENTION
  • The present invention relates to a method and apparatus for performing defect inspection while detecting the images of a plurality of patterns as formed on or above an object to be tested, such as a semiconductor wafer, photo-mask, printed circuit board or equivalents thereto.
  • BACKGROUND OF THE INVENTION
  • Typically in pattern defect inspection procedures, a one-dimensional (1D) or linear image sensor is used as the image detection means for picking up the image of an object to be tested. FIG. 4 is a diagram showing an arrangement of such image sensor 8, and FIG. 5 is a plan view of an inspection area of the object being tested, for indicating the area that is image-detectable by a single time of scanning. Scan the object under test in a direction at right angles to the layout direction of picture elements or “pixels” 81 of the image sensor 8, thereby acquiring a two-dimensional (2D) image. The length of the direction along which the pixels 81 are queued is called the “height” of the image sensor 8. In addition, in case the object under test is assumed to be a semiconductor wafer having a plurality of semiconductor chips being presently fabricated, the length of a single chip in the same direction as the height of image sensor 8 is called the chip height. Generally the chip height is larger than the height of image sensor 8, so it is merely possible to detect only an image of part of the chip through one-time scanning of the image sensor 8. The significance of this chip's partial image is determinable depending upon the height of the image sensor 8 that performs detection and the imaging magnification of an image focussing optical system for projecting the chip image onto this image sensor 8. This height is called the effective image pickup height of the image sensor 8. In a combination of a currently used image sensor and its associated image focusing optical system, the effective image pickup height is less than the chip height. Accordingly, in order to inspect an overall chip surface, a method is employed for scanning it while offsetting in the height direction for multiple times.
  • FIG. 6 is a plan view diagram showing a sensor scan locus 101 in case a plurality of chips 21 that are formed on a wafer are scanned by an image sensor for several times. Usually in the pattern defect inspection apparatus, the image sensor is fixed while using a stage to move the wafer under test. Firstly, let the test object move in the X direction; then, acquire an image. Information per pixel of one chip 21 is stored in a memory in the order of scanning. After having completed the image detection in a one-time scan cycle, let the test object move in the Y direction by a distance corresponding to the effective image pickup height of the image sensor. The stage is driven to shift in position as indicated by broken line in FIG. 6 so that the scan direction becomes reversed. This will be repeated to thereby achieve sequential image detection.
  • While inspection of the chip 21 is performed by image comparison of the same patterns, the image of a test area “c” is used as a reference image in the case of testing an area “b.” However, when testing an area “a” that is the forehand chip of each row to be scanned, it is impossible to perform any intended inspection due to the absence of a reference image in an area immediately preceding the same pattern. This would result in generation of noninspectable areas or regions in the outer periphery of the wafer. For this reason, non-inspectable chips would take place in those in the wafer outer periphery.
  • In prior known pattern defect inspecting apparatus, there is the one that solved the above-noted problem by modifying the scan method (for example, see JP-A-11-160247). FIG. 7 is a plan view showing the scanning locus of an image sensor in a similar way to FIG. 6. In this case, the effective image pickup height of the image sensor is one-third (⅓) of the chip height. Assume that scanning is done while dividing the test area into three strip-like regions. Although the scanning of the first row in the X direction is the same as that shown in FIG. 6, the second row is scanned while causing an object under test to move by a distance corresponding to the height of one chip in the Y direction. This will be repeated for execution of comparative inspection of the images of identical patterns each having its region equal in size to ⅓ of a chip. Upon completion of the last row, as indicated by dotted line in FIG. 6, the image of the same pattern in the next ⅓ regions of the chip is subjected to comparison inspection. After having finished the first chip, comparison inspection is done for the image of the same pattern in the remaining ⅓ region of the chip.
  • In the case of testing of an area “b” which is immediately after a fold-back or a halfway point, the pixel information of the area “c” for use as a reference image is read out in an order reverse to the order at the time of data storage, whereby the comparison inspection is executable while letting the area b and area c be the same pattern image. Optionally, the image of another area of the same pattern may be prestored as the reference image of the area a upon startup of the inspection. Whereby, it is possible to perform the inspection of the area a also.
  • However, in any one of the pattern defect inspection apparatus for performing inspection based on the scan locus shown in FIG. 6 and the pattern defect inspection apparatus for performing inspection relying upon the scan locus shown in FIG. 7, comparative inspection of the detection image of a chip is performed by comparing it to the reference image of its immediately preceding chip with the same pattern. Using the image of such immediately preceding chip in this way raises problems which follow.
  • An object under test for use as the object being subjected to pattern defect inspection is such that a pattern is typically formed of a material that is transparent with respect to the wavelength of visible light, such as a photo-resist or a dielectric film made of SiO2 or the like. In this case, even if a thin film is transparent relative to the wavelength of light being used in the defect inspection apparatus, it exhibits certain reflectivity which is determinable by such the light wavelength and the refractivity of a material making up the pattern plus a film thickness. This makes it possible for the defect inspection apparatus to detect its presence as a light-and-shade image. FIG. 1 shows an exemplary wafer having a pattern of thin film formed thereon, which is made of a material transparent to the wavelength of light being used in the defect inspection apparatus. Generally in such the wafer, the thickness of the thin film pattern is not perfectly flat on an entire wafer surface but slightly different depending on locations; however, a certain degree of film thickness error is made acceptable because such error does not affect the manufacture of semiconductor chips. Unfortunately, a difference in film thickness occurring depending on locations can create a likewise difference in reflectivity of the pattern, resulting in occurrence of an appreciable difference in brightness or luminance of an image to be detected. This phenomenon is called the color shading irregularity. For example, suppose that a neighboring chip “n” and its immediately preceding chip n−1 of FIG. 1 are such that the same shaped patterns “p” included therein are different in film thickness from each other, resulting in occurrence of color shading. In this case, if the comparison inspection is carried out while letting the chip n be a detection image and also regarding the chip n−1 as a reference image, then the pattern p must be erroneously detected as a defect. This occurs because the resultant image is different in light-and-shape property even though the pattern p is the same in shape between these two images and no defects are present therein. Such the false defect information raises difficulties in distinction from a true defect and thus is a serious problem relating to the reliability of the inspection apparatus.
  • Prior known approaches to avoiding the above-noted false defect information include two methods which follow:
  • (1) increasing the threshold value so that the color shading irregularity is insensitive to test results during inspection while comparing a detection image to reference image, wherein the threshold value becomes a criterion for judgment of which degree of difference is regarded as a dominant difference; and
  • (2) correcting or amending the influenceability of color shading irregularity occurring between the detection image and reference image and then performing comparison inspection after removal of the color shading.
  • The advantage of the method (1) does not come without accompanying the following penalties: the inspection apparatus decreases in detection sensitivity; and, its detection ability or “detectability” for true defects decreases simultaneously. Regarding the method (2), this is a method such as shown in JP-A-2000-97869 for example. Estimation of the degree of the color shading at a chip position of the detection image from the reference image of its immediately preceding chip is equivalent in principle to estimating by interpolation unknown information in the future from known information in the past. In addition, utilizable information items are as less as two images i.e., a single plane of detection image and a reference image plane. Thus, this method is disadvantageously limited in effects for enabling correction and removal of the color shading influenceability.
  • A pattern inspection apparatus is disclosed in JP-A-10-74812, which apparatus detects an image signal from a repeated pattern to be tested, and generates from this detected image signal a statistical image signal of the repeated pattern being tested, and then uses this generated statistical image signal as a reference image signal to compare it to the above-noted detected image signal while applying thereto position alignment, thereby extracting a defect or a defect candidate that is present in the pattern under test.
  • JP-A-3-286383 discloses therein a surface defect inspecting apparatus for detecting defects based on a pattern difference. This apparatus comprises means for sequentially accepting first patterns, pattern generator means for calculating an average value of the first patterns accepted by the accepting means to thereby generate a second pattern, and means for comparing the second pattern thus generated to a newly accepted first pattern and for detecting a pattern difference, if any.
  • JP-A-5-218160 discloses a semiconductor chip appearance inspection apparatus which includes a first image memory that sequentially temporarily stores dark-and-light grayscale information of a plurality of semiconductor chips obtained by dicing a single piece of wafer, a second image memory for storing reference grayscale information used for execution of comparative judgment by comparison with the grayscale information of the first image memory, a defect-free product detector unit for comparing the grayscale information of the first image memory to that of the second image memory to thereby detect non-defective semiconductor chip products, and an image averaging processor unit for performing, when the defect-free product detector unit judges a chip as a good product, computation of the grayscale information of the first and second image memories, for rewriting the grayscale information of the second image memory based on the computation result, and for allowing the rewritten information to become a new reference grayscale information.
  • SUMMARY OF THE INVENTION
  • An object of this invention is to provide a pattern defect inspection apparatus capable of improving the accuracy of pattern defect inspection even when a pattern which is formed of a transparent thin film is different in thickness between the position of a detection image and the position of a reference image. Another object of the invention is to provide a pattern defect inspection method with such the capability.
  • To attain the foregoing objects, the invention employs a technique for generating an average reference image from the images of a plurality of more than two patterns of identical shape—these include forth and back ones lying relatively near to a detection image with at least the detection image being interposed therebetween of those patterns having the same shape as continuously laid out on an object being tested at equal intervals in row and column directions.
  • To do this, the invention comprises a means for storing therein a detection image and the images of a plurality of more than two identical shape patterns containing the forth and back ones lying next to the detection image with at least the detection image interposed therebetween, an average reference image generator means for generating from such the stored images an average reference image through statistical computation processing, and an image comparator means for performing comparison inspection of the detection image and the average reference image to thereby detect defects, if any.
  • A feature of the invention lies in creation of the average reference image by statistical computation processing from four identical shape patterns on the up-down and right-left sides of the detection image, with two further patterns in the up-down directions being added thereto.
  • With this arrangement, it is possible, by generating the reference image from at least four up-down and right-left images with the detection image interposed therebetween, to obtain the intended reference image which approximates the color shading irregularity at the detection image position. Thus it is possible to effectively suppress color shading influenceabilities during comparison testing of this reference image and the detection image. This in turn makes it possible to provide the pattern defect inspection method and apparatus capable of improving the accuracy of pattern defect inspection even for an object under test that is relatively large in color shading influenceability.
  • According to the invention, it is possible to achieve an improved pattern defect inspection apparatus capable of removing or suppressing the color shading influenceability to thereby detect defects with high inspection accuracy even in cases where a pattern is formed of a transparent thin film on or above the object under test with the transparent thin film being variable in thickness depending upon locations overlying the object under test.
  • A pattern defect inspection apparatus of the present invention is the one that detects defects by comparing a detection image, which is obtainable by scanning using an image sensor those patterns having the same shape as continuously laid out on an object to be tested at equal intervals in row and column directions, to a reference image obtained by scanning such the identically shaped patterns residing side-by-side in the row and column directions. This apparatus is characterized by comprising means for generating an average reference image through statistical computation processing from the images of identical shape patterns residing next to a detection image, including eight nearest chips that neighbor the detection image on up-down and right-left sides and at oblique or diagonal positions with the detection image interposed therebetween, and means for comparing the detection image to the generated average reference image to thereby detect defects, if any.
  • In accordance with this arrangement, the reference image is generated from at least the eight, up-down and right-left plus diagonally neighboring nearest images with the detection image intermediately situated. Thus it becomes possible to obtain the reference image that approximates the color shading state at the detection image position so that it is possible to effectively lighten the color shading influenceability during comparison testing of this reference image and the detection image. This makes it possible to provide the intended pattern defect inspection method and apparatus capable of improving the accuracy of pattern defect inspection even for those objects under test with large color shading influenceability.
  • The statistical computation processing for generating the average reference image includes the step of performing simple averaging of the pattern of the nearest same shapes which reside next to the detection image on its up-down and right-left sides and at diagonally neighboring locations.
  • Alternatively the statistical computation processing for generating the average reference image includes performing calculation of an adaptable quadratic curved plane from eight nearest identical shape patterns which lie relatively near to the detection image on the up-down and right-left sides and also at diagonally neighboring positions.
  • A scheme for calculating the adapted quadratic curved plane is a least-squares method. To this end, the apparatus includes a means for calculating a mean square error at the same time during such calculation, means for using the mean square error to determine a threshold value for use during defect detection judgment, and means for judging based on this threshold value the presence or absence of a defect(s).
  • Optionally the invention is configurable in the form of a pattern defect inspection apparatus for detecting defects by comparing a detection image obtainable through scanning, by an image sensor, patterns having the identical shape and being continuously laid out on an object to be tested at equal intervals in row and column directions with a reference image obtained by scanning neighboring identical shape patterns in the row and column directions thereof, wherein the apparatus comprises means for generating an average reference image by statistical computation processing from both the detection image and the images of identical shape patterns residing next to the detection image including at least eight nearest chips on up-and-down and right-and-left sides and at diagonally neighboring positions with at least the detection image being intermediately situated, and means for detecting a defect by comparing the detection image to the average reference image thus generated.
  • Other objects, features and advantages of the invention will become apparent from the following description of the embodiments of the invention taken in conjunction with the accompanying drawings.
  • BRIEF DESCRIPTION OF THE DRAWINGS
  • FIG. 1 is a diagram showing a plan view of a wafer having its surface on which a pattern made of a transparent thin film is formed.
  • FIG. 2 is a plan view of a semiconductor wafer, along with an enlarged partial view of it.
  • FIG. 3 is a diagram representing a quadratic curved plane thus calculated.
  • FIG. 4 is a diagram showing the structure of an image sensor.
  • FIG. 5 is a plan view of an inspection area of an object to be tested.
  • FIG. 6 is a plan view showing a sensor scan locus in case a plurality of chips are scanned by the image sensor for multiple times.
  • FIG. 7 is a plan view showing an image sensor scan locus.
  • FIG. 8 is a diagram schematically showing a configuration of a pattern defect inspection apparatus.
  • DETAILED DESCRIPTION OF THE EMBODIMENTS
  • One embodiment of the invention will be explained with reference to the accompanying drawings.
  • FIG. 8 is a diagram schematically showing a configuration of pattern defect inspection apparatus. A wafer 3 that is an object to be tested is fixed onto a rotatable Zθ stage 2, which is movable in its height direction. The Zθ state 2 is situated on an X-Y stage 1 that is position-slidable in an X direction that is the horizontal direction and also in Y direction.
  • A half mirror 5 is located above the wafer 3, for directing illumination light from an illumination light source 4 toward the wafer 3 side to thereby illuminate the wafer 3 via an objective lens 6. Reflection light as given off from a top surface of the wafer 6 is guided to pass through the objective lens 6 and half mirror 5 to reach an image sensor 8, which receives it as detection light. Additionally the light that was split by the half mirror 7 enters an automatic focal point detector means 9, which calculates the optimum focussing position and then gives a movement instruction to a Z state of the Zθ stage 2, thereby enabling detection of an image at the optimum focal point. The detection light received by the image sensor 8 is passed through an analog-to-digital (A/D) converter 10 for conversion into a digital signal, which is then stored or recorded in an image storage means 11.
  • As the chip height is generally greater than the effective image pickup height of the image sensor 8, a process of testing an overall surface of a chip 21 includes the steps of subdividing an area of chip 21 by the effective image pickup height of the image sensor, and performing a multiplicity of scanning operations while shifting it in the height direction every time scan is done. An example is as follows. Suppose that the effective image pickup height of the image sensor is one-third (⅓) of the chip height. Also assume that the scanning is performed while dividing the test area into three regions. If this is the case, the scanning procedure is as follows: as shown in FIG. 7, after having performed the first-time scanning in the X direction from its left to right, let the object under test move in the Y direction by a distance corresponding to one chip height; then, perform a second scan operation. This will be executed iteratively to thereby perform comparison inspection of an image of the same pattern equivalent to the chip's ⅓ region. Upon completion of the last line, perform comparison inspection of an image of the same pattern of the chip's next ⅓ region as indicated by broken line in FIG. 7. When the first chip is ended, perform comparative inspection of an image of the same pattern of the chip's remaining ⅓ region whereby the inspection of the entire surface area of the chip 21 is completed.
  • As will be described later, the embodiment of this invention is arranged so that a reference image which is for use as an object being subjected to comparison inspection with the detection image is created from the images of eight nearest chips lying next to the chip of detection image on its up-down and right-left sides plus at diagonally neighboring positions. To this end, the above-noted image detector means 11 is required to have a capacity capable of storing all images corresponding to the effective image pickup height of the image sensor 8 with respect to a queue of three rows of chips. Note here that the term “right-left” refers to the front and rear or forth and back of the detection image in the scan direction, whereas “up-down” should be interpreted as the upper and lower portions of the detection image when folded back while the scan direction is changed by the chip height. The language “diagonally neighboring” is intended to mean four neighboring images on the “up-down” sides when folded back while changing the scan direction by the chip height. Details are shown in FIG. 2. Assume that the wafer under test is 300 mm in diameter, the pixel size at the time of inspection (size on the object under test) is set at 0.2 μm×0.2 μm, and a total number of pixels in the image sensor height direction is 4,096. Supposing that a 1 byte of memory space is required to store image information per each pixel, the storage capacity required is given as:

  • 300 mm÷0.2 μm×4,096×1 byte×3=approx. 17 gigabytes (GB),
  • (where, 1 GB=1,073,741,824 bytes).
  • Traditionally, this large capacity was achievable only by magnetic recording media of extremely low recording speeds, so it has been considered unrealistic to realize such the technology in the pattern defect inspection apparatus that is required to perform processing on a real-time basis during inspection. Fortunately, recent advances in semiconductor device technologies make it possible to attain such degree of storage capacity by use of an ensemble of semiconductor memories.
  • FIG. 2 is a plan view of a semiconductor wafer along with its enlarged partial view. In the pattern defect inspection apparatus of this embodiment, an image of a region adjacent to the test area is stored for later use as the reference image. This reference image is compared to an image of the test area to thereby extract as a defect a different portion between the both. On the single pierce of wafer 3 shown in FIG. 2, a plurality of chips 21 are laid out, each of which becomes an individual product. These chips 21 are continuously disposed, as patterns of identical shape, at equal intervals in the row and column direction. Here, an explanation will be given of an operation in the case of detecting whether defects are present or absent in a test area “a” within a chip (m, n). Sequentially scan the wafer of an object under test in the order of (n−1)th, n-th and (n+1)th rows. Upon completion of the scanning up to a chip in the (m+1)th column of the (n+1)th row, the resultant image is stored in the image storage means 11. At this time, the average reference image generator means 12 sequentially calculates a simple mean value (arithmetic average) of the signal intensity values of corresponding pixels of eight images of:
  • (m−1, n−1),
  • (m, n−1),
  • (m+1, n−1),
  • (m−1, n),
  • (m+1, n),
  • (m−1, n+1),
  • (m, n+1), and
  • (m+1, n+1),
  • thereby to produce an averaged reference image as the average of these eight images. It should be noted that since respective chips of the (n−1)th and (n+1)th rows and each chip of n-th row are such that the stage's scan direction is reversed, read-out is performed in the opposite direction during reading of the stored image(s), thereby attaining equalization of the direction of image information.
  • Next, an image of chip (m, n) is read out as the detection image, which is passed to the image comparator means 13 together with the above-noted average reference image. This image comparator means sequentially performs comparison of the signal intensity values of pixels corresponding to these two images. Thus, if a pixel is found to have a difference greater than a prespecified threshold value, then such pixel is detected as a defect.
  • In view of the fact that the average reference image created in this embodiment is calculated from the eight nearest chips on the up-down and right-left sides and at diagonal positions with the chip of the detection image being interposed therebetween, an image at a central chip position is obtained by interpolation from the images of these eight peripheral chips. Due to this, it is expectable that the status of color shading irregularities to be contained in this average reference image is sufficiently proximate to the color shading state at the chip of the detection image residing at the center of these eight chips, except for a special case where the thickness of a transparent thin film making up the pattern rapidly changes to exhibit appreciable increment and decrement with respect to the chip layout interval. Generally, it is assumable that semiconductor wafers are such that the interval or layout pitch of chips is less than or equal to 1/10 of the wafer diameter. Also assume that in those semiconductor wafers with film thickness errors falling into an allowable range, changes in thickness of the pattern-forming transparent thin film exhibit a simple increase or decrease distribution within the chip interval. As apparent from the foregoing, it is possible for the defect inspection method of this embodiment to obtain ultimate efficacy by simplified calculation processing, when compared to the methodology of estimating and correcting the degree of color shading irregularity at the chip position of the detection image by using only the information of a total of two images of the detection image one surface and the reference image one surface of its immediately preceding chip, as has been discussed in the introductory part of the description for example, such as the one indicated for example in JP-A-2000-97869.
  • Note here that although in the above embodiment the average reference image is obtained by calculation of the simple mean value (arithmetic average) of the eight nearest chips in the periphery of the detection image on a per-pixel basis, similar results are obtainable by a process having the steps of using a least-squares method to obtain, per each pixel corresponding to one of these eight chip images, the best adaptable quadratic curved plane:

  • g(x,y)=ax 2 +by 2 +cxy+dx+ey+f,  (Eq. 1)
  • then, identifying the value of g(x, y) at the chip position of a centrally located detection image, and next defining this value as the signal intensity concerning the brightness or luminance of such pixel. More specifically, the statistical computation method for generating the average reference image includes calculating a quadratic curved plane with respect to the signal intensity of the luminance on each corresponding pixel of the eight nearest chip images, obtaining the signal intensity on the quadratic curved plane corresponding to a pixel at the g(x, y) point of the detection image, and then comparing this averaged signal intensity to a signal at the above-noted g(x, y) point. FIG. 3 shows an example of such quadratic curved plane. Black dots as plotted herein represent the signal intensities at positions (x, y) within respective chip images. Eight points of black dots are used to calculate the quadratic curved plane by statistical computation, thereby obtaining the signal intensity at a position corresponding to detection on the quadratic curved plane thus calculated relative to the signal intensity at a position (x, y) within a detection chip image as indicated by a star sign or asterisk. Although an explanation as to its intermediate calculation process is eliminated herein, this calculation resultingly becomes very simple. The signal value of each pixel of the average reference image may be calculated as:

  • Im,n=−0.25×Im−1,n+1+0.5×Im,n+1−0.25×Im+1,n+1+0.5×Im−1,n+0.5×Im+1·n−0.25×Im−1,n−1+0.5×Im,n−1−0.25×Im+1,n−1
  • where, “Ip, q” denotes the signal value of the pixel of interest at a chip (p, q). With this method, the calculation procedure becomes somewhat complex when compared to the simple mean value (arithmetic average); however, it offers an advantage as to an ability to generate the average reference image with enhanced accuracy even in cases where the film thickness rapidly changes with respect to the chip interval.
  • Additionally in light of the fact that in this method using the least-squares method, it is possible to simultaneously obtain the mean square error (i.e., an expectation value of a square error between the quadratic curved plane thus obtained and the original sample data), there is another advantage. Typically even when comparing identical shape patterns having no defects, calculation of an image difference does not always result in zero due to the presence of various kinds of noise components attempting to superposing image signals and/or fluctuation or else of micro-shapes that are too small to be categorized as defects. For this reason, when judging whether defects are present or absent, a need is felt to detect as defects only in case the image difference exceeds a fixed value that was preset as a threshold value. Unfortunately, determining the threshold value is such that appropriate setup accompanies difficulties which follow: if it is too large, then the resultant sensitivity decreases unnecessarily; alternatively, if too small then noise components or the like are picked up even where no defects are present in reality, resulting in unwanted production of false defect information. This mean square error acts as a parameter or index indicative of the exact degree of deviation owned by the identical shape patterns contained in these eight chips even after correction of the color shading influenceability using this quadratic curved plane. Accordingly, when using this value to dynamically determine, during testing, the threshold value upon judgment of whether defects are present or absent, it is possible to determine the threshold value while allowing it to reflect the actual variations. It is also possible to perform inspection while automatically increasing the threshold value at certain locations large in noise components and pattern shape fluctuations and adversely automatically lowering the threshold value at those locations less in such influenceability. Thus it becomes possible to obtain an advantage as to the capability for effectively detecting defects.
  • It should be further understood by those skilled in the art that although the foregoing description has been made on embodiments of the invention, the invention is not limited thereto and various changes and modifications may be made without departing from the spirit of the invention and the scope of the appended claims.

Claims (2)

1. A pattern defect inspection apparatus for detecting defects by comparing a detection image obtainable through scanning, by an image sensor, patterns having an identical shape and being continuously laid out on an object to be tested at equal intervals in row and column directions with a reference image obtained by scanning patterns of the identical shape neighboring in the row and column directions thereof, said apparatus comprising:
means for generating an average reference image by statistical computation processing from images of identical shape patterns lying next to the detection image including at least four nearest chips on up-and-down and right-and-left sides with the detection image being intermediately situated; and
means for detecting a defect by comparing the detection image to the average reference image thus generated.
2-8. (canceled)
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Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20120070089A1 (en) * 2009-05-29 2012-03-22 Yukari Yamada Method of manufacturing a template matching template, as well as a device for manufacturing a template
US20130322737A1 (en) * 2012-05-30 2013-12-05 Hitachi High-Technologies Corporation Defect inspection method and defect inspection apparatus
US9766186B2 (en) 2014-08-27 2017-09-19 Kla-Tencor Corp. Array mode repeater detection
US9766187B2 (en) 2014-08-27 2017-09-19 Kla-Tencor Corp. Repeater detection
US20170309007A1 (en) * 2016-04-22 2017-10-26 Kla-Tencor Corporation System, method and computer program product for correcting a difference image generated from a comparison of target and reference dies
WO2018089459A1 (en) * 2016-11-10 2018-05-17 Kla-Tencor Corporation High sensitivity repeater defect detection
CN109060841A (en) * 2018-08-11 2018-12-21 珠海宝利通耗材有限公司 Printer cartridge image quality method of determination and evaluation and system
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Families Citing this family (78)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP4351522B2 (en) * 2003-11-28 2009-10-28 株式会社日立ハイテクノロジーズ Pattern defect inspection apparatus and pattern defect inspection method
JP4758358B2 (en) 2004-01-29 2011-08-24 ケーエルエー−テンカー コーポレイション Computer-implemented method for detecting defects in reticle design data
JP4904034B2 (en) 2004-09-14 2012-03-28 ケーエルエー−テンカー コーポレイション Method, system and carrier medium for evaluating reticle layout data
US7128992B2 (en) 2004-12-16 2006-10-31 Utc Fuel Cells, Llc Dual pump fuel cell temperature management system
US8194946B2 (en) * 2005-07-28 2012-06-05 Fujifilm Corporation Aligning apparatus, aligning method, and the program
US7769225B2 (en) 2005-08-02 2010-08-03 Kla-Tencor Technologies Corp. Methods and systems for detecting defects in a reticle design pattern
KR100648201B1 (en) * 2005-08-08 2006-11-23 삼성전자주식회사 Method of inspecting a substrate and apparatus for inspecting substrate using the same
US7676077B2 (en) 2005-11-18 2010-03-09 Kla-Tencor Technologies Corp. Methods and systems for utilizing design data in combination with inspection data
US7570796B2 (en) 2005-11-18 2009-08-04 Kla-Tencor Technologies Corp. Methods and systems for utilizing design data in combination with inspection data
US8041103B2 (en) 2005-11-18 2011-10-18 Kla-Tencor Technologies Corp. Methods and systems for determining a position of inspection data in design data space
DE102006005800B4 (en) * 2006-02-08 2007-12-06 Atg Test Systems Gmbh Method and apparatus for testing unpopulated printed circuit boards
JP4165580B2 (en) * 2006-06-29 2008-10-15 トヨタ自動車株式会社 Image processing apparatus and image processing program
JP5466811B2 (en) * 2006-11-22 2014-04-09 オリンパス株式会社 Substrate inspection apparatus and substrate inspection method
JP2008139201A (en) * 2006-12-04 2008-06-19 Tokyo Electron Ltd Apparatus and method for detecting defect, apparatus and method for processing information, and its program
JP4065893B1 (en) * 2006-12-04 2008-03-26 東京エレクトロン株式会社 Defect detection device, defect detection method, information processing device, information processing method, and program thereof
JP4102842B1 (en) 2006-12-04 2008-06-18 東京エレクトロン株式会社 Defect detection device, defect detection method, information processing device, information processing method, and program thereof
JP4398971B2 (en) * 2006-12-07 2010-01-13 シャープ株式会社 Image processing device
WO2008077100A2 (en) 2006-12-19 2008-06-26 Kla-Tencor Corporation Systems and methods for creating inspection recipes
US8194968B2 (en) 2007-01-05 2012-06-05 Kla-Tencor Corp. Methods and systems for using electrical information for a device being fabricated on a wafer to perform one or more defect-related functions
US7962863B2 (en) 2007-05-07 2011-06-14 Kla-Tencor Corp. Computer-implemented methods, systems, and computer-readable media for determining a model for predicting printability of reticle features on a wafer
US7738093B2 (en) 2007-05-07 2010-06-15 Kla-Tencor Corp. Methods for detecting and classifying defects on a reticle
US8213704B2 (en) 2007-05-09 2012-07-03 Kla-Tencor Corp. Methods and systems for detecting defects in a reticle design pattern
JP5071782B2 (en) * 2007-07-02 2012-11-14 東京エレクトロン株式会社 Substrate defect inspection method and defect inspection program
US7796804B2 (en) * 2007-07-20 2010-09-14 Kla-Tencor Corp. Methods for generating a standard reference die for use in a die to standard reference die inspection and methods for inspecting a wafer
US7711514B2 (en) 2007-08-10 2010-05-04 Kla-Tencor Technologies Corp. Computer-implemented methods, carrier media, and systems for generating a metrology sampling plan
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US8139844B2 (en) 2008-04-14 2012-03-20 Kla-Tencor Corp. Methods and systems for determining a defect criticality index for defects on wafers
JPWO2009139394A1 (en) * 2008-05-13 2011-09-22 株式会社ニコン Optical inspection device
US9659670B2 (en) 2008-07-28 2017-05-23 Kla-Tencor Corp. Computer-implemented methods, computer-readable media, and systems for classifying defects detected in a memory device area on a wafer
JP5414215B2 (en) 2008-07-30 2014-02-12 株式会社日立ハイテクノロジーズ Circuit pattern inspection apparatus and circuit pattern inspection method
US8775101B2 (en) 2009-02-13 2014-07-08 Kla-Tencor Corp. Detecting defects on a wafer
US8204297B1 (en) 2009-02-27 2012-06-19 Kla-Tencor Corp. Methods and systems for classifying defects detected on a reticle
US8112241B2 (en) 2009-03-13 2012-02-07 Kla-Tencor Corp. Methods and systems for generating an inspection process for a wafer
JP5379571B2 (en) * 2009-06-19 2013-12-25 株式会社アドバンテスト Pattern inspection apparatus and pattern inspection method
US8577120B1 (en) 2009-11-05 2013-11-05 The United States Of America As Represented By The Administrator Of The National Aeronautics And Space Administration Methods and systems for characterization of an anomaly using infrared flash thermography
US9066028B1 (en) 2010-01-08 2015-06-23 The United States Of America As Represented By The Administator Of The National Aeronautics And Space Administration Methods and systems for measurement and estimation of normalized contrast in infrared thermography
US8781781B2 (en) 2010-07-30 2014-07-15 Kla-Tencor Corp. Dynamic care areas
KR20120045774A (en) * 2010-11-01 2012-05-09 삼성전자주식회사 Method for inspecting wafer
DE102010043477A1 (en) * 2010-11-05 2012-05-10 Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. Method and X-ray inspection system for testing identical components using X-radiation
JP5593209B2 (en) * 2010-11-30 2014-09-17 株式会社日立ハイテクノロジーズ Inspection device
US9170211B2 (en) 2011-03-25 2015-10-27 Kla-Tencor Corp. Design-based inspection using repeating structures
DE102011108754A1 (en) * 2011-07-28 2013-01-31 Khs Gmbh inspection unit
JP2012019220A (en) * 2011-08-01 2012-01-26 Hitachi High-Technologies Corp Circuit pattern inspection device and circuit pattern inspection method
US9087367B2 (en) 2011-09-13 2015-07-21 Kla-Tencor Corp. Determining design coordinates for wafer defects
US8831334B2 (en) 2012-01-20 2014-09-09 Kla-Tencor Corp. Segmentation for wafer inspection
DE102012101242A1 (en) * 2012-02-16 2013-08-22 Hseb Dresden Gmbh inspection procedures
TWI477768B (en) * 2012-03-30 2015-03-21 Intekplus Co Ltd Method and apparatus for automatic optical inspection of flat panel substrate
US8826200B2 (en) 2012-05-25 2014-09-02 Kla-Tencor Corp. Alteration for wafer inspection
US9189844B2 (en) 2012-10-15 2015-11-17 Kla-Tencor Corp. Detecting defects on a wafer using defect-specific information
US9390494B2 (en) * 2012-12-13 2016-07-12 Kla-Tencor Corporation Delta die intensity map measurement
US9053527B2 (en) 2013-01-02 2015-06-09 Kla-Tencor Corp. Detecting defects on a wafer
US9134254B2 (en) 2013-01-07 2015-09-15 Kla-Tencor Corp. Determining a position of inspection system output in design data space
US9311698B2 (en) 2013-01-09 2016-04-12 Kla-Tencor Corp. Detecting defects on a wafer using template image matching
KR102019534B1 (en) 2013-02-01 2019-09-09 케이엘에이 코포레이션 Detecting defects on a wafer using defect-specific and multi-channel information
US9390492B2 (en) * 2013-03-14 2016-07-12 Kla-Tencor Corporation Method and system for reference-based overlay measurement
US9865512B2 (en) 2013-04-08 2018-01-09 Kla-Tencor Corp. Dynamic design attributes for wafer inspection
US9310320B2 (en) 2013-04-15 2016-04-12 Kla-Tencor Corp. Based sampling and binning for yield critical defects
CN103913468B (en) * 2014-03-31 2016-05-04 湖南大学 Many defects of vision checkout equipment and the method for large-scale LCD glass substrate on production line
US10118345B2 (en) 2015-06-17 2018-11-06 Xerox Corporation System and method for evaluation of a three-dimensional (3D) object during formation of the object
US10005229B2 (en) 2015-08-31 2018-06-26 Xerox Corporation System for using optical sensor focus to identify feature heights on objects being produced in a three-dimensional object printer
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US10011078B2 (en) 2015-10-01 2018-07-03 Xerox Corporation System for using multiple optical sensor arrays to measure features on objects produced in a three-dimensional object printer
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JP7290780B1 (en) 2022-09-01 2023-06-13 株式会社エクサウィザーズ Information processing method, computer program and information processing device
CN116091506B (en) * 2023-04-12 2023-06-16 湖北工业大学 Machine vision defect quality inspection method based on YOLOV5

Citations (35)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5272536A (en) * 1990-03-13 1993-12-21 Sony Corporation Dark current and defective pixel correction apparatus
US5312779A (en) * 1992-05-26 1994-05-17 Texas Instruments Incorporated Color spatial light modulator and method of manufacture
US5574800A (en) * 1993-08-24 1996-11-12 Kabushiki Kaisha Toshiba Pattern defect inspection method and apparatus
US5638465A (en) * 1994-06-14 1997-06-10 Nippon Telegraph And Telephone Corporation Image inspection/recognition method, method of generating reference data for use therein, and apparatuses therefor
US5793471A (en) * 1995-07-07 1998-08-11 Canon Kabushiki Kaisha Projection exposure method and apparatus in which scanning exposure is performed in accordance with a shot layout of mask patterns
US5943551A (en) * 1997-09-04 1999-08-24 Texas Instruments Incorporated Apparatus and method for detecting defects on silicon dies on a silicon wafer
US5966677A (en) * 1997-02-28 1999-10-12 Fiekowsky; Peter J. High accuracy particle dimension measurement system
US20020001405A1 (en) * 2000-06-30 2002-01-03 Nidek Co., Ltd. Defect inspection method and defect inspection apparatus
US20020063792A1 (en) * 2000-04-21 2002-05-30 Robin Speed Interface and related methods facilitating motion compensation in media processing
US20020114506A1 (en) * 2001-02-22 2002-08-22 Takashi Hiroi Circuit pattern inspection method and apparatus
US6456899B1 (en) * 1999-12-07 2002-09-24 Ut-Battelle, Llc Context-based automated defect classification system using multiple morphological masks
US20020159101A1 (en) * 2001-04-25 2002-10-31 Timothy Alderson Scene-based non-uniformity correction for detector arrays
US20020188917A1 (en) * 2001-06-08 2002-12-12 Sumitomo Mitsubishi Silicon Corporation Defect inspection method and defect inspection apparatus
US6512843B1 (en) * 1998-10-28 2003-01-28 Tokyo Seimitsu Co., Ltd. Pattern comparison method and appearance inspection machine for performance comparison based on double detection without delay
US6529618B1 (en) * 1998-09-04 2003-03-04 Konica Corporation Radiation image processing apparatus
US6539106B1 (en) * 1999-01-08 2003-03-25 Applied Materials, Inc. Feature-based defect detection
US20030063792A1 (en) * 2001-09-28 2003-04-03 Takashi Hiroi Apparatus for inspecting a specimen
US6546120B1 (en) * 1997-07-02 2003-04-08 Matsushita Electric Industrial Co., Ltd. Correspondence-between-images detection method and system
US20040066962A1 (en) * 2002-10-08 2004-04-08 Dainippon Screen Mfg. Co., Ltd. Defect inspection apparatus, defect inspection method and program
US6768324B1 (en) * 1999-11-05 2004-07-27 Fab Solutions, Inc. Semiconductor device tester which measures information related to a structure of a sample in a depth direction
US6780574B2 (en) * 2000-03-02 2004-08-24 Canon Kabushiki Kaisha Multiple exposure method
US6840666B2 (en) * 2002-01-23 2005-01-11 Marena Systems Corporation Methods and systems employing infrared thermography for defect detection and analysis
US6879393B2 (en) * 2000-08-03 2005-04-12 Dai Nippon Printing Co., Ltd. Defect inspection apparatus for phase shift mask
US6883160B2 (en) * 2001-09-26 2005-04-19 Kabushiki Kaisha Toshiba Pattern inspection apparatus
US20050117796A1 (en) * 2003-11-28 2005-06-02 Shigeru Matsui Pattern defect inspection method and apparatus
US20060110009A1 (en) * 2004-11-22 2006-05-25 Xerox Corporation Systems and methods for detecting image quality defects
US20060159333A1 (en) * 2005-01-19 2006-07-20 Akio Ishikawa Image defect inspection method, image defect inspection apparatus, and appearance inspection apparatus
US7109483B2 (en) * 2000-11-17 2006-09-19 Ebara Corporation Method for inspecting substrate, substrate inspecting system and electron beam apparatus
US7113629B2 (en) * 2001-04-11 2006-09-26 Dainippon Screen Mfg. Co., Ltd. Pattern inspecting apparatus and method
US20070177787A1 (en) * 2006-01-20 2007-08-02 Shunji Maeda Fault inspection method
US7260256B2 (en) * 1996-09-17 2007-08-21 Renesas Technology Corporation Method and system for inspecting a pattern
US7330581B2 (en) * 2002-10-01 2008-02-12 Tokyo Seimitsu Co., Ltd. Image defect inspection method, image defect inspection apparatus and appearance inspection apparatus
US7408643B2 (en) * 2003-05-30 2008-08-05 Ebara Corporation Method and apparatus for inspecting samples, and method for manufacturing devices using method and apparatus for inspecting samples
US7423784B2 (en) * 2001-08-22 2008-09-09 Canon Kabushiki Kaisha Processing of signals from image sensing apparatus whose image sensing area includes a plurality of areas
US20090279775A1 (en) * 2006-09-13 2009-11-12 Yo Katagiri Method of inspecting mounting states of electronic components

Family Cites Families (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH03286383A (en) 1990-04-02 1991-12-17 Sumitomo Metal Ind Ltd Pattern comparing device and surface defect inspecting device
JPH04129241A (en) 1990-09-20 1992-04-30 Nec Corp Inspection device
JPH05218160A (en) 1992-01-31 1993-08-27 Sharp Corp Visual inspection equipment for semiconductor chip
JPH09178666A (en) 1995-10-24 1997-07-11 Nkk Corp Surface inspection device
JP3660763B2 (en) 1996-06-26 2005-06-15 株式会社日立製作所 Inspection pattern inspection method, manufacturing process diagnosis method, and semiconductor substrate manufacturing method
JP3409670B2 (en) 1997-11-28 2003-05-26 株式会社日立製作所 Appearance inspection method and apparatus
JP3878340B2 (en) 1998-09-18 2007-02-07 株式会社ルネサステクノロジ Pattern defect inspection method and apparatus
US6640308B1 (en) * 1999-04-16 2003-10-28 Invensys Systems, Inc. System and method of powering and communicating field ethernet device for an instrumentation and control using a single pair of powered ethernet wire
JP3091039U (en) 2002-06-27 2003-01-17 株式会社ブイ・テクノロジー Defect detection device based on 8-neighboring point adjacent comparison method in imaging inspection device
US7145439B2 (en) * 2003-10-16 2006-12-05 Powerdsine, Ltd. Powered device interface circuit
KR100648201B1 (en) * 2005-08-08 2006-11-23 삼성전자주식회사 Method of inspecting a substrate and apparatus for inspecting substrate using the same

Patent Citations (40)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5272536A (en) * 1990-03-13 1993-12-21 Sony Corporation Dark current and defective pixel correction apparatus
US5312779A (en) * 1992-05-26 1994-05-17 Texas Instruments Incorporated Color spatial light modulator and method of manufacture
US5574800A (en) * 1993-08-24 1996-11-12 Kabushiki Kaisha Toshiba Pattern defect inspection method and apparatus
US5638465A (en) * 1994-06-14 1997-06-10 Nippon Telegraph And Telephone Corporation Image inspection/recognition method, method of generating reference data for use therein, and apparatuses therefor
US5793471A (en) * 1995-07-07 1998-08-11 Canon Kabushiki Kaisha Projection exposure method and apparatus in which scanning exposure is performed in accordance with a shot layout of mask patterns
US7260256B2 (en) * 1996-09-17 2007-08-21 Renesas Technology Corporation Method and system for inspecting a pattern
US5966677A (en) * 1997-02-28 1999-10-12 Fiekowsky; Peter J. High accuracy particle dimension measurement system
US6546120B1 (en) * 1997-07-02 2003-04-08 Matsushita Electric Industrial Co., Ltd. Correspondence-between-images detection method and system
US5943551A (en) * 1997-09-04 1999-08-24 Texas Instruments Incorporated Apparatus and method for detecting defects on silicon dies on a silicon wafer
US6529618B1 (en) * 1998-09-04 2003-03-04 Konica Corporation Radiation image processing apparatus
US6512843B1 (en) * 1998-10-28 2003-01-28 Tokyo Seimitsu Co., Ltd. Pattern comparison method and appearance inspection machine for performance comparison based on double detection without delay
US6539106B1 (en) * 1999-01-08 2003-03-25 Applied Materials, Inc. Feature-based defect detection
US6768324B1 (en) * 1999-11-05 2004-07-27 Fab Solutions, Inc. Semiconductor device tester which measures information related to a structure of a sample in a depth direction
US6456899B1 (en) * 1999-12-07 2002-09-24 Ut-Battelle, Llc Context-based automated defect classification system using multiple morphological masks
US6780574B2 (en) * 2000-03-02 2004-08-24 Canon Kabushiki Kaisha Multiple exposure method
US20020063792A1 (en) * 2000-04-21 2002-05-30 Robin Speed Interface and related methods facilitating motion compensation in media processing
US20020001405A1 (en) * 2000-06-30 2002-01-03 Nidek Co., Ltd. Defect inspection method and defect inspection apparatus
US6928185B2 (en) * 2000-06-30 2005-08-09 Nidek Co., Ltd. Defect inspection method and defect inspection apparatus
US6879393B2 (en) * 2000-08-03 2005-04-12 Dai Nippon Printing Co., Ltd. Defect inspection apparatus for phase shift mask
US7109483B2 (en) * 2000-11-17 2006-09-19 Ebara Corporation Method for inspecting substrate, substrate inspecting system and electron beam apparatus
US20020114506A1 (en) * 2001-02-22 2002-08-22 Takashi Hiroi Circuit pattern inspection method and apparatus
US7113629B2 (en) * 2001-04-11 2006-09-26 Dainippon Screen Mfg. Co., Ltd. Pattern inspecting apparatus and method
US20020159101A1 (en) * 2001-04-25 2002-10-31 Timothy Alderson Scene-based non-uniformity correction for detector arrays
US20020188917A1 (en) * 2001-06-08 2002-12-12 Sumitomo Mitsubishi Silicon Corporation Defect inspection method and defect inspection apparatus
US6779159B2 (en) * 2001-06-08 2004-08-17 Sumitomo Mitsubishi Silicon Corporation Defect inspection method and defect inspection apparatus
US7423784B2 (en) * 2001-08-22 2008-09-09 Canon Kabushiki Kaisha Processing of signals from image sensing apparatus whose image sensing area includes a plurality of areas
US6883160B2 (en) * 2001-09-26 2005-04-19 Kabushiki Kaisha Toshiba Pattern inspection apparatus
US20030063792A1 (en) * 2001-09-28 2003-04-03 Takashi Hiroi Apparatus for inspecting a specimen
US6840666B2 (en) * 2002-01-23 2005-01-11 Marena Systems Corporation Methods and systems employing infrared thermography for defect detection and analysis
US7149343B2 (en) * 2002-01-23 2006-12-12 Marena Systems Corporation Methods for analyzing defect artifacts to precisely locate corresponding defects
US7330581B2 (en) * 2002-10-01 2008-02-12 Tokyo Seimitsu Co., Ltd. Image defect inspection method, image defect inspection apparatus and appearance inspection apparatus
US20040066962A1 (en) * 2002-10-08 2004-04-08 Dainippon Screen Mfg. Co., Ltd. Defect inspection apparatus, defect inspection method and program
US7408643B2 (en) * 2003-05-30 2008-08-05 Ebara Corporation Method and apparatus for inspecting samples, and method for manufacturing devices using method and apparatus for inspecting samples
US20050117796A1 (en) * 2003-11-28 2005-06-02 Shigeru Matsui Pattern defect inspection method and apparatus
US7457455B2 (en) * 2003-11-28 2008-11-25 Hitachi High-Technologies Corporation Pattern defect inspection method and apparatus
US20060110009A1 (en) * 2004-11-22 2006-05-25 Xerox Corporation Systems and methods for detecting image quality defects
US20060159333A1 (en) * 2005-01-19 2006-07-20 Akio Ishikawa Image defect inspection method, image defect inspection apparatus, and appearance inspection apparatus
US7346207B2 (en) * 2005-01-19 2008-03-18 Tokyo Seimitsu Co., Ltd. Image defect inspection method, image defect inspection apparatus, and appearance inspection apparatus
US20070177787A1 (en) * 2006-01-20 2007-08-02 Shunji Maeda Fault inspection method
US20090279775A1 (en) * 2006-09-13 2009-11-12 Yo Katagiri Method of inspecting mounting states of electronic components

Cited By (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20120070089A1 (en) * 2009-05-29 2012-03-22 Yukari Yamada Method of manufacturing a template matching template, as well as a device for manufacturing a template
US8929665B2 (en) * 2009-05-29 2015-01-06 Hitachi High-Technologies Corporation Method of manufacturing a template matching template, as well as a device for manufacturing a template
US20130322737A1 (en) * 2012-05-30 2013-12-05 Hitachi High-Technologies Corporation Defect inspection method and defect inspection apparatus
US8953868B2 (en) * 2012-05-30 2015-02-10 Hitachi High-Technologies Corporation Defect inspection method and defect inspection apparatus
US9766186B2 (en) 2014-08-27 2017-09-19 Kla-Tencor Corp. Array mode repeater detection
US9766187B2 (en) 2014-08-27 2017-09-19 Kla-Tencor Corp. Repeater detection
US20170309007A1 (en) * 2016-04-22 2017-10-26 Kla-Tencor Corporation System, method and computer program product for correcting a difference image generated from a comparison of target and reference dies
US9984454B2 (en) * 2016-04-22 2018-05-29 Kla-Tencor Corporation System, method and computer program product for correcting a difference image generated from a comparison of target and reference dies
WO2018089459A1 (en) * 2016-11-10 2018-05-17 Kla-Tencor Corporation High sensitivity repeater defect detection
US10395358B2 (en) 2016-11-10 2019-08-27 Kla-Tencor Corp. High sensitivity repeater defect detection
CN109060841A (en) * 2018-08-11 2018-12-21 珠海宝利通耗材有限公司 Printer cartridge image quality method of determination and evaluation and system
CN109585323A (en) * 2018-11-27 2019-04-05 德淮半导体有限公司 Test scan method

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