JP2014232071A - Pattern inspection method and pattern inspection device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an inspection method that enables suppression of an unwanted increase in the number of defects.SOLUTION: A pattern inspection method according to an embodiment of the present invention comprises the steps of: using an optical image and a design image to compute a reaction value for defect determination by a prescribed algorithm for each pixel; generating a reaction value map with the reaction value of each pixel as a map value; specifying a peak position of the reaction values in a defect candidate area where a group of a plurality of reaction values equal to or more than a defect candidate threshold value to identify defect candidates is defined, using the reaction map; and inputting sensitivity area information in which a plurality of sensitivity areas corresponding to any of a plurality of different determination threshold values are defined, using a determination threshold value corresponding to the sensitivity area to which the peak position belongs in the defect candidate area from the plurality of sensitivity areas, to perform a defect determination as to each of the reaction values of the defect candidate area.

Description

  The present invention relates to a pattern inspection method and a pattern inspection apparatus. For example, the present invention relates to an inspection apparatus and method for inspecting a pattern by acquiring an optical image of a pattern image by irradiating a laser beam.

  In recent years, the circuit line width required for a semiconductor element has been increasingly narrowed as a large scale integrated circuit (LSI) is highly integrated and has a large capacity. These semiconductor elements use an original pattern pattern (also referred to as a mask or a reticle, hereinafter referred to as a mask) on which a circuit pattern is formed, and the pattern is exposed and transferred onto a wafer by a reduction projection exposure apparatus called a stepper. It is manufactured by forming a circuit. Therefore, a pattern drawing apparatus using an electron beam capable of drawing a fine circuit pattern is used for manufacturing a mask for transferring such a fine circuit pattern onto a wafer. A pattern circuit may be directly drawn on a wafer using such a pattern drawing apparatus. Alternatively, development of a laser beam drawing apparatus for drawing using a laser beam in addition to an electron beam has been attempted.

  In addition, improvement in yield is indispensable for manufacturing an LSI that requires a large amount of manufacturing cost. However, as represented by a 1 gigabit class DRAM (Random Access Memory), the pattern constituting the LSI is about to be in the order of submicron to nanometer. One of the major factors that reduce the yield is a pattern defect of a mask used when an ultrafine pattern is exposed and transferred onto a semiconductor wafer by a photolithography technique. In recent years, with the miniaturization of LSI pattern dimensions formed on semiconductor wafers, the dimensions that must be detected as pattern defects have become extremely small. Therefore, it is necessary to improve the accuracy of a pattern inspection apparatus that inspects defects in a transfer mask used in LSI manufacturing.

  On the other hand, with the development of multimedia, LCDs (Liquid Crystal Display) are increasing in size of the liquid crystal substrate to 500 mm × 600 mm or more, and TFTs (Thin Film Transistors) formed on the liquid crystal substrate. : Thin film transistors) and the like are being miniaturized. Therefore, it is required to inspect a very small pattern defect over a wide range. For this reason, it has become an urgent task to develop a pattern inspection apparatus for efficiently inspecting defects of a photomask used in manufacturing such a large area LCD pattern and a large area LCD in a short time.

  As an inspection method, an optical image obtained by imaging a pattern formed on a sample such as a lithography mask using a magnifying optical system at a predetermined magnification is compared with an optical image obtained by imaging design data or the same pattern on the sample. A method of performing an inspection by doing this is known. For example, as a pattern inspection method, “die to die inspection” in which optical image data obtained by imaging the same pattern at different locations on the same mask is compared, or a pattern is formed using CAD data with a pattern design as a mask. Drawing data (design pattern data) converted into a device input format for the drawing device to input at the time of drawing is input to the inspection device, design image data (reference image) is generated based on this, and the pattern and the pattern are generated. There is a “die to database (die-database) inspection” that compares an optical image that is captured measurement data. In the inspection method in such an inspection apparatus, the sample is placed on the stage, and the stage is moved so that the light beam scans on the sample and the inspection is performed. The sample is irradiated with a light beam by a light source and an illumination optical system. The light transmitted or reflected by the sample is imaged on the sensor via the optical system. The image picked up by the sensor is sent to the comparison circuit as measurement data. In the comparison circuit, after the images are aligned, the measurement data and the reference data are compared according to an appropriate algorithm, and if the response value of the algorithm is outside the threshold value, it is determined that there is a pattern defect.

  By taking area sensitivity information such as a design intent into the inspection apparatus, the defect determination threshold in the inspection area can be made variable. However, when there is a defect in the area that you want to reduce the sensitivity of, the pixel that has become higher due to the influence of the defect, the defect judgment response value by the set algorithm will straddle the normal area or the area that you want to increase the sensitivity Occurs. In such a case, the pixel in the portion extending over the normal region is determined to be defective with the threshold of the normal region, or the pixel in the portion extending over the region to be increased in sensitivity is determined with a strict threshold for the increased sensitivity region. For this reason, there is a problem that even a defect that does not need to be detected is detected, leading to an unnecessary increase in the number of defects.

  Here, a technique for determining a defect with the strictest tolerance when a defect extends over a plurality of areas is disclosed (for example, see Patent Document 1). However, with such an inspection apparatus, it is difficult to prevent an unnecessary increase in the number of defects.

JP 2006-170922 A

  Accordingly, an object of the present invention is to provide an inspection apparatus and method capable of overcoming such problems and suppressing an unnecessary increase in the number of defects.

The pattern inspection method of one embodiment of the present invention includes:
Acquiring an optical image of the patterned sample to be inspected;
A step of generating a design image based on a design pattern that is a basis for pattern formation of a sample to be inspected;
A step of calculating a reaction value for defect determination by a predetermined algorithm for each pixel using the optical image and the design image;
Creating a reaction value map using the reaction value of each pixel as a map value;
Identifying a reaction value peak position in a defect candidate region in which a plurality of reaction values of a group equal to or higher than a defect candidate threshold for identifying a defect candidate are defined using a reaction value map;
Input sensitivity region information in which a plurality of sensitivity regions corresponding to any of a plurality of different determination threshold values are defined, and determine a determination threshold value corresponding to the sensitivity region to which the peak position in the defect candidate region belongs from among the plurality of sensitivity regions. And using the defect determination for each reaction value of the defect candidate region,
It is provided with.

  In addition, when the peak position extends over two or more sensitivity regions of the plurality of sensitivity regions, the weakest determination threshold value among the plurality of determination threshold values corresponding to the two or more sensitivity regions straddled is used to determine the defect candidate region. It is preferable to perform defect determination for each reaction value.

  In addition, when a plurality of peak positions are specified in the defect candidate area and the plurality of peak positions belong to a plurality of different sensitivity areas, the loosest of the plurality of determination thresholds corresponding to the plurality of sensitivity areas to which the plurality of peak positions belong. It is preferable to perform defect determination for each reaction value in the defect candidate region using the determination threshold.

The pattern inspection apparatus according to one aspect of the present invention includes:
An optical image acquisition unit for acquiring an optical image of the patterned sample to be inspected;
A design image data generation unit that generates a design image based on a design pattern that is a basis for pattern formation of the sample to be inspected;
A reaction value calculation unit that calculates a reaction value for defect determination by a predetermined algorithm for each pixel using the optical image and the design image;
A reaction value map creating unit for creating a reaction value map, in which the reaction value of each pixel is a map value;
Using a reaction value map, a peak position specifying unit for specifying a peak position of a reaction value in a defect candidate region in which a plurality of reaction values of a group equal to or higher than a defect candidate threshold for identifying a defect candidate is defined;
Input sensitivity region information in which a plurality of sensitivity regions corresponding to one of a plurality of different determination threshold values are defined, and a determination threshold value corresponding to the sensitivity region to which the peak position in the defect candidate region belongs is selected from the plurality of sensitivity regions. A determination unit that performs defect determination for each reaction value in the defect candidate region,
It is provided with.

  In addition, when the peak position spans two or more sensitivity regions among the plurality of sensitivity regions, the determination unit uses the loosest determination threshold value among the plurality of determination threshold values corresponding to the two or more sensitivity regions straddled, It is preferable to perform defect determination for each reaction value in the defect candidate region.

  ADVANTAGE OF THE INVENTION According to this invention, it can prevent detecting the defect which exists in the area | region which wants to make it low sensitivity with threshold values, such as high sensitivity. Therefore, an unnecessary increase in the number of defects can be suppressed.

1 is a configuration diagram illustrating a configuration of a pattern inspection apparatus according to a first embodiment. 3 is a diagram illustrating an internal configuration of a comparison circuit in the first embodiment. FIG. FIG. 3 is a flowchart showing main steps of the inspection method according to Embodiment 1. FIG. 3 is a conceptual diagram for explaining a pattern on a sample and a scan area in the first embodiment. 6 is a diagram illustrating an example of sensitivity area information configured with text data in Embodiment 1. FIG. FIG. 6 is a flowchart showing an internal process of a sensitivity region data creation process in the first embodiment. 6 is a conceptual diagram illustrating an example of a reference image, a frame image, and a reaction value map according to Embodiment 1. FIG. 3 is a conceptual diagram illustrating an example of a frame image, a reaction value map, and a sensitivity region in Embodiment 1. FIG. FIG. 6 is a conceptual diagram illustrating another example of a reaction value map and a sensitivity region in the first embodiment. FIG. 6 is a conceptual diagram illustrating another example of a reaction value map and a sensitivity region in the first embodiment.

Embodiment 1 FIG.
FIG. 1 is a configuration diagram showing the configuration of the pattern inspection apparatus according to the first embodiment. In FIG. 1, an inspection apparatus 100 for inspecting a defect of a pattern formed on a sample, for example, a mask, includes an optical image acquisition unit 150 and a control system circuit 160 (control unit).

  The optical image acquisition unit 150 includes a light source 103, an illumination optical system 170, a movable XYθ table 102, a magnifying optical system 104, and a photodiode array 105 (an example of a sensor), a sensor circuit 106, a stripe pattern memory 123, And a laser measuring system 122. A sample 101 is arranged on the XYθ table 102. Examples of the sample 101 include a photomask for exposure that transfers a pattern to a wafer. The photomask is formed with a pattern composed of a plurality of figures to be inspected. For example, the sample 101 is arranged on the XYθ table 102 with the pattern formation surface facing downward.

  In the control system circuit 160, the control computer 110 serving as a computer transmits a position circuit 107, a comparison circuit 108, a development circuit 111, a reference circuit 112, a region management circuit 140, an autoloader control circuit 113, and a table control circuit 114 via the bus 120. , A magnetic disk device 109, a magnetic tape device 115, a flexible disk device (FD) 116, a CRT 117, a pattern monitor 118, and a printer 119. The sensor circuit 106 is connected to the stripe pattern memory 123, and the stripe pattern memory 123 is connected to the comparison circuit 108. The XYθ table 102 is driven by an X-axis motor, a Y-axis motor, and a θ-axis motor. The XYθ table 102 is an example of a stage.

  In the inspection apparatus 100, the light source 103, the XYθ table 102, the illumination optical system 170, the magnifying optical system 104, the photodiode array 105, and the sensor circuit 106 constitute a high magnification inspection optical system. The XYθ table 102 is driven by the table control circuit 114 under the control of the control computer 110. It can be moved by a drive system such as a three-axis (XY-θ) motor that drives in the X, Y, and θ directions. For example, step motors can be used as these X motor, Y motor, and θ motor. The XYθ table 102 can be moved in the horizontal direction and the rotation direction by a motor of each axis of XYθ. The movement position of the XYθ table 102 is measured by the laser length measurement system 122 and supplied to the position circuit 107.

  Here, FIG. 1 shows components necessary for explaining the first embodiment. It goes without saying that the inspection apparatus 100 may normally include other necessary configurations.

  FIG. 2 is a diagram illustrating an internal configuration of the comparison circuit according to the first embodiment. In FIG. 2, in the comparison circuit 108, memories 50, 52, 54, 58, 66, a frame division unit 56, an alignment unit 60, a reaction value calculation unit 62, a reaction value map creation unit 64, and a peak position specification unit 68. , And a defect determination unit 70 are arranged. The functions such as the frame division unit 56, the alignment unit 60, the reaction value calculation unit 62, the reaction value map creation unit 64, the peak position specification unit 68, and the defect determination unit 70 may be configured by software such as a program. Alternatively, it may be configured by hardware such as an electronic circuit. Alternatively, a combination thereof may be used. Necessary input data or calculation results in the comparison circuit 108 are stored in the memories 50, 52, 54, 58, 66 or a memory (not shown) each time.

  FIG. 3 is a flowchart showing main steps of the inspection method according to the first embodiment. 4, the inspection method according to the first embodiment includes an optical image acquisition step (S102), a reference image creation step (S104), a sensitivity region data creation step (S106), a frame division step (S108), a position A series of steps of a matching step (S110), a reaction value calculation step (S112), a reaction value map creation step (S113), a peak position identification step (S114), and a defect determination step (S116) are performed. .

  As the optical image acquisition step (S102), the optical image acquisition unit 150 acquires an optical image of the sample 101 to be inspected. Specifically, it operates as follows.

  The pattern formed on the sample 101 is irradiated with laser light (for example, DUV light) having a wavelength equal to or less than the ultraviolet region, which serves as inspection light, from the appropriate light source 103 via the illumination optical system 170. The light that has passed through the sample 101 is formed as an optical image on the photodiode array 105 (an example of a sensor) through the magnifying optical system 104 and is incident thereon. As the photodiode array 105, for example, a TDI (Time Delay Integration) sensor or the like is preferably used.

  FIG. 4 is a conceptual diagram for explaining the pattern on the sample and the scan area in the first embodiment. In FIG. 4, the inspection area 10 (entire inspection area) of the sample 101 is, as shown in FIG. 4, for example, for each of a plurality of strip-shaped inspection stripes 20 (an example of stripe areas) having a scan width W in the Y direction. The optical image is picked up by scanning (scanning). As described above, the inspection apparatus 100 acquires an image (stripe region image) for each inspection stripe 20. For each of the inspection stripes 20, an image of a graphic pattern arranged in the stripe region is taken in the longitudinal direction (X direction) of the stripe region using laser light. As the XYθ table 102 moves, the photodiode array 105 relatively continuously moves in the X direction, and an optical image is acquired. The photodiode array 105 continuously captures optical images having a scan width W as shown in FIG. In other words, the photodiode array 105 as an example of the sensor captures an optical image of the pattern formed on the sample 101 using the inspection light while moving relative to the XYθ table 102 (stage). In the first embodiment, after taking an optical image in one inspection stripe 20, the optical image having the scan width W is similarly moved while moving in the Y direction to the position of the next inspection stripe 20 and moving in the opposite direction. Take images continuously. That is, imaging is repeated in a forward (FWD) -backforward (BWD) direction in the opposite direction on the forward path and the backward path.

  Here, the imaging direction is not limited to repeating forward (FWD) -backforward (BWD). You may image from one direction. For example, FWD-FWD may be repeated. Alternatively, BWD-BWD may be repeated.

  The pattern image formed on the photodiode array 105 is photoelectrically converted by each light receiving element of the photodiode array 105, and further A / D (analog / digital) converted by the sensor circuit 106. Pixel data is stored in the stripe pattern memory 123 for each inspection stripe. When capturing such image data (striped region image), the dynamic range of the photodiode array 105 is a dynamic range having a maximum gradation when the amount of illumination light is 100% incident. Thereafter, the pixel data of the stripe region image is sent to the comparison circuit 108 together with data indicating the position of the sample 101 on the XYθ table 102 output from the position circuit 107. The measurement data of each pixel of the stripe region image is, for example, 8-bit unsigned data, and expresses the brightness gradation (light quantity) of each pixel. The stripe image data output in the comparison circuit 108 is stored in the memory 50.

  As a reference image creation step (S104), an example of a design image data generation unit such as the development circuit 111 and the reference circuit 112 generates a design image based on a design pattern that is a basis for pattern formation of the sample 101 to be inspected. First, the development circuit 111 reads design pattern information from the magnetic disk device 109 through the control computer 110, and displays the design pattern as design graphic data of the sample 101 to be inspected as a binary or multivalued image. The image data is converted into data (design image data), and the image data is sent to the reference circuit 112.

Here, the figure included in the design pattern is a basic figure of a rectangle or a triangle. For example, the coordinates (x, y) at the reference position of the figure, the length of the side, and the figure type such as a rectangle or a triangle are distinguished. The graphic data defining the shape, size, position, etc. of each pattern graphic is stored with information such as a graphic code as an identifier.
When a design pattern as such graphic data is input to the expansion circuit 111, it is expanded to data for each graphic, and a graphic code, a graphic dimension, and the like indicating the graphic shape of the graphic data are interpreted. Then, binary or multivalued design image data is developed as a pattern arranged in a grid having a grid with a predetermined quantization size as a unit. In other words, the design pattern information is read and the occupancy ratio of the figure in the design pattern is calculated for each cell formed by virtually dividing the inspection area as a cell with a predetermined dimension as a unit, and the n-bit occupancy rate is calculated. Output data. For example, it is preferable to set one square as one pixel. If a resolution of 1/2 ⁸ (= 1/256) is given to one pixel, 1/256 small areas are allocated by the figure area arranged in the pixel, and the occupation ratio in the pixel is set. Calculate. Then, it is output to the reference circuit 112 as 8-bit occupancy data for each pixel.

  The reference circuit 112 performs an appropriate filtering process on the design image data which is the image data of the sent graphic. The measurement data as an optical image obtained from the sensor circuit 106 is in a state in which the filter is activated by the resolution characteristic of the magnifying optical system 104, the aperture effect of the photodiode array 105, or the like, in other words, in an analog state that continuously changes. By applying the filter process to the design image data which is the image data on the design side where the image intensity (the gray value) is a digital value, it can be matched with the measurement data. In this way, a reference image (design image) to be compared with the optical image (frame image) is created. For example, a reference image of 512 × 512 pixels is generated. The reference image is output to the comparison circuit 108 and stored in the memory 52.

  Here, first, prior to the inspection, area information defining a plurality of sensitivity areas corresponding to any of a plurality of different determination threshold values is input from the outside and stored in the magnetic disk device 109 or the like. As the area information, for example, text data and graphic pattern data can be used.

  FIG. 5 is a diagram illustrating an example of sensitivity region information configured by text data in the first embodiment. In FIG. 5, area information 46 shows an example of sensitivity area information composed of text data. In the area information 46, positions of areas such as a cell area, a lead line area, a power supply area, a dummy fill area,... Are defined as text data. Of these regions, for example, the cell region is a high sensitivity determination region. The other areas are low sensitivity determination areas. For the cell area, an arrangement period such as a cell number such as cell area 1 and cell area 2, x and y coordinates, x and y size, and x and y pitch is defined. For the lead line area, power supply area, dummy fill area, and the like, area information such as x, y coordinates, x, y size (length) is defined.

  Further, the area information composed of graphic pattern data is defined by, for example, rectangular graphic pattern data. In the graphic pattern data, a graphic code indicating the type of graphic, for example, coordinates of a reference point such as a lower left corner of a rectangle, and x and y sizes of the graphic are defined.

  In the sensitivity region data creation step (S106), sensitivity region data is created using region information in which a plurality of sensitivity regions corresponding to any of a plurality of different determination thresholds are defined.

  FIG. 6 is a flowchart showing an internal process of the sensitivity region data creation process in the first embodiment. In FIG. 6, the sensitivity region data creation step (S106) executes at least one of a text interpretation step (S302) and a pattern development step (S304). The inspection apparatus 100 is configured to be able to handle both the area information composed of the text data and the area information composed of the graphic pattern data in order to create the sensitivity area data. When the input area information is text data, a text interpretation step (S302) is performed. If the input area information is graphic pattern data, a pattern development step (S304) is performed. Therefore, the sensitivity area data may be created in accordance with the data format of the input area information. However, the present invention is not limited to this, and only one of the text interpretation process (S302) and the pattern development process (S304) may be implemented.

  First, when the input area information is text data, the area information composed of the text data is input from the outside of the inspection apparatus 100 and stored in the magnetic disk device 109, for example.

  In the text interpretation step (S302), the area management circuit 140 reads, for example, area information composed of text data from the magnetic disk device 109, and interprets the contents of the text data. Then, the area management circuit 140 acquires the position coordinates (x, y) and size of the cell area that becomes the high sensitivity area from the text data. If the cell area is arranged in an array, the position coordinates (x, y) and size of the first cell 1, the position coordinates (x, y) and size of the last cell 2, and the x and y pitch are acquired. . Similarly, the area management circuit 140 acquires the position coordinates (x, y) and size of the lead line area, power supply area, and / or dummy fill area, which are low sensitivity determination areas, from the text data. . Sensitivity area data (an example of sensitivity area information) is created using data for specifying an area such as coordinates and size and identifier data for identifying whether the area is a high sensitivity area or a low sensitivity area. The created sensitivity area data is output to the comparison circuit 108 and stored in the memory 54.

  Alternatively, when the input area information is graphic pattern data, the area information composed of the graphic pattern data is input from the outside of the inspection apparatus 100 and stored in the magnetic disk device 109, for example.

  As a pattern development step (S304), the development circuit 111 reads area information composed of graphic pattern data from the magnetic disk device 109 through the control computer 110. Then, the read graphic pattern data is subjected to pattern development and converted into binary or multi-value image data to create area image data (sensitivity area image). The area image data is created as, for example, 8-bit unsigned data, and expresses the brightness gradation (light quantity) of each pixel. For example, it is only necessary to identify whether the position of the pixel is a high sensitivity region or a low sensitivity region based on the gradation value (or range) of each pixel. Alternatively, for example, an identifier for identifying a high sensitivity region or a low sensitivity region may be defined in 8-bit unsigned data. Area image data (an example of sensitivity area information) is output to the comparison circuit 108 and stored in the memory 54.

  In the frame dividing step (S108), the frame dividing unit 56 reads the stripe image from the memory 50, and divides the stripe area image into a plurality of frame images with a predetermined size in the x direction (for example, the same width as the scan width W). To do. For example, the image is divided into 512 × 512 pixel frame images. The plurality of divided frame images are stored in the memory 58.

  As the alignment step (S110), the alignment unit 60 performs alignment between the frame image and the corresponding reference image. It is preferable to perform high-precision alignment using a pattern after rough alignment of the image frame. For example, alignment is performed in units of subpixels.

  As the reaction value calculation step (S112), the reaction value calculation unit 62 calculates a reaction value for defect determination by a predetermined algorithm for each pixel using the frame image (optical image) and the reference image (design image). To do. For example, the reaction value is calculated using the target pixel of the frame image (optical image) and the reference image (design image) and the pixel values of a plurality of pixels around the target pixel. For example, when the inclination of the pattern edge (end) estimated from a plurality of continuous pixels in the frame image (optical image) changes greatly with respect to the corresponding portion of the reference image (design image), the reaction value is increased. It is preferable to do so. What is necessary is just to set an algorithm suitably.

  In the reaction value map creation step (S113), the reaction value map creation unit 64 creates a reaction value map using the calculated reaction values for each pixel as map values. The created reaction value map is stored in the memory 66.

  FIG. 7 is a conceptual diagram illustrating an example of a reference image, a frame image, and a reaction value map in the first embodiment. FIG. 7A shows an example of the reference image pattern 34. FIG. 7B shows an example of a frame image pattern 32 (sensor image) at a position corresponding to the reference image of FIG. The meshes shown in FIG. 7A and FIG. 7B show each pixel 30. FIG. 7C shows a reaction value map obtained using such a frame image and a reference image. A defect portion 36 exists in the pattern 32 of the frame image. When calculating the defect reaction value of the target pixel, when using an algorithm that also considers the influence of the surrounding pixels, not only the pixel of the defective portion 36 (◯), but also the defect reaction values of the surrounding pixels from the defective portion 36 are used. Affected by. Therefore, also in the reaction value map shown in FIG. 7C, the defect reaction values of the defective portion 36 (◯ mark) and the surrounding pixels are high.

  FIG. 8 is a conceptual diagram illustrating an example of a frame image, a reaction value map, and a sensitivity region in the first embodiment. FIG. 8B shows an example of a frame image pattern 32 (sensor image). The mesh shown in FIG. 8B shows each pixel 30. FIG. 8B shows a case where the low sensitivity region 40 and the high sensitivity region 42 exist in the frame image. In the example of FIG. 8B, the case where the pattern 32 is located in the low sensitivity region 40 is shown. Therefore, in the example of FIG. 8B, the defective portion 36 is also located in the low sensitivity region 40. However, as shown in FIG. 8A, in the reaction value map, a region having a high reaction value is generated so as to straddle the high sensitivity region 42 in addition to the pixels of the defective portion 36 in the low sensitivity region 40. . Therefore, if it is simply determined whether or not it is a defect based on the determination threshold value of the sensitivity region in which the target pixel is located, the pixel in the high sensitivity region 42 in which the reaction value is high due to the defect portion 36 in the low sensitivity region 40. Is determined by a highly sensitive determination threshold (strict threshold). In that case, if the determination threshold is low (a loose threshold), the defect may be determined even if the defect is not determined. As a result, there arises a problem that the number of defects is unnecessarily increased. Therefore, in the first embodiment, the peak position of the pixel group affected by the defective portion is specified, and the determination threshold is selected based on the peak position.

  As the peak position specifying step (S114), the peak position specifying unit 68 uses the reaction value map to determine the reaction value in the defect candidate region in which a plurality of reaction values of a group equal to or higher than the defect candidate threshold value for identifying the defect candidate are defined. Specify the peak position. Specifically, a contour line corresponding to the value of the reaction value is virtually defined in the reaction value map. For example, in the example of FIG. 8A, with the maximum response value 70 as a peak, 60 reaction value pixels are adjacent to each other, and 50 reaction value pixels are located around the pixel. For example, when the defect candidate threshold value is set to 50, the defect candidate area 44 defined by a group of reaction values of 50 or more can be specified. The peak position specifying unit 68 specifies the pixel position 48 (peak position) indicating the peak of the reaction value in the defect candidate region 44. In the example of FIG. 8A, the position of the pixel showing the maximum reaction value 70 is specified as the peak position 48.

  As the defect determination step (S116), the defect determination unit 70 (an example of a determination unit) reads out sensitivity region data in which a plurality of sensitivity regions corresponding to any of a plurality of different determination threshold values are defined from the memory 54 (input). Thus, defect determination is performed for each reaction value in the defect candidate region 44 using a determination threshold corresponding to the sensitivity region to which the peak position 48 in the defect candidate region 44 belongs among the plurality of sensitivity regions. In the example of FIG. 8A, since the sensitivity region to which the peak position 46 belongs is the low sensitivity region 40, each pixel in the defect candidate region 44 is determined using a determination threshold corresponding to the low sensitivity region 40. The reaction value of is determined. As described above, even when the pixels of the defect candidate region 44 extend over the high sensitivity region 42, each pixel of the defect candidate region 44 in the high sensitivity region 42 can be determined as a defect with the determination threshold corresponding to the low sensitivity region 40. . Therefore, it is possible to determine the defect with the determination threshold corresponding to the low sensitivity region 40 for the pixel in the high sensitivity region 42 in which the reaction value is high due to the defect portion 36 in the low sensitivity region 40. Therefore, an unnecessary increase in the number of defects can be suppressed or reduced.

  FIG. 9 is a conceptual diagram showing another example of the reaction value map and the sensitivity region in the first embodiment. As shown in FIG. 9, the peak position 48 may straddle two sensitivity regions, a low sensitivity region 40 and a high sensitivity region 42. In the example of FIG. 9, the case of straddling two sensitivity regions is shown, but the present invention is not limited to this. It may be a case where three or more sensitivity regions are straddled. As described above, when the peak position 48 extends over two or more sensitivity regions among the plurality of sensitivity regions, the defect determination unit 70 determines the loosest determination among the plurality of determination threshold values corresponding to the two or more sensitivity regions straddled. Defect determination is performed for each reaction value in the defect candidate region 44 using the threshold value. Thereby, an unnecessary increase in the number of defects can be suppressed or reduced.

  FIG. 10 is a conceptual diagram showing another example of the reaction value map and the sensitivity region in the first embodiment. As shown in FIG. 10, a plurality of peak positions 48a and 48b are specified in the defect candidate area 44, and the plurality of peak positions 48a and 48b may belong to a plurality of different sensitivity areas. In the example of FIG. 10, the peak position 48 a is located in the high sensitivity region 42 and the peak position 48 b is located in the low sensitivity region 40. Such a phenomenon occurs depending on the contents of the algorithm. For example, even though the defective portion extends over a plurality of pixels and the direction of the pattern edge at the end of the defective portion is greatly different from the direction of the pattern edge of the corresponding portion of the reference image, the central portion of the defective portion In this case, the direction of the pattern edge is the same as the direction of the pattern edge of the corresponding part of the reference image. In such a case, the defect determination unit 70 uses the loosest determination threshold value among the plurality of determination threshold values corresponding to the plurality of sensitivity regions to which the plurality of peak positions 48a and 48b belong, and uses the weakest determination threshold value for each reaction value in the defect candidate region 44. Make a decision. Thereby, an unnecessary increase in the number of defects can be suppressed or reduced.

  As described above, the defect determination unit 70 determines a defect for each pixel in the aligned frame image (optical image) and reference image (design image). Then, the determined result is output. The determination result is displayed on the pattern monitor 118, for example. Alternatively, it is output from the printer 119. Alternatively, it may be output to the outside by other means.

  As described above, according to the first embodiment, it is possible to prevent a defect present in a region where sensitivity is desired to be detected with a threshold such as high sensitivity. Therefore, an unnecessary increase in the number of defects can be suppressed. As a result, the reliability of pattern inspection and the yield can be improved.

  In the above description, what is described as “˜circuit” or “˜process” can be configured by hardware such as an electronic circuit. Alternatively, it can be configured by a program operable by a computer. Or you may make it implement by not only the program used as software but the combination of hardware and software. Alternatively, a combination with firmware may be used. When configured by a program, the program is recorded on a recording medium such as a magnetic disk device, a magnetic tape device, an FD, or a ROM (Read Only Memory). For example, the table control circuit 114, the expansion circuit 111, the reference circuit 112, the area management circuit 140, the comparison circuit 108, and the like that constitute the arithmetic control unit may be configured by electrical circuits or processed by the control computer 110. It may be realized as software that can. Moreover, you may implement | achieve with the combination of an electrical circuit and software.

  The embodiments have been described above with reference to specific examples. However, the present invention is not limited to these specific examples. For example, in the embodiment, a transmission illumination optical system using transmitted light is shown as the illumination optical system 170, but the present invention is not limited to this. For example, a reflective illumination optical system using reflected light may be used. Alternatively, the transmitted light and the reflected light may be used simultaneously by combining the transmitted illumination optical system and the reflected illumination optical system. In the embodiment, the die-database inspection is performed to compare the measurement data and the reference image created from the design data, but the present invention is not limited to this. The present invention is also suitable when performing die-to-die inspection for comparing measured data. In the above-described example, the high sensitivity region and the low sensitivity region are described as examples. However, it goes without saying that other sensitivity regions such as an intermediate sensitivity region may exist.

  In addition, although descriptions are omitted for parts and the like that are not directly required for the description of the present invention, such as a device configuration and a control method, a required device configuration and a control method can be appropriately selected and used. For example, although the description of the configuration of the control unit that controls the inspection apparatus 100 is omitted, it goes without saying that the required control unit configuration is appropriately selected and used.

  In addition, all pattern inspection apparatuses and pattern inspection methods that include elements of the present invention and that can be appropriately modified by those skilled in the art are included in the scope of the present invention.

10 inspection area 20 inspection stripe 30 pixel 32, 34 pattern 40 low sensitivity area 42 high sensitivity area 44 defect candidate area 46 area information 48 peak position 50, 52, 54, 58, 66 memory 56 frame division section 60 alignment section 62 reaction Value calculation unit 64 Reaction value map creation unit 68 Peak position specification unit 70 Defect determination unit 100 Inspection device 101 Sample 102 XYθ table 103 Light source 104 Magnifying optical system 105 Photodiode array 106 Sensor circuit 107 Position circuit 108 Comparison circuit 109 Magnetic disk device 110 Control computer 111 Expansion circuit 112 Reference circuit 113 Autoloader control circuit 114 Table control circuit 115 Magnetic tape device 116 FD
117 CRT
118 Pattern Monitor 119 Printer 120 Bus 122 Laser Length Measuring System 123 Stripe Pattern Memory 140 Area Management Circuit 150 Optical Image Acquisition Unit 160 Control System Circuit 170 Illumination Optical System

Claims (5)

Acquiring an optical image of the patterned sample to be inspected;
Generating a design image based on a design pattern serving as a basis for pattern formation of the sample to be inspected;
Using the optical image and the design image, calculating a reaction value for defect determination by a predetermined algorithm for each pixel;
Creating a reaction value map using the reaction value of each pixel as a map value;
Identifying a peak position of a reaction value in a defect candidate region in which a plurality of reaction values of a group equal to or higher than a defect candidate threshold for identifying a defect candidate is defined using the reaction value map;
Sensitivity area information in which a plurality of sensitivity areas corresponding to any one of a plurality of different determination threshold values is defined is input, and the sensitivity area to which the peak position in the defect candidate area belongs is selected from the plurality of sensitivity areas. A step of performing defect determination for each reaction value of the defect candidate region using a determination threshold;
A pattern inspection method comprising:   When the peak position extends over two or more sensitivity regions of the plurality of sensitivity regions, the defect candidate is determined using the loosest determination threshold value among the plurality of determination threshold values corresponding to the two or more sensitivity regions straddled. The pattern inspection method according to claim 1, wherein defect determination is performed for each reaction value in the region.   When a plurality of peak positions are specified in the defect candidate area and the plurality of peak positions belong to a plurality of different sensitivity areas, the most of the plurality of determination thresholds corresponding to the plurality of sensitivity areas to which the plurality of peak positions belong The pattern inspection method according to claim 1, wherein defect determination is performed for each reaction value of the defect candidate region using a loose determination threshold. An optical image acquisition unit for acquiring an optical image of the patterned sample to be inspected;
A design image data generation unit that generates a design image based on a design pattern that is a basis for pattern formation of the inspection sample;
Using the optical image and the design image, a reaction value calculation unit that calculates a reaction value for defect determination by a predetermined algorithm for each pixel;
A reaction value map creating unit for creating a reaction value map, in which the reaction value of each pixel is a map value;
Using the reaction value map, a peak position specifying unit for specifying a peak position of a reaction value in a defect candidate region in which a plurality of reaction values of a group equal to or higher than a defect candidate threshold for identifying a defect candidate is defined;
Input sensitivity region information in which a plurality of sensitivity regions corresponding to any of a plurality of different determination threshold values are defined, and correspond to the sensitivity region to which the peak position in the defect candidate region belongs among the plurality of sensitivity regions. A determination unit that performs defect determination for each reaction value of the defect candidate region using a determination threshold;
A pattern inspection apparatus comprising:   The determination unit uses the loosest determination threshold value among a plurality of determination threshold values corresponding to the two or more sensitivity regions straddled when the peak position extends over two or more sensitivity regions of the plurality of sensitivity regions. The pattern inspection apparatus according to claim 4, wherein defect determination is performed for each reaction value in the defect candidate area.

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