Abstract:
To quantify the degree of a defect, and provide information useful for yield management. Disclosed is a defect quantification method wherein: a defect image is classified; a measurement region and a measurement area are set to each of the defect image and a reference image on the basis of defect image classification results, said reference image corresponding to the defect image; and an evaluation value of a defect is calculated using each of the measurement values obtained from each of the measurement areas of the defect image and the reference image, and the defect is quantified.

Description:
TECHNICAL FIELD 
       [0001]    The present invention relates to a method and a device for quantifying a defect on a semiconductor wafer of which image is captured with a defect inspection device, and a device for displaying an evaluation value obtained through quantification. 
       BACKGROUND ART 
       [0002]    In production process of a semiconductor product, it is important to detect a reduction in the yield at an earlier point in time and perform yield management using an analysis technique for analyzing a change in the yield in order to ensure a high product yield. Various kinds of defects that occur in the production process are detected through the yield management at an earlier point in time, and countermeasures are taken. In normal circumstances, this is performed in the following three steps. (1) A semiconductor wafer is inspected with a wafer external appearance inspection device, a wafer foreign object inspection device, or the like, and the positions of a defect that occurred and a foreign object attached are detected. (2) A defect observation of the detected defect is performed, and the defect is classified on the basis of the external appearance of the defect. In this defect observation work, normally, a defect observation device having a scanning electron microscope (SEM) and the like for observing a defect portion with a high magnification rate. (3) A countermeasure is taken for each reason on the basis of the classification result. 
         [0003]    In a case where the number of defects detected by the inspection device is extremely large, the defect observation work of (2) requires a vast amount of labor, and therefore, a defect observation device having an automatic defect review (ADR) function for automatically capturing and collecting images of defect portions and an automatic defect classification (ADC) function for automatically classifying the collected images has been developed. 
         [0004]    There exists Patent Literature 1 as a method for performing measurementby changing a measurement region and a measurement direction. 
         [0005]    There exists Patent Literature 2 as a method obtaining a measurement value from an SEM image and design information. 
         [0006]    There exists Patent Literature 3 as an example of a classification method of a defect. 
       CITATION LIST 
     Patent Literature 
       [0007]    PATENT LITERATURE 1: Japanese Patent Laid-Open No. 2000-311925 
         [0008]    PATENT LITERATURE 2: Japanese Patent No. 5202110 
         [0009]    PATENT LITERATURE 3: Japanese Patent Laid-Open No. 2001-331784 
       SUMMARY OF INVENTION 
     Technical Problem 
       [0010]    As a method for performing measurement by changing a measurement region and a measurement direction, Patent Literature 1 discloses an evaluation method of photoresist application failure of a semiconductor wafer. Patent Literature 1 indicates that measurement regions are set in a radial form by making use of a fact that a target defect region is in a radial form from the center of the wafer, and a measurement value is obtained. However, in this method, measurement regions and directions specialized in photoresist application failure are designated, and it is impossible to perform measurements supporting various types of defects. 
         [0011]    As another method, Patent Literature 2 discloses a method for detecting a pattern abnormality part from an SEM image and a design information, performing defect classification in the detected pattern abnormality part, setting a measurement location in the pattern abnormality part, and obtaining a measurement value. However, in this method, the measurement is not performed on the basis of a result of defect classification, and an appropriate measurement location cannot be set on the basis of the defect type. 
         [0012]    In this case, the inventors et al. have found a new utilization method of a measurement result in which, when a countermeasure is taken for a defect, not only the classification result is derived, but also an evaluation value obtained by quantifying the degree of the defect is calculated, so that a more detailed countermeasure can be taken. 
         [0013]    For example, in a short defect, an evaluation value indicating the degree how much the short defect is close to a complete short-circuit is presented to the user so as to allow the user to determine the degree how much the situation affects the product. As a result, something like the degree of closeness of the distance between wires, which cannot be determined in a conventional classification based on only whether it is a short circuit or not, can be evaluated, and data that can be used for various kinds of objects, e.g., whether it affects the lifetime of the product, can be obtained. Likewise, something like the degree of the reduction of the width of a wire, which cannot he determined in a conventional classification based on only whether a wire is broken nor not, can be evaluated, and data that can be used for various kinds of objects, e.g., whether it affects the lifetime of the product, can be obtained. 
         [0014]    Further, monitoring of a situation of occurrence of a critical defect, prediction of the number of acquisition of conforming chips (yield prediction) based on a monitor result, and the like can be performed, 
         [0015]    One of the problems to he solved by the present invention is to provide a technique capable of setting a measurement location on the basis of a defect type. Another problem to be solved by the present invention is to provide a defect quantification method, a defect quantification device, and a defect evaluation value display device capable of quantifying the degree of the defect in association with various defects. 
       Solution to Problem 
       [0016]    An example for solving the above problem is as follows. 
         [0017]    A defect image is classified, and a measurement region and a measurement location are set for each of a defect image and a reference image corresponding to the defect image on the basis of a defect image classification result, and an evaluation value of the defect is calculated by using each measurement value obtained from measurement locations of the defect image and the reference image, and a defect is quantified. 
         [0018]    Further configurations and effects of the present invention will he understood from the disclosure of the entire specification as follows. 
       Advantageous Effects of Invention 
       [0019]    According to the present invention, a defect measurement according to the type of the defect can he performed for various defect types, and information useful for yield management can be provided by a defect evaluation value based on this measurement value. 
     
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         [0020]      FIG. 1  is a configuration diagram illustrating a defect quantification device according to an embodiment of the present invention. 
           [0021]      FIG. 2  is a configuration diagram illustrating a defect observation device according to an embodiment of the present invention. 
           [0022]      FIG. 3  is a flow diagram illustrating a procedure of a defect observation according to an embodiment of the present invention. 
           [0023]      FIG. 4  is an explanatory diagram illustrating an example of measurement locations of defect images and reference images for each defect type according to an embodiment of the present invention. 
           [0024]      FIG. 5  is a flow diagram illustrating a procedure of defect quantification processing according to an embodiment of the present invention. 
           [0025]      FIG. 6  is a flow diagram illustrating an example of a procedure of pattern defect classification processing according to an embodiment of the present invention. 
           [0026]      FIG. 7  is an explanatory diagram illustrating an example of an intermediate result of pattern defect classification processing according to an embodiment of the present invention. 
           [0027]      FIG. 8  is a flow diagram illustrating a procedure of measurement location setting processing according to an embodiment of the present invention. 
           [0028]      FIG. 9  is an explanatory diagram illustrating an example of intermediate images of processing for setting a measurement region and measurement location in a defect image and a reference image on the basis of a measurement recipe according to an embodiment of the present invention. 
           [0029]      FIG. 10  is a figure illustrating an example of a screen input and an output display for setting a measurement recipe for each defect type according to an embodiment of the present invention. 
           [0030]      FIG. 11  is a figure illustrating an example of a screen input/output display for displaying a quantification result according to an embodiment of the present invention. 
           [0031]      FIG. 12  is a configuration diagram illustrating a defect quantification device according to an embodiment of the present invention. 
           [0032]      FIG. 13  is a flow diagram illustrating a procedure of defect quantification processing according to an embodiment of the present invention. 
           [0033]      FIG. 14  is a configuration diagram illustrating a defect quantification device according to an embodiment of the present invention. 
           [0034]      FIG. 15  is a flow diagram illustrating a procedure of an image-capturing recipe generation according to an embodiment of the present invention. 
       
    
    
     DESCRIPTION OF EMBODIMENTS 
       [0035]    The present invention relates to a defect quantification method for quantifying various kinds of defects on a semiconductor wafer, and a device therefor, and also relates to a defect evaluation value display device for displaying an evaluation value of a defect obtained with this defect quantification method and device. 
         [0036]    Hereinafter, embodiments of the present invention will be explained in details with reference to drawings. Throughout all of the drawings for explaining the embodiments, the same members are basically denoted with the same reference numerals, and repeated explanation thereabout is omitted. In the present embodiment, a method for quantifying a defect using a defect image captured with a defect observation device having an SEM will be explained, but an input to a defect quantification method and a device thereof according to the present invention may be those other than an SEM image, and the method and the device may use a defect image captured with optical means, an ion microscope, and the like. 
         [0037]    Defect observation of a semiconductor wafer is targeted on various kinds of defects such as a short, an open, and the like. For this reason, in quantification of a defect, a portion to be measured is also different according to the type of defect, and it is necessary to set a measurement location by switching a measurement region, a measurement target, a measurement direction, a measurement method for each defect. For example, in a half short c which adjacent wires are almost short-circuited, in order to evaluate the degree of short-circuit, it is necessary to evaluate the distance between wires which has become narrower due to a defect and a normal inter-wire distance in which there is no defect, and therefore in a half open defect in which wires are almost broken, in order to evaluate the degree of open, it is necessary to evaluate a wire width which has become narrower due to a defect and a normal wire width in which there is no defect. Information about the measurement region, the measurement target, the measurement direction, the measurement method, and the like, or a file having information thereabout will be hereinafter referred to as a measurement recipe in the present invention. 
       First Embodiment 
       [0038]      FIG. 1  is a configuration diagram illustrating a first embodiment of the present invention. 
         [0039]    A defect quantification device  101  is connected to a defect observation device  102  observing a defect on a semiconductor wafer via communication means  103 . The defect observation device  102  is a device for obtaining an image of a defect portion. The details of the defect observation device  102  will be explained later with reference to  FIG. 2 . An image of a defect obtained by the defect observation device  102  is transmitted via the communication means  103  to the defect quantification device  101 . The defect quantification device  101  classifies the received defect image in accordance with the type of defect, and calculates a quantitative value about the defect, and the defect quantification device  101  has a function of displaying, on the input/output unit  104 , the obtained classification result, an evaluation value, calculated on the basis of the defect quantitative value, related information used for evaluation value calculation, and the defect image. The input/output unit  104  is constituted by a keyboard, a mouse, a display device, and the like for presenting data to an operator and receiving an input from the operator. 
         [0040]    The details of this defect quantification device  101  will be explained. The defect quantification device  101  includes an overall control unit  105  for controlling operation of the device, a storage unit  106  for storing images received from the defect observation device  102  and measurement recipes required for measuring the images, a processing unit  107  for performing measurement recipe operation, image measurement processing, evaluation value calculation, and the like required for defect quantification, an input/output unit  104 , an input/output I/F unit  108  for data transfer via the communication means  103 , a memory  109 , for storing programs, image information, and the like, and a bus  111  for performing data communication between the storage unit  106 , the processing unit  107 , the memory  109 , the overall control unit  105 , and the input/output I/F  108 . 
         [0041]    The storage unit  106  includes an image storage unit  110  storing a defect image and a reference image captured by the defect observation device  102  and a measurement recipe storage unit  112  for storing measurement region information that is set for the images captured by the defect observation device  102  and a measurement recipe including information about the target measurement method. The processing unit  107  includes a defect image classification unit  113  for classifying a defect image captured by the defect observation device  102  for each type of defect, a measurement recipe selection unit  114  for selecting a measurement recipe stored in the measurement recipe storage unit  112  on the basis of a classification result, an image measurement processing unit  115  for setting a measurement region in a defect image and a reference image on the basis of the selected measurement recipe and performing measurement processing of the measurement target on the image, a defect quantification unit  116  for calculating an evaluation value of defect from the measurement value, a wire pattern recognition unit  117  for recognizing a wire pattern from an image captured by the defect observation device, and a defect detection unit  118  for detecting a defect region from a defect image. It should be noted that the details of the processing performed by the processing unit will be explained later. 
         [0042]      FIG. 2  is a configuration diagram illustrating a defect observation device  102 . The defect observation device  102  is configured so that an SEM column  201 , an SEM control unit  208 , an input/output I/F  209 , a storage unit  211 , and a supplementary information generation unit  214  are connected via communication means  215 . The input/output I/F  209  is connected to the input/output unit  210 , and performs input/output of data to and from the operator. 
         [0043]    The SEM column  201  includes an electron source  202 , a sample wafer  207 , and a stage  206  on which the sample wafer  207  is placed, and multiple detection devices  203 ,  204 ,  205  for detecting secondary electrons and backscattering electrons which are generated as a result of an emission of a primary electron beam to the sample wafer  207  from the electron source  202 . In addition, the SEM column  201  includes a deflection device not shown) for scanning a primary electron beam on an observation region of the sample wafer  207 , an image generation unit (not shown) for generating a digital image by converting the strength of the detected electron into digital, and the like. An image obtained by detecting the secondary electrons with the detection device  203  will be referred to as an SE image, and an image obtained by detecting the backscattering electrons with the detection devices  204  and  205  will be referred to as an L image and an R image. 
         [0044]    The storage unit  211  includes an image-capturing recipe storage unit  212  storing a coordinate of a defect, of which image is to be captured, on the wafer and SEM image-capturing conditions (acceleration voltage, probe current, the number of added frames, visual field size, and the like) and an image memory  213  saving obtained image data. 
         [0045]    The supplementary information generation unit  214  has a function of generating information supplementing each piece of image data, e.g., image-capturing conditions such as an acceleration voltage, a probe current, the number of added frames, and the like during image-capturing process, ID information for identifying an image-capturing device, a type and a property of the detection devices  203  to  205  used for image generation, an ID and process of a wafer, and information such as the date and the time at which an image is captured. Information about the ID and process of the wafer may be input by the user with the input/output unit  210  and the like, or may he read from the surface of the wafer or read from a box (not shown) in which the wafer is stored. When image data is transferred via the input/output I/F  209 , the generated supplementary information and the image data is transferred at a time. 
         [0046]    The SEM control unit  208  is a unit for controlling al the processing performed with the defect observation device  102  such as image acquisition. In accordance with a control from the SEM control unit  208 , the defect observation device  102  performs movement of the stage  206  for moving a predetermined observation portion on the sample wafer  207  into an image-capturing visual field, emission of a primary electron beam onto the sample wafer  207 , detection of electrons generated from the sample with the detection devices  203  to  205 , imaging of detected electrons, saving the, image to the image memory  213 , generation of supplementary information for the captured image with the supplementary information generation unit  214 , and the like. Various kinds of commands given by the operator, designations of image-capturing conditions, and the like are given by using the input/output unit  210  constituted by a keyboard, a mouse, a display, and the like. 
         [0047]    Hereinafter, a method of a defect observation according to the presentation will be explained with reference to  FIG. 3 .  FIG. 3  illustrates a flow of defect observation including defect quantification according to the present invention. 
         [0048]    First, defect position information (defect coordinate) obtained with an inspection device such as a wafer external appearance inspection device or a wafer foreign object inspection device is obtained (S 301 ). The defect coordinate may be saved to an image-capturing recipe stored in the image-capturing recipe storage unit  212 . 
         [0049]    Subsequently, a defect image and a reference image corresponding to each defect coordinate are captured with the defect observation device  102  (S 303 ), and the defect quantification device  101  performs defect quantification in the defect image and the reference image, and calculates an evaluation value (S 304 ). The processing in S 303  to S 304  is repeated for the number of defect coordinates (i.e., the number of defects). The details about the defect quantification processing S 304  will be explained later. 
         [0050]    The defect image is a SEM image including a defect portion detected with the inspection device, and the reference image means a conforming image that does not include any defect portion in which the same pattern as the wire pattern of the defect image is captured. A semiconductor has such a feature that the same wire pattern is generated for each die, and therefore, the reference image may be captured at a position corresponding to the defect coordinate on a die adjacent to the die having the defect. A reference image may be generated by masking a defect portion of a defect image and combining the mask region with an image of a peripheral region. In a case where there is design information of a wire pattern corresponding to the defect coordinate, a reference image may be generated through simulation from the design information. 
         [0051]    Hereinafter, the quantification processing S 304  of the defect will be explained with reference to  FIGS. 4, 5 . In the quantification of the defect disclosed in the present embodiment, not only the measurement value of the defect portion obtained from the defect image but also the measurement value obtained from the reference image are used as a reference of comparison. For example, in a case where the adjacent wire patterns are almost shorted even though they are not actually shorted, the minimum distance between the adjacent wire patterns and the inter-wire distance in the reference image are measured, and the measurement values thereof are compared, so that a defect can be evaluated by quantifying the degree how much the distance between the wires is narrowed as compared to the normal case. In the quantification of the defect, the method of the quantification differs according to the defect type, and the measurement region setting method in the defect image and the reference image, the definition of the measurement location, and the calculation method of the quantitative value are different. 
         [0052]      FIG. 4  collectively illustrates measurement regions and measurement locations of the defect image and the reference image for each defect type. A defect type (a) indicates an example of a full-short where adjacent wire patterns are completely shorted. A defect type (b) indicates an example of a half-short where adjacent wire patterns are almost shorted. A defect type (c) indicates an example of a full-open where wire patterns are completely cut off. A defect type (d) indicates an example of a half-open where wire patterns are almost cut off and the width is narrowed. A defect type (e) indicates an example of a roughness where fluctuation of a wire width occurs. A defect type (f) indicates an example of a hole defect where a hole diameter is reduced. The hole defect also includes a case where the hole diameter is expanded, but it is not shown in this case. 
         [0053]    Reference symbols  411  to  416  denote examples of defect images corresponding to each defect type. Reference symbols  421  to  426  denote examples of reference images corresponding to  411  to  416 . Reference symbols  411  to  415 ,  421  to  425  denote examples where a wire pattern  401  is formed on a base  402 . The defect images  412  to  415  and the reference images  421  to  425  are also shown in the same manner, and more specifically, a wire pattern  401  is indicated in a bright manner and a base  402  is indicated in a dark manner although reference symbols are not given. The defect image  416  is an example where a hole  406  is formed in an upper layer  405 , and although a reference symbol is not attached., the corresponding reference image  426  is also shown in the same manner, and more specifically, an upper layer  405  is indicated in a bright manner and a hole  406  is indicated in a dark manner. The defect types (a) to (d) of  FIG. 4  are referred to as pattern defects. 
         [0054]    The image  411  illustrates an example of a measurement region  403  including a measurement target and a measurement location  404 . Reference symbol  404  indicates that the measurement location is defined by a distance between both ends of an arrow. The indications of the measurement locations in reference symbols  412  to  416 ,  421  to  426  are also given in a similar manner. 
         [0055]    Hereinafter, an example of calculation of the measurement region, the measurement location, and the defect evaluation value for each defect type will he explained. It should be noted that the example of calculation shown here shows an example of calculation in which, e.g., when the defect evaluation value is higher, it is a defect which it is necessary to pay attention to, for example, the criticality of the product is higher, or it is a defect that greatly affects the yield. 
       (a) Full-Short: 
       [0056]    When a short defect occurs over a larger range between adjacent wires, it is a defect which it is necessary to pay attention to. In order to express this, the shortest distance of the shorted portion shown in the defect image  411  (the measurement value of the defect image) and the inter-wire distance in the reference image  121  (the measurement value of the reference image) are measured, and an evaluation value obtained by normalizing it with the inter-wire distance according to the following defect evaluation value calculation expression is calculated. 
         [0000]      evaluation value=measurement value of defect image/measurement value of reference image   (Expression 1)
 
       (b) Half Short: 
       [0057]    When the distance between the wires is narrower, it is a defect which it is necessary to pay attention to, even though it is not a full-short. In order to express this, the shortest distance between wires in a portion that is almost short-circuited shown in the defect image  412  (the measurement value of the defect image) and the inter-wire distance in the reference image  422  (the measurement value of the reference image) are measured, and an evaluation value obtained by normalizing it with the inter-wire distance according to the following defect evaluation value calculation expression is calculated. 
         [0000]      evaluation value=1.0−measurement value of defect image/measurement value of reference image   (Expression 2)
 
       (c) Full-Open: 
       [0058]    When an open defect has a larger break in the wire, it is a defect which it is necessary to pay attention to. In order to express this, the shortest distance in an open portion shown in the defect image  413  (the measurement value of the defect image) and the wire width in the reference image  423  (the measurement value of the reference image) are measured, and an evaluation value is calculated with the defect evaluation value calculation expression in Expression (1). 
       (d) Half Open: 
       [0059]    When the wire width is narrower even though it is not completely open, it is a defect which it is necessary to pay attention to. In order to express this, the wire minimum width of a portion that is almost open shown in the defect image  414  (the measurement value of the defect image) and the wire width in the reference image  424  (the measurement value of the reference image) are measured, and an evaluation value is calculated with the defect evaluation value calculation expression in Expression (2). 
       (e) Roughness: 
       [0060]    When the fluctuation of the wire th due to roughness is larger, the degree of attention is higher. In order to express this, the maximum width of the fluctuation of the roughness shown in the defect image  415  (the measurement value of the defect image) and the wire width in the reference image  425  (the measurement value of the reference image) are measured, and an evaluation value is calculated with the defect evaluation value calculation expression in Expression (1). 
       (f) Hole Defect: 
       [0061]    When the hole diameter of the defect image is more greatly different from the hole diameter of the reference image in the hole defect, it is a defect which it is necessary to pay attention to. In order to express this, the hole diameter obtained from the defect image  416  (the measurement value of the defect image) and the hole diameter obtained from the reference image  426  (the measurement value of the reference image) are measured, and an evaluation value is calculated with the following defect evaluation value calculation expression. 
         [0000]      evaluation value=1 measurement value of defect image−measurement value of reference image 1/measurement value of reference image   (Expression 3)
 
         [0062]    In the above explanation, although an example of the defect types (a) to (f) has been explained, the present invention can also be applied to other defect types. For example, a foreign object can be classified in accordance with how a wire is short--circuited due to the foreign object in a similar manner to (a) full-short, (b) half short, and the evaluation value can be calculated by using a calculation expression of the measurement method and evaluation value similar thereto. 
         [0063]    The examples of the measurement regions and the measurement location of  FIG. 4  are examples, and the user sets and registers a measurement recipe for each defect type, so that a measurement location intended by the user can be set on the basis of the measurement recipe that is different for each defect type. 
         [0064]    The setting method of the measurement recipe will be explained later with reference to  FIG. 10 . The details of the measurement location setting with the measurement recipe will be explained later with reference to  FIG. 8 . 
         [0065]    FIG,  4  shows the example where a single portion is measured each of the defer image and the reference image, but the measurement region and the measurement location are not limited to a single portion. Alternatively, multiple locations may be set, and an evaluation value may be calculated from multiple measurement values by using arithmetic calculation and weighted addition. There may be multiple evaluation values to be calculated, and the measurement values may he output as evaluation values without any calculation. Even in a case where the measurement values may be output as evaluation values without any calculation, it will be referred to as calculation of the evaluation values in the explanation. 
         [0066]      FIG. 5  is a detailed flow of the defect quantification processing S 304 . In the defect quantification, first, the defect classification unit  113  classifies images in accordance with the defect type such as full-short, half short, and the like (S 501 ). Subsequently, the measurement recipe selection unit  114  reads a measurement recipe corresponding to the classification result from the measurement recipe storage unit  112 , and the image measurement processing unit  115  sets the measurement region for each of the defect image and the reference image on the basis of the measurement region information described in the measurement recipe ( 5502 ). Subsequently, the measurement location designated in the measurement recipe is measured in the measurement region of the defect image and the reference image (S 503 ). A specific processing method in S 501  to S 503  will be explained later. Finally, the evaluation value is calculated from the measurement value (S 504 ). The calculation expression of the evaluation value is performed by using the expression designated in the measurement recipe. S 503  and  5504  are executed by the defect quantification unit  116 , 
         [0067]    In a case where a SEM image captured from an adjacent die and the like as the reference image is used in the quantification processing of  5304 , this allows comparison with the measurement value of the conforming pattern produced through an actual process, and therefore, there is an advantage in that an evaluation value more precisely based on the reality can be calculated as compared with the case where a value of a wire width and a wire distance obtained from the design information is used. In a case where the reference image is composed from a defect image or in a case where the reference image is generated from design information, it is not necessary to individually capture the reference image, and therefore, there is an advantage in that the image-capturing throughput per defect is improved. 
         [0068]    The defect image classification processing (S 501 ) will be explained with reference to  FIG. 6  and  FIG. 7 .  FIG. 6  is a flowchart illustrating defect image classification processing for a pattern defect.  FIG. 7  schematically illustrates the steps of processing of an image in the flowchart of  FIG. 6 . 
         [0069]    First, in the defect detection processing, a defect region is extracted from the defect image (S 601 ). In a specific processing example of the defect detection processing, a differential image is generated from a difference in grayscale at each pixel between the defect image and the reference image, and a location having a large absolute value of the grayscale value in the differential image, or a large positive or negative value thereof may he extracted as the defect region. In order to extract a region from a grayscale image, Otsu binarization and the like may be used as the binarization method of the grayscale value. In a case where the position of the wire pattern differs between the defect image and the reference image, the position of the wire pattern may be adjusted between the defect image and the reference image by using Normalized Cross Correlation and the like, and thereafter, the differential image may be generated. In  FIG. 7 , a defect image  701  is an example of a full-short defect, and  702  denotes a corresponding reference image. In the example of  FIG. 7 , when the defect detection processing is executed, a defect detection image  703  is obtained, and a defect region  711  is extracted. 
         [0070]    Subsequently, the wire pattern recognition processing is performed on the reference image, and a wire pattern region is extracted (S 602 ). The wire pattern recognition processing may be performed with a generally-available region dividing technique of images. For example, in a case where the grayscale value of the wire pattern region is high, and the grayscale value of the base is low, the wire pattern region is extracted by using a binarization technique such as Otsu binarization. Alternatively, edge detection filter processing such as sobel filter may be performed, and a wire edge may be detected by binarizing the processing image, so that the image may be divided into regions by using the edges, and a wire pattern region may be extracted. A wire pattern recognition image  704  of  FIG. 7  denotes a wire pattern recognition result in a reference image  702  and a wire pattern region  712  is extracted. 
         [0071]    Finally, the pattern defect is classified from a position relationship between the defect region and the wire pattern region obtained in S 601  and S 602  (S 603 ). In this classification, the defect region and the wire pattern region are overlaid, and in a case where the defect region is on the wire pattern region, it can be determined to be an open defect, and in a case where the defect region is outside of the wire pattern region, it can be determined to be a short defect. In this case, the position relationship of the regions means whether or not the defect region is on the wire pattern region or outside of the wire pattern region. In order to determine whether the defect region is on the wire region or outside of the wire region, summations of the number of pixels in the defect region overlapping the wire pattern region and the number of pixels in the defect region not overlapping the wire pattern region are calculated, and a comparison is performed, and in a case where the number of pixels in the defect region overlapping the wire pattern region is higher, the defect region may be determined to be inside of the wire pattern region, and in a case where the number of pixels in the defect region not overlapping the wire pattern region is higher, the defect region may be determined to be outside of the wire pattern region,  100521   
         [0072]    In a case of an open defect, the defect region may be classified into a full-open when the defect region completely covers the wire pattern region, and the defect region may be classified into a half-open when the defect region does not completely cover the wire pattern region. In this case, the position relationship of the regions means whether or not the defect region completely covers the wire pattern region. In order to determine whether or not the defect region completely covers the wire pattern region, for example, a rectangle circumscribing the defect region (circumscribing rectangle) is calculated, and when the edges of both ends of the wire pattern region are included in the circumscribing rectangle, the defect region can be determined to completely include the wire pattern region. The edge may be detected by applying an edge detection filter such as sobel filter to the wire pattern recognition result and performing the binarization. 
         [0073]    In a case of short defect, the defect region can be classified into a full-short when independent wire regions are connected by the defect region, and the defect region can be classified into a half-short when independent wire regions are not connected by the defect region. In this case, the position relationship of the regions means whether independent wire regions are connected by the defect region or not. In order to determine whether the defect region connects the wire regions or not, for example, a rectangle circumscribing the defect region may be calculated, and a determination may be made as to whether both edges of an adjacent wire pattern region are included in the circumscribing rectangle. In a case where both edges are included, the defect region can be determined to completely extend over both of the wires. Reference symbol  705  of  FIG. 7  illustrates a figure displaying a defect region  711  and a wire pattern region  712  in an overlapping manner, and the defect region can be classified into a full-short defect since the defect region is outside of the wire pattern region and completely extends over wires. The rules of the classifications may be registered in advance by the user. 
         [0074]    In this case, the method for classifying a pattern defect from a position relationship between a defect region and a wire pattern region has been explained. Alternatively, a classification may be performed in accordance with a technique for calculating a feature quantity such as circularity, brightness dispersion, and the like of a defect from a defect image and a reference image and classifying the pattern defect on the basis of machine learning from the feature quantity, described in Patent Literature  3 . In the classification based on the machine learning using the feature quantity, the classification can be performed with those other than the pattern defects. 
         [0075]    An operation of the defect image classification processing explained above performed on a device will be explained with reference to  FIG. 1 . The defect image and the reference image captured by the defect observation device  102  are transmitted via the communication means  103  to the defect quantification device  101 , and the transmitted images are read via the input/output OF  108  to the defect quantification device  101 . The read images are transferred by the overall control unit  105  to the defect detection unit  118 , and the defect detection unit  118  executes the defect detection processing. The read reference images are transferred by the overall control unit  105  to the wire pattern recognition unit  117 , and the wire pattern recognition unit  117  executes the wire pattern recognition processing. The defect detection image obtained by the defect detection unit  118  and the wire pattern recognition image obtained by the wire pattern recognition unit  117  are sent by the overall control unit  105  to the defect classification unit  113 , which executes the defect image classification processing. The classification result is stored in the memory  109 . 
         [0076]    Subsequently,the processing S 502  for setting a measurement region on the basis of a classification result will be explained with reference to  FIG. 8 .  FIG. 8  illustrates a processing flow of S 502 . First, a measurement recipe prepared in advance for each classification type is selected on the basis of the classification result (S 801 ). In this case, the measurement recipe is information for designating measurement regions in a defect image and a reference image and the measurement location of a measurement target, and includes information about a definition of a measurement location such as, for example, a relative position of the measurement region with respect to the wire pattern on the defect region and the reference image, a measurement direction for a measurement target (e.g., whether it is in the vertical direction or the horizontal direction with respect to the wire pattern), a measurement target (wire width or inter--wire distance), a measurement method (the shortest distance, the average distance, and the like of the measurement target in the measurement region), and the like. The measurement direction may be designated as the horizontal direction and the vertical direction in the defect image and the reference image, or may be designated as a diagonal direction by using a combination of the vertical and horizontal directions. The measurement recipe is set by the user in advance, and stored in the measurement recipe storage unit  112 . The setting method of the measurement recipe will be explained later with reference to  FIG. 10 . Subsequently, the measurement region is set in the defect image and the reference image on the basis of the measurement recipe selected in S 801  (S 802 ). 
         [0077]    An operation of the measurement region setting processing explained above performed on a device will be explained with reference to  FIG. 1 . The measurement recipe selection unit  114  reads, from the measurement recipe storage unit  112 , a measurement recipe corresponding to the classification result stored in the memory  109 , and sends the measurement recipe to the image measurement processing unit  115 . The image measurement processing unit  115  converts position information about the measurement region into a coordinate on the defect image and the reference image on the basis of the selected measurement recipe. 
         [0078]    The details of S 802  and S 503  performed subsequent to S 802  will be explained with reference to  FIG. 9 .  FIG. 9  illustrates, using images, intermediate processing states in S 802  and S 503  in a case of a half short defect, for example.  5802  and  5503  are executed for each of the defect image and the reference image. 
         [0079]    The measurement region is determined from information about the measurement direction, the measurement target, and the measurement portion of the measurement recipe, and the defect region and the wire pattern region obtained from the image processing. For example, an image  901  of a half short defect of  FIG. 9  and a corresponding reference image  902  is used for the explanation. A defect detection result  903  and a wire pattern recognition result  904  are obtained in accordance with the above method from the defect image  901  and the reference image  902 . As illustrated in  FIG. 4 , in a case of a half short, the measurement location in the defect image is an inter-wire distance of an almost-shorted portion, and the measurement location in the reference image is an inter-wire distance. The short-circuit occurs with an adjacent wire, and therefore, the measurement direction in the defect image is a direction perpendicular to the wire (x direction in  FIG. 9 ), the measurement target is an inter-wire distance, and the measurement portion may be set to a location where the inter-wire distance is the shortest. 
         [0080]    It should be noted that the wire direction can be determined by deriving a direction of a wire edge in accordance with a technique such as Hough transform from the edge detection result of the wire pattern region  904  in the reference image. The image  905  is an image obtained by superimposing the defect region and the pattern region, and reference numeral  914  denotes a measurement region  914  of the defect. The measurement region  914  is set to include the measurement location. In a case of  905 , the edge of the defect and the edge of the adjacent wire pattern are the measurement location. The measurement region  914  may be set to a region obtained by stretching a rectangle  913  circumscribing the defect region  911  in the measurement direction (x direction) so as to be deformed to include a wire pattern region edge portion at the side opposite to the defect region which is the measurement location. In  FIG. 9 , for the sake of explanation, the circumscribing rectangle  913  is shown in a region slightly larger than the rectangle circumscribing the defect region  911 . 
         [0081]    An image  906  showing the measurement step of S 503  indicates a result in which a measurement location  916  is set from the measurement region  914 , and the measurement location is indicated with an arrow like  FIG. 4 . In order to obtain the measurement value on the basis of the measurement location, for example, in each y coordinate in the measurement region  914 , the measurement direction (x direction) is scanned, and the location where the defect region  911  and the wire pattern region  912  are closest is extracted, and a combination of coordinates may be adopted as the measurement location. 
         [0082]    As illustrated in  FIG. 4 , the measurement direction in the reference image  902  of  FIG. 9  may be set to a wire vertical direction (x direction), the measurement target may be set to an inter-wire distance, and the measurement portion may be set to an average distance between wires. When the measurement portion is the average in the measurement region, the influence of the noise can be reduced in a pattern having a simple shape such as a line pattern. A measurement region  915  is a measurement region for the reference image. The rectangle  913  circumscribing the defect region of the defect image is stretched in the measurement direction, and a measurement region is set on the reference image so as to include the portion between the wires which is the measurement target. More specifically, the reference image is scanned in the measurement direction (x direction) by using the center coordinate of the defect region of the defect image, and the measurement region may be stretched until the edge of the wire pattern region  912  is found. An image  907  indicating the measurement step of S 503  in the reference image shows, with an arrow, a result in which the measurement location  917  is set from the measurement region  915 . In order to obtain the measurement value on the basis of the measurement location, for example, in each y coordinate in the measurement region  915 , the measurement direction (x direction) is scanned, and the distance between the right and the left wire pattern regions  912  within the measurement region  915  may be measured. In the image  917 , a measurement value is shown as the distance between the two points, but the average of the distance between the wires that can be measured in the measurement region  915  may be used. For the measurement region in the reference image, the same region as that in the defect image may be used. 
         [0083]    As another method of the measurement processing S 503 , the measurement region that has been set may be used with the technique described in Patent Literature 2. 
         [0084]    By making use of the fact that the grayscale value increases at the wire pattern edge portion, the end of the defect portion, and the like which are to be set in the SEM image, one-dimensional waveform (grayscale profile) of the grayscale value in the measurement direction on the image is obtained, and a highly accurate measurement value is calculated from the grayscale profile. A grayscale profile in the measurement direction that has been set is obtained in the measurement region, and the threshold value is calculated from the maximum value and the minimum value of the grayscale value in a portion of the grayscale profile where there is a grayscale inclination (i.e., a wire pattern edge portion or an end of the defect portion), and a coordinate where the grayscale value is a threshold value is searched and determined to be the measurement position. The measurement location is set from multiple measurement positions determined from the grayscale profile. In this case, the measurement location is not a coordinate on the image, but is a position on the grayscale profile. 
         [0085]    In the grayscale profile of the SEM image, there may he positions where the grayscale value is equal to the threshold value at both sides of the position of the portion where there is the grayscale inclination and where the grayscale value is the highest. In this case, which position is determined to be the measurement position may be determined from the measurement target included in the measurement recipe. For example, when the measurement target is a wire width, the position farther from the center coordinate of the measurement region is determined to be the measurement position, and when the measurement target is an inter-wire distance, the position closer to the center coordinate of the measurement region is determined to be the measurement position. In order to reduce the influence of the noise, the grayscale profile may be projected in a direction perpendicular to the measurement direction, and an arithmetic mean may be employed. 
         [0086]    The setting method of the measurement recipe will be explained reference to  FIG. 10 . 
         [0087]    As described above, the measurement recipe is set in advance for each defect type, and stored in the measurement recipe storage unit  112 .  FIG. 10  is a screen for setting a measurement recipe. Reference symbol  1001  shows defect types that can be classified in the defect classification processing S 501 . Reference symbol  1002  shows, for each defect type, values of information (measurement direction, measurement target, measurement method, and the like) required for setting a measurement location for a defect image. The direction means a measurement direction, and includes a direction parallel to or perpendicular to a wire, or horizontal and vertical directions of the image, or the like. The target means a measurement target, and includes a wire region width, a distance between wire regions, a defect size in an image horizontal direction, a defect size in an image vertical direction, a distance between a defect region and a wire region, and the like. The method means a measurement method, and includes an average value, the minimum value, the maximum value, an intermediate value, and the like of the measurement target. Each item can he changed into any given value with a combo box and the like. Reference symbol  1003  displays, for each defect type, values of information required for setting a measurement location for a reference image. The measurement recipe may include items other than the measurement direction, the measurement target, and the measurement method as long as it is information required for the measurement processing. Although not shown in the drawing, the defect evaluation value calculation expression explained above is also configured so that it can be set for each defect type. Reference symbol  1004  denotes a button for adding an item of a defect type, and reference symbol  1005  denotes a button for deleting a defect type. In reference symbol  1001 , information about a defect type used in the classification in the defect image classification processing S 501  may be read and displayed. 
         [0088]    A display of a quantification result will be explained with reference to  FIG. 11 .  FIG. 11  is a display screen illustrating a processing result in the defect quantification processing S 304 . Displayed on the screen are a defect ID  1101 , a defect image  1102 , a reference image  1103 , a classification result  1104  in the defect image classification processing S 501 , a measurement value  1105  in the defect image measured in S 503  and a measurement value  1106  in a reference image, and an evaluation value  1107  calculated from a defect image and a reference image in S 504 . A measurement region  1108  and a measurement location  1109  are displayed on the defect image  1102  and the reference image  1103 . In a case where there are multiple measurement locations for a single measurement region, only a representing measurement location may be displayed. There may not be only one measurement region  1108  and only one measurement location  1109  in the defect image and the reference image, and in a case where there are multiple measurement regions  1108  and measurement locations  1109 , the multiple measurement regions  1108  and measurement locations  1109  may be displayed. In a case where there are multiple defect image measurement values  1105 , reference image measurement values  1106 , and evaluation values  1107 , all or some of the defect image measurement values  1105 , reference image measurement values  1106 , and evaluation values  1107  may be displayed on the screen. In a case where there are multiple measurement values, IDs may be given to the measurement values, and the corresponding IDs may be displayed in proximity to the measurement region and the measurement location on the image, so that the measurement locations and the measurement regions can be associated with each other. Reference symbol  1110  is a combo box for selecting a type of an image displayed as the defect image  1102  and the reference image  1103 . 
         [0089]    According to the first embodiment explained above, an appropriate measurement location can he set on the defect image and the reference image on the basis of the type of the defect, and the evaluation value is calculated by using the obtained measurement value, so that information useful for yield management can he presented to the user. 
       Second Embodiment 
       [0090]    In the second embodiment, a defect quantification method for calculating the measurement value of a defect image and a reference image on the basis of multiple stored measurement recipes, selecting a measurement value used for evaluation value calculation on the basis of a classification result of a defect, and calculating the evaluation value will be explained. 
         [0091]    The present embodiment is different from the first embodiment only in the device configuration ( FIG. 1 ) and the quantification flow ( FIG. 5 ), and except the above, the present embodiment includes a method, a device, and a screen input/output display similar to those of the first embodiment. Hereinafter, only portions different from the first embodiment will be explained. 
         [0092]    A device configuration according to the present embodiment is shown in  FIG. 12 . In addition to the device configuration of the first embodiment explained in  FIG. 1 , a measurement value selection unit  1201  for selecting a measurement value used for quantification is provided in the processing unit  107 . 
         [0093]    Subsequently, a procedure of quantification will be explained with reference to  FIG. 13 .  FIG. 13  is an example of a quantification flow according to the present embodiment. In the present embodiment, first, the defect image classification processing is executed (S 502 ), and multiple measurement regions are set for each of a defect image and a reference image (S 1301 ). S 1301  is executed by the image measurement processing unit  115 , and the setting is made on the basis of all or some of the measurement recipes stored in the measurement recipe storage unit  112 . The setting of the measurement locations may be performed by using a method similar to that of the first embodiment. 
         [0094]    Subsequently,in accordance with a method similar to the first embodiment, measurement locations that are set in the defect image and the reference image are measured (S 503 ). 
         [0095]    On the basis of the classification result of S 501 , a measurement value used for evaluation value calculation is selected from among the measurement values obtained in S 503  (S 1302 ). S 1302  is executed by the measurement value selection unit  1201 . In the selection of the measurement value, for example, a measurement recipe associated with the classified defect type may be read from the measurement recipe storage unit  112 , and the measurement value of the measurement location matching the setting of the measurement recipe may be selected. When the measurement location is set and measured, the defect type information corresponding to the used measurement recipe may also be stored together with the measurement value, and a measurement value may be selected from information about the defect type. 
         [0096]    Finally, in accordance, with a method similar to the first embodiment, the evaluation value calculation is performed from the selected measurement value. It should be noted that the defect classification processing  5501  may be performed, at any given point in time as long as it is before the measurement value selection processing S 1302 . 
         [0097]    According to the above second embodiment, effects similar to those of the first embodiment can be obtained, and an appropriate measurement location can he set on the defect image and the reference image on the basis of the type of the defect, and the evaluation value is calculated by using the obtained measurement value, so that information useful for the yield management can be presented to the user. 
       Third Embodiment 
       [0098]    In the third embodiment, a method for identifying a location where defect observation is to be performed on a wafer of the same process on the basis of an evaluation value of a defect quantified according to the first or second embodiment and executing defect observation will be described. It should be noted that the present embodiment will be explained on the basis of the first embodiment, but even if the evaluation value is obtained according to the second embodiment, the present embodiment can be executed. 
         [0099]    The present embodiment is different from the first embodiment only in the device configuration ( FIG. 1 ) and the flow of the defect observation ( FIG. 3 ), and except the above, the present embodiment includes a method, a device, and, a screen input/output display similar to those of the first embodiment. 
         [0100]    A device configuration according to the present embodiment is shown in  FIG. 14 . In addition to the device configuration of the first embodiment explained in  FIG. 1  an image-capturing recipe generation unit  1401  for capturing an image of a wafer of the same process as the wafer for which the defect evaluation value has been calculated and an image-capturing recipe storage unit  1402  for storing the generated image-capturing recipe are provided in the processing unit  107 . In this case, the image-capturing recipe means information having a coordinate of the observation position On the wafer where the defect observation is to be performed, an observation magnification rate at that position, an image-capturing condition of an electron optical system, and the like. 
         [0101]    Subsequently, a procedure of image-capturing recipe generation will be explained with reference to  FIG. 15 .  FIG. 15  is an example of an image-capturing recipe generation according to the present embodiment. In  5301  to  5304 , processing similar to that in the first embodiment is performed. Subsequently, the evaluation value obtained in S 304  and a threshold value are compared (S 1501 ). It is assumed that the threshold value is set in advance by the user. In a case where there are multiple evaluation values, a threshold value corresponding to each of the evaluation values is prepared. 
         [0102]    In a case where the evaluation value is equal to or more than the threshold value, the quantified coordinate of the defect on the water is added to the image-capturing recipe as an image-capturing target (S 1502 ). The condition for adding the defect coordinate to the image-capturing recipe is not limited to the condition that the evaluation value is equal to or more than the threshold value. The condition may be any given condition, and it is assumed that this condition is set before the flow of  FIG. 15  is executed. 
         [0103]    According to the above third embodiment, the defect coordinate is added to the image-capturing recipe on the basis of the evaluation value of the defect, which enables fixed-point observation of the defect occurrence position determined to be an important defect on the basis of the defect evaluation value, and the defect observation position effective for the yield management can be obtained efficiently. When the wafer defect observation is performed with the image-capturing recipe for the fixed-point observation generated as described above, an occurrence tendency of the important defect can be monitored. 
         [0104]    The present invention has been hereinabove explained on the basis of the embodiments in a specific manner, but the present invention is not limited to the above embodiments, and it is to be understood that the present invention can be changed in various manners without deviating from the gist thereof. 
       REFERENCE SIGNS LIST 
       [0105]      101  . . . defect quantification device,  102  . . . defect observation device,  103  . . . communication means,  104  . . . input/output unit,  105  . . . overall control unit,  106  . . . storage unit,  107  . . . processing unit,  108  . . . input/output I/F,  109  . . . memory,  110  . . . image storage unit,  111  . . . bus,  112  . . . measurement recipe storage unit,  113  . . . defect image classification unit,  114  . . . measurement recipe selection unit,  115  . . . image measurement processing unit,  116  . . . defect quantification unit,  117  . . . wire pattern recognition unit,  118  . . . defect detection unit