Abstract:
Disclosed is a method of inspecting an object to be inspected in a semiconductor manufacturing process, for resolving the problem to increase defect detection sensitivity. An image capture means is used to image capture a designated area of the object to be inspected; a defect is detected in the captured image; a circuit pattern is recognized from the captured image; a characteristic value is computed, relating to an image tone and shape, from the detected defect; a characteristic value is computed, relating to the image tone and shape, from the recognized circuit pattern; either a specified defect or circuit pattern is filtered and extracted from the detected defect and the recognized circuit pattern; a mapping characteristic value is determined from the characteristic value of either the filtered and extracted specified defect or circuit pattern; and the distribution of the determined characteristic values is displayed onscreen in a map format.

Description:
TECHNICAL FIELD 
       [0001]    The present invention relates to a method of inspecting defects and circuit patterns on a sample using image obtaining means, and a device therefor. 
       BACKGROUND ART 
       [0002]    In order to ensure earnings in manufacturing of semiconductor wafers, it is important that manufacturing processes thereof are quickly established to promptly shift to a mass production system at a high yield rate. 
         [0003]    For this purpose, various inspection/measurement devices have been introduced in a production line. In order to promptly determine process conditions under which desired circuit patterns can be formed, for example, process conditions are intentionally changed to produce plural wafers or chips for inspection at the stage of process establishment, and are determined on the basis of the inspection result. On the other hand, wafers at the stage of mass production are inspected for the purpose of process monitoring. Namely, a wafer sampling inspection is performed during wafer production to check occurrence of defects on the surface of each wafer or to check circuit patterns formed on the surface of each wafer for abnormalities. In the case where defects or abnormalities of circuit patterns are detected as a result of the inspection, the cause is examined to take necessary measures. 
         [0004]    As a typical inspection device used at the stage of process establishment or mass production, an optical wafer inspection device is known. For example, Japanese Patent Application Laid-Open Publication No. 2000-97869 (Patent Literature 1) discloses a technique in which an optical image of a wafer surface is captured by bright-field illumination and is compared to an image of a good-quality area (for example, an image of the adjacent chip) to inspect defects. However, such an optical inspection device is affected by the wavelength of illumination, and the resolution limitation of the obtained image becomes about several hundred nanometers. Accordingly, for defects in the order of several dozen nanometers on a wafer, only the presence or absence thereof can be detected. In the case where the defects are analyzed in detail, a defect observer with higher image-capture resolution is additionally necessary. 
         [0005]    As a wafer inspection device other than the optical type, a scanning electron microscope (SEM)-type inspection device is known. The device performs an inspection in such a manner that an electron beam is irradiated onto an inspection area on a wafer, and an image obtained by detecting secondary electrons and the like generated therefrom is compared to an image of a good-quality area. Unlike the optical inspection device, image resolution can be increased to the order of nanometer in the SEM-type inspection device. In addition, a defect mode, such as conduction faults of contact holes exposed as electric potential on a wafer surface, that cannot be exposed in an optical image can be inspected. Japanese Patent Application Laid-Open Publication No. 2003-106829 (Patent Literature 2) describes a wafer inspection method by such an SEM-type wafer inspection device. 
         [0006]    It is important for a defect inspection device to process in a wide range at high speeds. Thus, the amount of image data is reduced by increasing the pixel size (namely, making the resolution lower) of an image to be obtained as much as possible, and the existence of defects can be confirmed from the detected low-resolution image can be confirmed, but the types of defects cannot be identified in detail in many cases. Accordingly, an observer is used. The observer is a device by which the coordinates of defects of a wafer are captured at high resolution using outputs of an inspection device to output an image. With the advanced miniaturization in a semiconductor manufacturing process, the size of defects accordingly reaches the order of several dozen nanometers. Thus, the resolution in the order of a few nanometers is necessary to observe defects in detail. 
         [0007]    Therefore, an observer (hereinafter, referred to as a review SEM) using a scanning electron microscope has been widely used in recent years. Automation of observing work has been desired in a semiconductor mass production line, and the review SEM is provided with an automatic defect review (ADR) function to automatically collect an image at the coordinates of defects in a sample. The coordinates of defects output from the inspection device contain errors, and the defects are detected again from an SEM image captured in a wide viewing field centering on the coordinates of defects output from the inspection device to capture the positions of the defects detected again at high resolution in the ADR. 
         [0008]    As a method of detecting defects from the SEM image, Japanese Patent Application Laid-Open Publication No. 2001-189358 (Patent Literature 3) describes a method of detecting defects in which an image obtained by capturing a region where a defect area and the same circuit patterns are formed is used as a non-defective image, and an image obtained by capturing the defect area is compared to the non-defective image. Further, Japanese Patent Application Laid-Open Publication No. 2007-40910 (Patent Literature 4) describes a method of detecting defects from one image obtained by capturing a defect area. 
         [0009]    Further, a pattern measurement device is used for a wafer inspection. As an example thereof, a CD-SEM (Critical-Dimension SEM: length measuring SEM) as an SEM-type pattern measurement device is known. The CD-SEM is a device for measuring the line widths of circuit patterns on a wafer at subnanometer measurement accuracy, and is particularly used for management of a semiconductor exposure process. A position to be measured, the template shapes (a line pattern, a hole pattern and the like) of circuit patterns to be measured, measurement items (a line width, a wiring pitch, the diameter of a hole pattern, and the like), and the like are registered in advance in a condition setting file referred to as a recipe. At the time of measurement, an electron beam is irradiated onto each measurement area, and secondary electrons generated therefrom are detected to obtain an image of circuit patterns of an inspection target. Then, a pattern to be measured is searched from the pattern image by pattern matching, and a processing algorithm for computing the set measurement items is applied to the searched pattern for pattern measurement. Japanese Patent Application Laid-Open publication No. 2003-59441 (Patent Literature 5) describes a pattern measurement method in the CD-SEM. 
       CITATION LIST 
     Patent Literature 
       [0000]    
       
         Patent Literature 1: Japanese Patent Application Laid-Open Publication No. 2000-97869 
         Patent Literature 2: Japanese Patent Application Laid-Open Publication No. 2003-106829 
         Patent Literature 3: Japanese Patent Application Laid-Open Publication No. 2001-189358 
         Patent Literature 4: Japanese Patent Application Laid-Open Publication No. 2007-40910 
         Patent Literature 5: Japanese Patent Application Laid-Open Publication No. 2003-59441 
       
     
       SUMMARY OF INVENTION 
     Technical Problem 
       [0015]    In order to improve the yield rate of semiconductor products, it is important that the cause of occurrence of fatal defects is specified to take measures. As means for specifying the cause of occurrence of fatal defects, it is important to recognize a trend of occurrence of the fatal defects in a wafer plane. However, with the miniaturization of patterns, the size of fatal defects is miniaturized. If the sensitivity of a defect inspection device is increased to detect minute defects, a manufacturing tolerance that is not originally a defect is detected, and it becomes difficult to understand a trend of occurrence of defects. 
         [0016]    Further, with the miniaturization of semiconductor manufacturing processes, manufacturing processes become complicated, and a wide variety of defects are generated. Further, at the time of establishing a mass production line, systematic defects are likely to frequently occur due to the shapes of circuit patterns and process conditions such as exposure, etching, polishing, and the like, other than defects such as foreign substance defects that are randomly generated. The cause of occurrence of random defects is different from that of systematic defects, and thus it is important to recognize a trend of occurrence of each defect in a wafer plane by discriminating the both from each other. Further, there are plural types of systematic defects (for example, short defects, open defects, and the like). In the case where the cause of occurrence differs depending on the types of defects, it is important to recognize a trend of occurrence in a wafer plane for each type of defect. The resolution is as low as several hundred nanometers in an optical inspection device, and thus it is difficult to discriminate the types of defects at high accuracy although the positions of defects can be specified. Thus, a high-accuracy image is obtained by an observer different from an inspection device, and it is necessary to classify according to the types of defects. 
         [0017]    Further, in order to obtain the margin of exposure conditions, a focal position and the amount of exposure at the time of exposure are changed in a wafer plane to quantify a trend of occurrence of defects or a trend of changes in the shapes of circuit patterns. These processes are performed in such a manner that defects are detected by an inspection device and the line widths are measured by the CD-SEM. 
         [0018]    Namely, in the case where fatal defects and non-fatal defects are mixed, or in the case where there are plural defects that are different in the reason for occurrence, it is necessary to confirm the frequency or trend of occurrence of only desired defects in a wafer plane or chip plane, and to visualize a trend of changes in the shapes of circuit patterns in a wafer plane or a chip plane. 
         [0019]    The present invention provides a method of visualizing a trend of occurrence of desired defects and a trend of changes in the various shapes of circuit patterns in a wafer plane. 
       Solution to Problem 
       [0020]    In order to address the problem, an aspect of the present invention provides an inspection method for inspecting an inspection target, the method including: capturing an image of a designated area of the inspection target using image capturing means; detecting defects from the captured image; recognizing circuit patterns from the captured image; computing characteristic values related to the grey value of the image and shapes from the detected defects; computing characteristic values related to the grey value of the image and shapes from the recognized circuit patterns; extracting specific defects or circuit patterns by filtering from the detected defects and recognized circuit patterns; determining characteristic values to be mapped among the characteristic values of the specific defects or circuit patterns extracted by filtering; and displaying a distribution of the determined characteristic values on a screen in a map format. 
         [0021]    Further, in order to address the problem, an aspect of the present invention provides a device for inspecting an inspection target, including: image capture which captures an image of a designated area of the inspection target; detector which detects defects from the captured image; recognizer which recognizes circuit patterns from the captured image; defect characteristic value computer which computes characteristic values related to the grey value of the image and shapes from the detected defects; circuit pattern characteristic value computer which computes characteristic values related to the grey value of the image and shapes from the recognized circuit patterns; extractor which extracts specific defects or circuit patterns by filtering from the defects detected by the detector and the circuit patterns recognized by the recognizer; characteristic value determiner which determines characteristic values to be mapped among the characteristic values of the specific defects or circuit patterns extracted by filtering by the extractor; and display unit which displays a distribution status of the characteristic values determined by the determiner on a screen in a map format. 
       Advantageous Effect of Invention 
       [0022]    According to the present invention, in the case where fatal defects and non-fatal defects are mixed, or in the case where there are plural defects that are different in the reason for occurrence, it is possible to confirm the frequency or trend of occurrence of only desired defects in a wafer plane or a chip plane. Further, it is possible to visualize a trend of changes in the shapes of circuit patterns in a wafer plane or a chip plane. 
     
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         [0023]      FIG. 1A  is a flow diagram for showing an outline flow of an inspection process according to a first embodiment. 
           [0024]      FIG. 1B  is a flow diagram for showing a detailed flow of the inspection process according to the first embodiment. 
           [0025]      FIG. 2  is a block diagram for showing an outline configuration of an inspection device according to the first embodiment. 
           [0026]      FIG. 3  is a coordinate system for showing an example of an image capture area designating method. 
           [0027]      FIG. 4  is a plan view of a wafer for showing an example of the image capture area designating method according to the first embodiment. 
           [0028]      FIG. 5  is a front view of an inspection condition setting screen according to the first embodiment. 
           [0029]      FIG. 6  is a flow diagram of a non-defective image producing process according to the first embodiment. 
           [0030]      FIG. 7  is an enlarged view of a chip for showing a setting example of an inspection region according to the first embodiment. 
           [0031]      FIG. 8  is a front view of an inspection region setting screen according to the first embodiment. 
           [0032]      FIG. 9  is a front view of a parameter setting screen of a defect detection process according to the first embodiment. 
           [0033]      FIG. 10  is a front view of a parameter setting screen of a circuit pattern recognition process according to the first embodiment. 
           [0034]      FIG. 11  is a flow diagram of a characteristic value computing process of a defect area according to the first embodiment. 
           [0035]      FIG. 12  is a flow diagram of a characteristic value computing process of a circuit pattern according to the first embodiment. 
           [0036]      FIG. 13  is a front view of a mapping condition designation screen according to the first embodiment. 
           [0037]      FIG. 14  is a front view of a part of a screen for showing an example of a display method of an inspection result according to the first embodiment. 
           [0038]      FIG. 15  is a front view of a part of a screen for showing an example of a display method of an inspection result according to the first embodiment. 
           [0039]      FIG. 16  is a front view of a part of a screen for showing an example of a display method of an inspection result according to the first embodiment. 
           [0040]      FIG. 17  is a front view of a part of a screen for showing an example of a display method of an inspection result according to the first embodiment. 
           [0041]      FIG. 18  is a flow diagram of a characteristic value aggregation process according to the first embodiment. 
           [0042]      FIG. 19  is a front view of a part of a screen for showing an example of a display method of an inspection result according to a second embodiment. 
           [0043]      FIG. 20  is a flow diagram of a characteristic value aggregation process according to the second embodiment. 
           [0044]      FIG. 21A  is a flow diagram for showing an outline flow of an inspection process according to a third embodiment. 
           [0045]      FIG. 21B  is a flow diagram for showing a detailed flow of the inspection process according to the third embodiment. 
           [0046]      FIG. 22  is a block diagram for showing an outline configuration of an inspection device according to the third embodiment. 
           [0047]      FIG. 23  is a flow diagram of an inspection condition automatic setting process according to the third embodiment. 
           [0048]      FIG. 24  is a diagram for showing a determination method of the inspection condition automatic setting process according to the third embodiment and a relation between image capture areas in a chip and characteristic value aggregating conditions. 
           [0049]      FIG. 25  is a front view of a screen related to designation of inspection conditions according to the third embodiment. 
           [0050]      FIG. 26  is a front view of a screen related to designation of inspection conditions according to the third embodiment. 
       
    
    
     DESCRIPTION OF EMBODIMENTS 
       [0051]    Hereinafter, a method of inspecting defects and circuit patterns using a scanning electron microscope will be described as an embodiment according to the present invention. 
       First Embodiment 
       [0052]      FIG. 2  shows a configuration diagram of an inspection device according to the present invention. In the device, an SEM  201  is connected to an inspection unit  202  via communication means  203 . The SEM  201  includes an electronic optical system column  204 , an SEM control unit  205 , a storing unit  206 , an input/output interface  207 , and an input/output terminal  208 . 
         [0053]    Further, the electronic optical system column  204  includes, in addition to a movable stage  210  that can be moved in an X-Y plane while mounting a sample wafer  209  thereon, an electron source  211  for irradiating an electron beam onto the sample wafer  209 , and detectors  212  for detecting secondary electrons and reflection electrons generated from the sample wafer, a deflector (not shown) for allowing an electron beam to scan on the sample wafer, and an image generating unit  213  that converts a signal from the detector  212  into a digital signal to generate a digital image. 
         [0054]    The storing unit  206  includes an image capture condition storing unit  214  that stores accelerating voltage, probe current, and an image capture viewing field size as image capture conditions of the SEM, an image storing unit  215  that saves obtained image data, and an image capture position information storing unit  216  that stores position information where the image was captured. 
         [0055]    The SEM control unit  205  is a unit to control processes of the SEM  201  such as obtaining an image. On the basis of an instruction from the SEM control unit  205 , the movable stage  210  is moved to allow a predetermined inspection area on the sample wafer  209  to be placed within an image capture viewing field, an electron beam is irradiated onto the sample wafer  209 , and data detected by the detectors  212  is converted into an image to be saved into the image storing unit  215 . Through the input/output terminal  208  configured using a keyboard, a mouse, a display, and the like, various instructions are issued and image capture conditions are designated by an operator. 
         [0056]    The inspection unit  202  is a unit to perform an inspection process for the captured image obtained by capturing the sample wafer  209  with SEM  201 . The inspection unit  202  includes an inspection-unit control unit  217  that controls the entire inspection unit  202 , an image processing unit  218  that performs various operations for an image to compute characteristic values, a filtering processing unit  219  that extracts a specific pattern from the computed characteristic values, a characteristic value aggregation processing unit  220  that aggregates the computed characteristic values, an inspection result display unit  221  that produces and displays a wafer map on the basis of the aggregated characteristic values, an inspection information storing unit  222  that stores various information necessary for the inspection process, an input/output interface  223  that has an interface function for sending and receiving data to/from the SEM-side, and an input/output terminal  224  by which conditions of various processes performed by the inspection unit  202  are input and an inspection result is displayed. 
         [0057]    The inspection information storing unit  222  includes an inspection region information storing unit  225  that stores a non-defective image necessary for the inspection process and information of the inspection region associated with the non-defective image, an image processing parameter storing unit  226  that stores various parameters necessary when performing operations for an image, a mapping condition storing unit  227  that stores filtering conditions for extracting a specific pattern from detected patterns and aggregating conditions of characteristic values necessary to generate a wafer map, and a characteristic value storing unit  228  that stores the computed characteristic values. Next, an inspection method using the inspection device shown in  FIG. 2  will be described. 
         [0058]    In the first place, an outline of the inspection method according to the present invention will be described using  FIG. 1A . 
         [0059]    First, an SEM image of the sample wafer  209  is obtained by the SEM  201  (S 11 ). Next, the obtained SEM image is processed by the inspection unit  202  to detect defects (S 12 ), and recognize circuit patterns in the SEM image (S 13 ). The defect detection process and the circuit pattern recognition process may be performed sequentially or in parallel.  FIG. 1A  shows a case of the parallel processing. Next, a filtering process is performed for the detected defect image and circuit pattern image to classify the defects and circuit patterns (S 14 ), and characteristic values are computed from the desired defect or circuit pattern image (S 15 ). A map is displayed based on the computed result (S 16 ), and the process is completed. 
         [0060]    Next, the processing flow described in  FIG. 1A  will be described in detail using  FIG. 1B . In the first place, the process corresponding to that of obtaining an SEM image (S 11 ) described in  FIG. 1A  will be described in detail. The sample wafer  209  as an inspection target is set on the stage  210  (S 101 ). Next, an image capture area of the inspection target wafer  209  is designated (S 102 ). The image capture area is generally referred to as a risk point. The risk point is susceptible to exposure conditions at the time of forming a circuit pattern and changes in process conditions, and the like, and is a point at which defects causing chip faults are likely to occur. The risk point can be predicted by a process simulator or the like. The image capture area may be designated as a point predicted to have a risk by the process simulator, or may be designated as a point assumed to have a risk from the experience of a user. Further, the image capture area may be arbitrarily designated other than the risk point. 
         [0061]    It should be noted that since a plurality of the same circuit patterns are formed in every chips on a semiconductor wafer, in case an object of the inspection is to evaluate occurrence of defects in the wafer and changes in shapes of the circuit patterns, it is not always necessary to inspect all the chips. Therefore, coordinates to be used in image capturing are represented as chip coordinates as shown in  FIG. 3 , and chips whose images are captured may be selected as shown in  FIG. 4 . 
         [0062]    Next, an SEM image at a designated area is obtained by the SEM  201  (S 103 ). The SEM control unit  205  reads image capture conditions (for example, accelerating voltage, probe current, and the number of additional frames) from the image capture condition storing unit  214  to control the stage  210  to the position where an image of the designated area can be captured. Then, an electron beam irradiated from an electron gun  211  is allowed to scan in an image capture viewing field, and secondary electrons and reflection electrons generated from the sample  209  are detected by the detectors  212 . Thereafter, analog signals output from the detectors  212  are converted into digital signals by the image generating unit  213  and the image is saved into the image storing unit  215 . 
         [0063]    It should be noted that a few micron meters of movement errors of the stage  210  occur, and thus there is a problem that the designated area is different from the area whose image is actually captured. In order to address the problem, as described in Patent Literature 5, an image of the designated area may be captured by beam shifting after an image of a predetermined unique circuit pattern existing around the designated area is captured and is aligned by pattern matching. 
         [0064]    After the image obtaining is completed, the obtained image is processed to perform inspection by the inspection unit  202 . The inspection-unit control unit  217  obtains the image captured by the SEM  201  through the input/output interface  223 , and the obtained image is displayed on the input/output terminal  224 .  FIG. 5  shows a GUI  500  (hereinafter, described as an inspection condition setting GUI  500 ) for designating inspection conditions, and includes an obtained image display region  501  in which a list of obtained images is displayed. 
         [0065]    Next, among plural captured images displayed in the obtained image display region  501  of the inspection condition setting GUI  500 , a non-defective image is designated (S 104 ). The non-defective image is used to detect defects from the captured image of the object to be inspected by comparison inspection. Thus, the non-defective image should be an image in which patterns are formed as expected, and no defects are contained. In a general inspection at a mass production line after a manufacturing process is established, it is conceivable that a non-defective image is included in the captured images. For example, a circuit pattern is correctly formed at the central part of a wafer. However, in the case where the focus point is deviated in the exposure process due to the effects of the warpage of the wafer and the pattern becomes thinner at the outer periphery of the wafer, the captured image of the central part of the wafer may be designated as a non-defective image. In this case, the non-defective image is selected from the list of images of the inspection condition setting GUI, and a registration button  502  is clicked to complete the designation. 
         [0066]    The above description is a case in which there is an ideal area (an area at which no defects are contained and a pattern is normally formed) of the wafer plane in the captured non-defective image. However, there is no ideal image capture area in some cases, such as when establishing a mass production line or providing process conditions. 
         [0067]    In such a case, a non-defective image is produced by compounding from plural captured images to enable the inspection. Plural images used in composition are selected from the list of images of the inspection condition setting GUI, and a compound button  502  is clicked, so that a composition process is executed. At the time of composition, images with the same layout of circuit patterns are used. If coordinates in chips are the same in a semiconductor wafer, the layout of circuit patterns is the same. Thus, it is only necessary to perform the composition process for each coordinate in the chip. 
         [0068]    A flow of the composition process is shown in  FIG. 6 . In the first place, plural images are aligned (S 601 ). The stage is moved to the designated area in the SEM  201  to measure stage movement errors, and a scanning range of the electron beam is determined on the basis of the measured result to obtain an image. Thus, high-accuracy positioning can be performed. However, it is general that image capture positions are slightly different between the images due to errors occurring when measuring the stage movement errors. Accordingly, alignment is performed by an image process in which the circuit patterns in the images are overlapped. 
         [0069]    Next, an average image with an average gray value is produced from plural images (S 602 ). The average value of each pixel is computed, so that the gray value at a defect area is averaged by pixels at a normal area and an image in which defects are not exposed can be produced. Further, the non-defective image can be stored, as a new name, into the image storing unit  215  by clicking a save button  504 , and can be read from the image storing unit  215  by clicking a read button  505  while designating the name. Accordingly, an image captured on a different wafer can be designated as a non-defective image. 
         [0070]    Next, inspection region information is set (S 105 ). The inspection region information is information of a region that is defined in a viewing field of the non-defective image by a user, and is used as conditions at the time of filtering.  FIG. 7  shows a setting example of the inspection region information. In the example of  FIG. 7 , a non-defective image  701  contains circuit patterns with different structures in the vertical and horizontal directions. In the case where, for example, it has been found that the reasons for occurrence of the defects are different depending on the circuit patterns in the vertical and horizontal directions, it is important to produce a wafer map in which the number of defects is plotted in accordance with the direction of the circuit pattern. 
         [0071]    Accordingly, in the case where a region A ( 702 ) is set at the circuit pattern region in the vertical direction and a region B ( 703 ) is set at the circuit pattern region in the horizontal direction as shown in  FIG. 7 , only the defects of the region A ( 702 ) and the region B ( 703 ) can be extracted if a filtering process, to be described later, is used. A GUI for setting the inspection region information is shown in  FIG. 8 . The GUI is called by clicking a region setting button  503  of the inspection condition setting GUI ( FIG. 5 ). 
         [0072]    The GUI is configured using an interface  801  for displaying the non-defective image set in S 104 , an interface  802  for adding or deleting the region information, and various tool buttons  803  for defining the regions. A user selects an appropriate shape setting tool from the tool buttons in accordance with the shape of the region to be defined, and defines the region by designating coordinates on the non-defective image using a mouse or the like. It should be noted that a method of defining the region may be one other than focusing attention on the directions of the circuit patterns. For example, a memory cell part and a logic part may be separately designated, or a pattern region for a test or a dummy pattern region may be designated. 
         [0073]    Next, image processing parameters for “defect detection” and “circuit pattern recognition” are set and adjusted (S 106 ). Each of  FIG. 9  and  FIG. 10  shows a GUI for adjusting the image processing parameters, and is displayed by clicking a parameter setting button  506  on the inspection condition setting GUI ( FIG. 5 ). Parameter adjustment screens related to “defect detection” and “circuit pattern recognition” can be switched and displayed by using tabs on the image processing parameter adjustment GUI, and  FIG. 9  shows a state in which the tab for the parameter adjustment screen related to “defect detection” is being selected. The defect detection parameter adjustment screen includes interfaces ( 901  to  903 ) for displaying a non-defective image, an inspected image, and an image of a defect detection result, and an interface  904  for changing a defect detection algorithm or adjusting the value of the parameter. 
         [0074]    In  FIG. 9 , regions extracted as defects are displayed using white as the defect detection result. It should be noted that regions detected as defects on the inspected image may be highlighted by changing the display color thereof. Further, in the case where the defect detection algorithm or the value of the parameter is adjusted, a defect detection process may be executed to reflect the result on the display of the GUI. Accordingly, the result of adjusting the parameter can be confirmed in real-time, and the parameter can be easily adjusted. 
         [0075]      FIG. 10  shows a state in which the tab for the parameter adjustment screen related to “circuit pattern recognition” is being selected among the image processing parameter adjustment screens. As similar to the parameter adjustment screen of “defect detection”, provided are interfaces ( 1001  to  1003 ) for displaying a non-defective image, an inspected image, and an image of a circuit pattern recognition result, and an interface  1004  for changing a circuit pattern recognition algorithm and adjusting the value of the parameter. 
         [0076]    In  FIG. 10 , circuit pattern regions recognized as a result of recognizing a circuit pattern are displayed using white, and base regions are displayed using black. Further, in the case where the circuit pattern recognition algorithm or the value of the parameter is adjusted, a circuit pattern recognition process may be executed to reflect the result on the display of the GUI. Information of the values of the parameters related to “defect detection” and the “circuit pattern recognition” process set as described above and the selected algorithm is stored in the image processing parameter storing unit  226 . 
         [0077]    Next, the processes corresponding to the defect detection (S 12 ) and the circuit pattern recognition (S 13 ) described in  FIG. 1A  will be described in detail. 
         [0078]    When a process execution button  507  on the inspection condition setting GUI  500  shown in  FIG. 5  is clicked, a defect detection process (S 107 ), a circuit pattern recognition process (S 108 ), a defect characteristic value computing process (S 109 ), and a circuit pattern characteristic value computing process (S 110 ) are executed for the inspected image by the image processing unit  218 . In this case, the defect detection process (S 107 ) and the circuit pattern recognition process (S 108 ) are independently executed. Thus, these processes may be executed in parallel. The processing time can be shortened by executing in parallel. 
         [0079]    The defect detection process (S 107 ) is a process in which defect areas are detected from the inspected image of the sample wafer  209  obtained by the SEM  201 . As a method of detecting defects, a method of detecting defect areas by comparing a non-defective image and an inspected image to each other may be used. As an example of the comparison method, Patent Literature 3 describes an example in which a difference between a non-defective image and an inspected image is calculated after being aligned, and regions where the value of the difference is a certain value or larger are detected as defects. Further, defects may be detected from one inspected image without using the non-defective image. As an example of the method, Patent Literature 4 describes an example of detecting defects in which the repeated periodicity of circuit patterns contained in an inspected image is used to estimate a non-defective image. 
         [0080]    The circuit pattern recognition process (S 108 ) is a process in which circuit patterns are detected from the non-defective image and the inspected image. The circuit patterns in this case mean structures configured on a semiconductor wafer, such as wirings, holes, and semiconductor elements. As a method of recognizing the circuit patterns, the following methods may be used. An area where a grey value is drastically changed in an image is extracted as the outline of a circuit pattern, and an inner region of the circuit pattern is specified and recognized on the basis of the grey value and the changing direction thereof. Alternatively, a region of a circuit pattern is recognized on the basis of a grey value in an image. Further, a circuit pattern in an image may be recognized using design information in which layout information of the circuit pattern of a semiconductor product as an inspection target is described. 
         [0081]    Next, characteristic values related to the brightness, shape, position, and the like of each of the detected defects and the recognized circuit patterns are computed (S 109  and S 110 ). 
         [0082]      FIG. 11  shows a method of computing the defect characteristic values (S 109 ). In the defect characteristic value computing process, a non-defective image  1101 , an inspected image  1102 , a defect detection result, and inspection region information  1104  set in S 104  are input to compute the characteristic values of each of the detected defects ( 1105 ). In the example of  FIG. 11 , four defects are detected, and the characteristic values of each defect are computed ( 1106 ). 
         [0083]      FIG. 12  shows a method of computing the circuit pattern characteristic values (S 110 ). As similar to the defect characteristic value computing process, a non-defective image  1201 , an inspected image  1202 , a circuit pattern recognition result  1203 , and inspection region information  1204  are input to compute the characteristic values of each of the recognized circuit patterns ( 1205 ). For example, in the case where n circuit patterns are extracted, the characteristic values of each of the n circuit patterns are computed ( 1206 ). It should be noted that the types of characteristic values computed in the defect characteristic value computing process and the circuit pattern characteristic value computing process may be different from each other. 
         [0084]    Next, filtering conditions and characteristic value aggregating conditions are set on a wafer map GUI  1300  shown in  FIG. 13  (S 111  to S 116 ) to produce a wafer map. The GUI  1300  includes an interface  1301  for setting the filtering conditions, an interface  1302  for confirming a filtering result, an interface  1303  for setting the characteristic value aggregating conditions, an interface  1304  for displaying the produced wafer map, and an interface  1305  for displaying a histogram of the aggregated characteristic values. Further, both of the set filtering conditions and characteristic value aggregating conditions are used as mapping conditions, and the mapping conditions are saved, as a new name, into the storing unit by clicking a save button  1306 . Then, the saved mapping conditions can be read by clicking a read button  1307  while designating the name. 
         [0085]    Next, the process corresponding to the filtering (S 14 ) described in  FIG. 1A  will be described in detail. 
         [0086]    In the first place, filtering conditions are set (S 111 ). The filtering is performed to extract only specific defects or circuit patterns from the plural types of defects and circuit patterns contained in an image. For example, in the case where short defects and open defects are mixed in an image and the reasons for occurrence of the defects are different, it is important to separately aggregate the numbers. Accordingly, for example, only the open defects are extracted by the filtering, and a trend of occurrence of the defects in the wafer can be confirmed. On the filtering condition setting interface  1301 , “defect” or “circuit pattern” is selected as the designation of the filtering conditions. 
         [0087]    Next, conditions for the computed characteristic values are designated. As a method thereof, for example, one or more condition expressions are set for the characteristic values, and a method of combining the conditions may be set. For example, in the case where only the short defects are to be extracted, conditions such as “the number of adjacent circuit patterns ≧2” and “the brightness of the defect part=the brightness of the circuit pattern” may be set. 
         [0088]    The filtering conditions are set by combining the plural condition expressions as described above. Thus, the interface  1301  for setting the filtering conditions includes an interface  13011  for designating the inspection region set in S 104 , an interface  13012  for defining the condition expressions for the characteristic values, and an interface  13013  for defining the method of combining the defined condition expressions using a logical expression. 
         [0089]    It should be noted that other than the method of combining the conditions for each of the characteristic values, filtering may be performed by a method of setting a threshold value for each of characteristic values represented by the linear sum of the characteristic values, or filtering may be performed by setting a non-linear identifying plane in a characteristic value space with each characteristic value used as a base. Further, in the case where the filtering conditions are set or changed, the inspection-unit control unit  217  uses the filtering processing unit  219  to determine whether or not each of the extracted defects or circuit patterns matches the conditions (S 112 ). 
         [0090]    The inspection-unit control unit  217  reflects the result on the filtering result confirmation interface  1302  of the GUI  1300 . As a method of displaying the filtering result, the defects or circuit patterns extracted by the filtering may be highlighted with frames, or the defects or circuit patterns that are extracted and the defects or circuit patterns that are not extracted may be displayed using different colors. Accordingly, the filtering conditions can be set while checking the result, and the conditions can be easily set. 
         [0091]    Next, the process corresponding to the characteristic value computation/aggregation (S 15 ) described in  FIG. 1A  will be described in detail. 
         [0092]    In the first place, the aggregating conditions of the characteristic values are set (S 113 ). The aggregation of the characteristic values is a process in which the characteristic values displayed on the wafer map  1304  are computed from the characteristic values of the defects or circuit patterns extracted by the filtering. In the defect characteristic value computing step S 109  or the circuit pattern characteristic value computing step S 110  described above, the characteristic values are computed for each of the extracted defects and circuit patterns. However, it is occasionally necessary to compute the characteristic values for one chip when displaying on the wafer map  1304 , and it is necessary to compute the characteristic values to be mapped from plural defects or circuit patterns in one chip. 
         [0093]    The aggregating conditions of the characteristic values are set on the interface  1303  for setting characteristic value aggregating conditions. First, as aggregation characteristic values  13031 , characteristic values to be mapped are set among the computed characteristic values. Next, as an aggregation method  13032 , one of “average/total/standard deviation/maximum value/minimum value” is selected. For example, in the case where the average line width of the circuit patterns in the plane is to be computed, “line width” may be selected as the aggregation characteristic values  13031 , and “average” may be selected as the aggregation method  13032 . Further, if “standard deviation” is selected as the aggregation method  13032 , variations in the line widths of the circuit patterns in the plane can be displayed on the wafer map  1304 . In the case where the characteristic value aggregating conditions  13031  are set or changed, the inspection-unit control unit  217  uses the characteristic value aggregation processing unit  220  to compute the characteristic values for each chip as shown in  FIG. 18  from the computed characteristic values on the basis of the set characteristic value aggregating conditions (S 114 ). The computed characteristic values are saved in the characteristic value storing unit  228  (S 115 ) to be used for display of the wafer map  1304  (S 116 ). 
         [0094]    When the characteristic value aggregation process (S 114 ) is completed, display of the wafer map  1304  and the characteristic value histogram  1305  in  FIG. 13  is updated. The wafer map  1304  is used to express the magnitudes of the characteristic values. For example, the magnitudes may be represented by changing a display color  1401  as shown in  FIG. 14 , by changing the size  1501  of a drawing as shown in  FIG. 15 , or by using a three-dimensional graph as shown in  FIG. 16 . 
         [0095]    If the characteristic value aggregation process (S 114 ) is finished and the update of the display of the wafer map  1304  and the characteristic value histogram  1305  is completed, the wafer as an inspection target is unloaded (S 117 ) to complete a series of operations. 
         [0096]    Further, the inspection device according to the present invention includes a display-by-condition GUI  1700  for displaying on the input/output terminal  224  the aligned wafer maps produced under plural mapping conditions ( FIG. 17 ). If an addition-of-condition button  1701  on the display-by-condition GUI  1700  is clicked and the name of the saved mapping conditions is selected, the corresponding mapping conditions are read to produce a wafer map, and a list of wafer maps is displayed on an interface  1702 . Further, the GUI  1700  includes an interface  1703  for comparing the number of defects or circuit patterns matching the filtering conditions under different mapping conditions to be displayed. Thus, for example, the numbers of short defects and foreign substance defects can be compared to each other. 
         [0097]    In the embodiment, there has been described a method in which defects or circuit patterns are extracted from a captured image, the characteristic values thereof are computed, only the defects or circuit patterns designated by a user are extracted by a filtering process, and the characteristic values designated by the user are displayed on a wafer map. 
       Second Embodiment 
       [0098]    In the first embodiment, there has been described the inspection method in which the characteristic values are displayed on the wafer map as an inspection result. In the second embodiment, there will be described an inspection method in which a trend of changes relative to the number of generated defects and the shapes of circuit patterns in a chip is visualized by mapping the characteristic values for each image capture area in the chip as shown in  FIG. 19 . 
         [0099]    An inspection flow according to the embodiment is the same as those of  FIG. 1A  and  FIG. 1B  described in the first embodiment, and the configuration of a device is the same as that of  FIG. 2 . However, the aggregation method of the characteristic values in S 114  and the display method in S 116  are different. Only a point different from the first embodiment will be described below. 
         [0100]    When aggregating the characteristic values in S 114 , the characteristic values are aggregated for each chip as shown in  FIG. 18  in the first embodiment. In the second embodiment, the characteristic values are aggregated for each image capture area in a chip as shown in  FIG. 20 . The designating method of the characteristic value aggregation method is the same as that in the first embodiment. 
         [0101]    Further, the magnitudes of the characteristic values are expressed by changing display colors in  FIG. 19 . However, as similar to the case of the first embodiment, for example, the magnitudes of the characteristic values may be expressed by changing the size of a drawing as shown in  FIG. 15 , or by using a three-dimensional graph as shown in  FIG. 16 . 
       Third Embodiment 
       [0102]    In each of the first embodiment and the second embodiment, there has been described the inspection method in which a trend of occurrence of defects and a trend of changes in the shapes of circuit patterns on a wafer or in a chip are visualized by displaying the computed characteristic values on the basis of the mapping conditions designated by a user. In the case where the number of computed characteristic values is several tens to several hundreds, it becomes difficult to set conditions of producing a map by which a trend of fatal defects or circuit patterns can be recognized. Here in the third embodiment, a method of automatically computing candidates of mapping conditions will be described. 
         [0103]    First, an outline of an inspection method in the third embodiment will be described using  FIG. 21A . First of all, an SEM image of the sample wafer  209  is obtained by the SEM  201  (S 21 ). Next, the obtained SEM image is processed by the inspection unit  202  to detect defects (S 22 ), and recognize circuit patterns in the SEM image (S 23 ). The defect detection process and the circuit pattern recognition process may be performed sequentially or in parallel.  FIG. 21A  shows a case of the parallel processing. These steps of the flow are the same as those of the first embodiment described in  FIG. 1A . Next, conditions of mapping the detected defect image and circuit pattern image are set (S 24 ), and characteristic values are computed from a desired image of defects or circuit patterns to be saved (S 25 ). The computed characteristic values are displayed on a map on the basis of the set mapping conditions (S 26 ), and the process is completed. 
         [0104]    Next, the flow of the processes described in  FIG. 21A  will be described in detail using  FIG. 21B . 
         [0105]    S 2101  to S 2110  in the processing flow shown in  FIG. 21B  are the same as S 101  to S 110  in the processing flow shown in  FIG. 1B  of the inspection method in the first embodiment and the second embodiment as described above. 
         [0106]    Next, the process (S 24 ) of setting the conditions of mapping the detected defect image and circuit pattern image will be described. In the inspection method according to the third embodiment, the characteristic values of defects are computed in S 2109  and the characteristic values of circuit patterns are computed in S 2110 . Thereafter, the mapping condition candidates are automatically computed (S 2111 ). Next, it is determined by a user whether or not there exists a map representing a desired trend of changes in the wafer in-plane among the automatically-computed mapping condition candidates (S 2112 ). If the map exists, the conditions are selected (S 2113 ). If not, the mapping conditions are designated again (S 2114 ). It should be noted that the designation of the mapping conditions in S 2114  is the same as the designation (S 111  to S 114 ) of the mapping conditions in the first embodiment and the second embodiment. 
         [0107]    Next, the computed characteristic values are saved (S 2115 ) to display a map (S 2116 ), and the wafer as an inspection target is finally unloaded (S 2117 ). The steps of S 2115  to S 2117  are the same as those of S 115  to S 117  in the first embodiment and the second embodiment. 
         [0108]    A device configuration according to the third embodiment is shown in  FIG. 22 . The device configuration shown in  FIG. 22  is characterized in that a mapping condition candidate computing unit  2201  is provided in addition to the device configuration according to the first embodiment and the second embodiment. In the device configuration shown in  FIG. 22 , the same reference numerals are given to constitutional elements same as those shown in  FIG. 2 . 
         [0109]    A flow of an automatic computing method of mapping condition candidates in S 2111  processed by the mapping condition candidate computing unit  2201  will be described using  FIG. 23 . First, defects or circuit patterns to be extracted are designated on a GUI  2500  shown in  FIG. 25  (S 2301 ). In  FIG. 25 , provided is an interface  2503  on which one or more types of defects to be extracted can be defined using input means such as a mouse on an inspected image. 
         [0110]    In  FIG. 25 , the reference numeral  2501  denotes an interface on which an inspected image and a defect detection result are displayed and selected defects are displayed while being highlighted. The selected defects are displayed by changing the display colors of the extracted defect areas or the selected defects on the inspected image, or displayed with frames. A user selects a pattern selection tool  2502  and clicks a defect to be extracted on the image  2501 . It should be noted that plural types of defects to be extracted can be selected, and can be added and deleted on the interface  2503 .  FIG. 25  shows a selection method related to defects. However, circuit patterns can be designated by the similar method. 
         [0111]    Next, candidates of filtering conditions for extracting only the designated defects or circuit patterns are computed (S 2302 ). As a method, for example, a threshold value for separating patterns that are to be extracted from patterns that are not to be extracted is independently computed for each characteristic value, or an identifying plane for separating patterns that are to be extracted from patterns that are not to be extracted in a characteristic value space is computed using a conventional supervised learning method. 
         [0112]    Next, candidates of characteristic value aggregating conditions are computed for each filtering condition (S 2303 ). As a method thereof, for example, wafer maps for all the characteristic value aggregating conditions for each image capture area in a chip are produced as shown in  FIG. 24 , and characteristic value aggregating conditions in which the similar trend of changes can be observed irrespective of image capture areas may be obtained. 
         [0113]    In the example of  FIG. 24 , the similar trend of changes can be observed in a characteristic value aggregating condition  1  irrespective of image capture areas. However, the trend of the wafer map is changed depending on image capture areas in a characteristic value aggregating condition  2 . In the case of the characteristic value aggregating conditions representing a trend of changes in the wafer in-plane, the trend of the wafer map is not changed depending on image capture areas, and the characteristic value aggregating conditions in which the trend of the wafer map is changed depending on image capture areas are excluded from the candidates. It should be noted that the similarity of the wafer map can be quantified by computing a correlation coefficient. 
         [0114]    A GUI  2600  for confirming the mapping condition candidates produced in S 2112  is shown in  FIG. 26 . First, a user selects one or more defects or circuit patterns designated on the interface  2503  of the GUI  2500  of  FIG. 25  from an interface  2601 . Next, one of the automatically-set filtering condition candidates is selected using an interface  2602 , and the filtering conditions and the filtering result are confirmed using interfaces  2603  and  2604 . An interface  2605  is an interface for displaying the wafer maps produced using the automatically-set characteristic value aggregating condition candidates, and a user selects characteristic value aggregating conditions from the interface  2605  to obtain a desired wafer map. 
       INDUSTRIAL APPLICABILITY 
       [0115]    The present invention is used in processes of inspecting circuit patterns formed on a semiconductor wafer using image obtaining means in a production line of semiconductor wafers. 
       REFERENCE SINGS LIST 
       [0000]    
       
           201  . . . SEM 
           202  . . . inspection unit 
           205  . . . SEM control unit 
           206  . . . storing unit 
           207  . . . input/output interface 
           208  . . . input/output terminal 
           217  . . . inspection-unit control unit 
           218  . . . image processing unit 
           219  . . . filtering processing unit 
           220  . . . characteristic value aggregation unit 
           221  . . . inspection result display unit 
           222  . . . inspection information storing unit 
           223  . . . input/output interface 
           224  . . . input/output terminal