CN107144210A - Method for measuring line width and roughness of electron microscopic image - Google Patents
Method for measuring line width and roughness of electron microscopic image Download PDFInfo
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- CN107144210A CN107144210A CN201710279359.0A CN201710279359A CN107144210A CN 107144210 A CN107144210 A CN 107144210A CN 201710279359 A CN201710279359 A CN 201710279359A CN 107144210 A CN107144210 A CN 107144210A
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- 238000000034 method Methods 0.000 title claims abstract description 82
- 238000009826 distribution Methods 0.000 claims abstract description 68
- 238000000635 electron micrograph Methods 0.000 claims description 20
- 238000004458 analytical method Methods 0.000 claims description 17
- 230000003595 spectral effect Effects 0.000 claims description 15
- 238000004626 scanning electron microscopy Methods 0.000 claims description 10
- 238000012545 processing Methods 0.000 claims description 8
- 238000013459 approach Methods 0.000 claims description 4
- 238000009795 derivation Methods 0.000 claims description 3
- 238000001914 filtration Methods 0.000 claims description 3
- 238000007689 inspection Methods 0.000 claims description 3
- 238000012216 screening Methods 0.000 claims 1
- 238000005259 measurement Methods 0.000 abstract description 25
- 230000000694 effects Effects 0.000 abstract description 4
- 238000012935 Averaging Methods 0.000 abstract 1
- 238000000609 electron-beam lithography Methods 0.000 description 12
- 238000005530 etching Methods 0.000 description 6
- 238000010894 electron beam technology Methods 0.000 description 3
- 238000000691 measurement method Methods 0.000 description 3
- 238000001259 photo etching Methods 0.000 description 3
- 230000007547 defect Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000000605 extraction Methods 0.000 description 2
- 238000003384 imaging method Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 239000000758 substrate Substances 0.000 description 2
- 229910000577 Silicon-germanium Inorganic materials 0.000 description 1
- 238000012512 characterization method Methods 0.000 description 1
- 238000005520 cutting process Methods 0.000 description 1
- 125000004122 cyclic group Chemical group 0.000 description 1
- 239000003989 dielectric material Substances 0.000 description 1
- 230000003628 erosive effect Effects 0.000 description 1
- 238000009499 grossing Methods 0.000 description 1
- 230000004807 localization Effects 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 238000004377 microelectronic Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000005693 optoelectronics Effects 0.000 description 1
- 229920002120 photoresistant polymer Polymers 0.000 description 1
- 238000012827 research and development Methods 0.000 description 1
- 238000004439 roughness measurement Methods 0.000 description 1
- 238000001878 scanning electron micrograph Methods 0.000 description 1
- 238000010187 selection method Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000001039 wet etching Methods 0.000 description 1
Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B7/00—Measuring arrangements characterised by the use of electric or magnetic techniques
- G01B7/02—Measuring arrangements characterised by the use of electric or magnetic techniques for measuring length, width or thickness
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B7/00—Measuring arrangements characterised by the use of electric or magnetic techniques
- G01B7/34—Measuring arrangements characterised by the use of electric or magnetic techniques for measuring roughness or irregularity of surfaces
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- General Physics & Mathematics (AREA)
- Length-Measuring Devices Using Wave Or Particle Radiation (AREA)
- Analysing Materials By The Use Of Radiation (AREA)
Abstract
The invention belongs to the technical field of scanning electron microscopic measurement, and discloses a method for measuring line width and roughness of an electron microscopic image, which comprises the following steps: obtaining a scanning electron microscopic image of a line structure to be detected; intercepting a first area; carrying out averaging treatment along the line direction to obtain a line edge pixel distribution curve; determining a first boundary area according to the line edge pixel distribution curve; analyzing local pixels to obtain boundary distribution; and calculating the width and the roughness of the line to be detected according to the boundary distribution, and extracting the width and the roughness value of the line to be detected. The invention solves the problems that the workload of measuring the width and the roughness of the line is large, the measurement error caused by human intervention exists, and only a limited number of data points can be analyzed in the prior art, and achieves the technical effects of improving the accuracy and the reliability of measurement and saving the actual measurement time and cost of an engineer.
Description
Technical field
The present invention relates to scanning electron microscopy field of measuring technique, more particularly to a kind of electron micrograph image line thickness and
The measuring method of roughness.
Background technology
In fields such as microelectronics, photoelectron, MEMS, accurate measurement line thickness and roughness be one it is very important should
With.Especially for some situations, micro-nano device structure includes very serious Electronic beam intensity distribution, such as front layer figure
Layer, which has pair cross-section after figure has considerable influence, or section to electron beam patterning, to carry out electron beam patterning and assesses along height side
Had a strong impact on to Electronic beam distribution during line thickness by height and position, these phenomenons cause wide in measurement lines
There is major defect when spending.
When existing technology is such issues that processing, it usually needs the specified adjustment location of engineer avoids the shadow of background graphics
Ring, or different zones use independent parameter value, these methods bring larger workload, and can only analyze finite number
Strong point, and there is the measurement error that human intervention is caused.
The content of the invention
The embodiment of the present application is solved by providing the measuring method of electron micrograph image line thickness and roughness a kind of
Measurement line thickness and roughness workload is larger in the prior art, there is measurement error that human intervention causes and can only analyze
The problem of finite number strong point.
The embodiment of the present application provides the measuring method of a kind of electron micrograph image line thickness and roughness, including：Obtain
The scanning electron microscopy picture of linear to be measured；
Intercept first area；
Image in the first area is carried out along line orientations handling averagely, obtain line edge pixel distribution bent
Line；
According to the line edge pixel distribution curve, the first borderline region is determined；
Local pixel analysis is carried out to the image in first borderline region, border distribution is obtained；
It is distributed according to the border, calculates the width and roughness of the lines to be measured, extract the width of the lines to be measured
Number of degrees value and roughness value.
It is preferred that, after the scanning electron microscopy picture for obtaining linear to be measured, in addition to：It is determined that laterally and
Actual physics length representated by each pixel of longitudinal direction.
It is preferred that, the first area is not comprising the following region of any one or more：Scale, mark and non-interesting
Region.
It is preferred that, it is described according to the line edge pixel distribution curve, the first borderline region is determined, including：
Region in the range of the selection extreme value of pixel first is used as basic borderline region；
The first width is expanded to the basic frontier district is overseas, the basic borderline region and first width constitute institute
State the first borderline region.
It is preferred that, the first extreme value of pixel scope is the 20%~80% of pixel extreme value correspondence width.
It is preferred that, described according to the line edge pixel distribution curve, determine after the first borderline region, also wrap
Include：
To the line edge pixel distribution curve derivation, the maximum of slope absolute value is obtained, with first border
Region carries out common factor inspection, exclusive PCR region.
It is preferred that, the image in first borderline region carries out local pixel analysis, obtains border distribution, bag
Include：
Select border localized area scope；
Screen or remove unreasonable pixel；
To equalize the maximum value minimum of local area as according to calculating boundary position.
It is preferred that, the border localized area scope is covering at least one pixel region, the side along in line orientations
Boundary's localized area scope includes 1/2nd of pixel in the maximum pixel number along line orientations no more than background useful information.
It is preferred that, it is described to screen or remove unreasonable pixel, including：
It is whether obvious along lines distribution arrangement equalization local pixel value, or the isolated pixel value of addition filtering algorithm analysis
Method for independent noise, or use best-fitting of the curve carries out data processing, to screen or remove unreasonable pixel.
It is preferred that, the line thickness and the method for roughness of calculating includes：Normal scatter analytic approach, or power spectral density
Analytic approach.
The one or more technical schemes provided in the embodiment of the present application, have at least the following technical effects or advantages：
In the embodiment of the present application, the method being combined using borderline region and local scope, the former is by along lines side
To handling averagely, line edge pixel distribution curve is obtained, it is then determined that the first borderline region, so as to effectively define border
Scope；The latter obtains border distribution, so that by setting rational local scope to effectively reduce the back of the body by local pixel analysis
Scene element influence, makes boundary alignment more accurate.The inventive method can effectively reduce existing method it is determined that electron beam patterning
Limitation during figure, improves the accuracy and reliability of measurement, and dramatically saves on time of the actual measurement of engineer with
Cost.
Brief description of the drawings
In order to illustrate more clearly of the technical scheme in the present embodiment, used required in being described below to embodiment
Accompanying drawing is briefly described, it should be apparent that, drawings in the following description are one embodiment of the present of invention, for this area
For those of ordinary skill, on the premise of not paying creative work, other accompanying drawings can also be obtained according to these accompanying drawings.
Fig. 1 is the stream of the measuring method of a kind of electron micrograph image line thickness provided in an embodiment of the present invention and roughness
Cheng Tu；
Fig. 2 is the SEM image in the embodiment of the present invention one and its SEM average gray distribution curves along line orientations.
Fig. 3 is that the line edge distribution that the embodiment of the present invention one is obtained using original fixed pixel threshold measurement method is bent
Line, and the line edge distribution curve obtained using the inventive method.
Fig. 4 is that the line thickness roughness power spectral density distribution that the embodiment of the present invention one is obtained using original method is bent
Line, and the line thickness roughness power spectral density distribution curve obtained using this method.
Fig. 5 is SEM overhead view images comprising double-layer structure in the embodiment of the present invention two and its along X and the gray scale of Y-direction
Average value distribution curve.
Fig. 6 is that the line edge distribution that the embodiment of the present invention two is obtained using original fixed pixel threshold measurement method is bent
Line, and the line edge distribution curve obtained using the inventive method.
Fig. 7 is that the line thickness roughness power spectral density distribution that the embodiment of the present invention two is obtained using original method is bent
Line, and the line thickness roughness power spectral density distribution curve obtained using this method.
Embodiment
The embodiment of the present application is solved by providing the measuring method of electron micrograph image line thickness and roughness a kind of
Measurement line thickness and roughness workload is larger in the prior art, there is measurement error that human intervention causes and can only analyze
The problem of finite number strong point.
The technical scheme of the embodiment of the present application is in order to solve the above technical problems, general thought is as follows：
A kind of measuring method of electron micrograph image line thickness and roughness, including：
Obtain the scanning electron microscopy picture of linear to be measured；
Intercept first area；
Image in the first area is carried out along line orientations handling averagely, obtain line edge pixel distribution bent
Line；
According to the line edge pixel distribution curve, the first borderline region is determined；
Local pixel analysis is carried out to the image in first borderline region, border distribution is obtained；
It is distributed according to the border, calculates the width and roughness of the lines to be measured, extract the width of the lines to be measured
Number of degrees value and roughness value.
The method being combined by using borderline region and local scope, the former by along line orientations handling averagely,
Line edge pixel distribution curve is obtained, it is then determined that the first borderline region, so as to effectively define bounds；The latter passes through
Local pixel analysis, obtains border distribution, so as to be influenceed by setting rational local scope to effectively reduce background pixel, makes
Boundary alignment is more accurate.The inventive method can effectively reduce existing method it is determined that limitation during electron beam patterning figure
Property, the accuracy and reliability of measurement are improved, and dramatically saves on time and the cost of the actual measurement of engineer.
In order to be better understood from above-mentioned technical proposal, below in conjunction with Figure of description and specific embodiment to upper
Technical scheme is stated to be described in detail.
Embodiment one：
The measuring method of a kind of electron micrograph image line thickness and roughness is present embodiments provided, as shown in figure 1, bag
Include：
Step 10：Obtain the scanning electron microscopy picture of linear to be measured.
The linear to be measured can be the litho pattern obtained after photoetching process.The photoetching process is
Figure is formed on a photoresist, and the figure is further used for the mask layer of etching.It is described to treat that side linear be passed through
Etching technics to obtaining intermediate pattern or targeted graphical after layer to be etched perform etching, it is layer to be etched can for gate material layer,
The material layer of any need etching such as substrate, layer of dielectric material or metal level, etching technics can be that wet etching or photoetching are carved
Erosion.The linear to be measured can be the bargraphs after section.The linear to be measured can also be progress
Line thickness or the figure of roughness are measured the need for after other techniques, this is not restricted, and will not enumerate.
Particularly, the background pixel after the electron beam patterning of the scanning electron microscopy picture of linear to be measured is distributed not
Uniformly, or background include other figures.For example, while electron beam is to current layer structure imaging, front layer structure graph can be reacted,
So as to cause electron beam patterning to there is the interference of front layer pattern imaging；Or electron beam is imaged to piece cutting structure, due to different positions
Electron beam patterning pixel is uneven caused by the constraint difference that the electron beam running put is subject to, therefore uses traditional measurement
Method can have major defect when measuring line thickness or roughness.
In the present embodiment, linear to be measured is the slice map of deep etching linear, as shown in Fig. 2 along line orientations,
Coordinate position from 1 increase to 100 when, average pixel is significantly increased.
In addition, after the scanning electron microscopy picture for obtaining linear to be measured, determine horizontal and vertical every
Actual physics length representated by one pixel.
In the present embodiment, it is determined that each horizontal and vertical pixel represent physical length be 1nm.General, it is horizontal
Actual physics length representated by the pixel with longitudinal direction is identical, but there may be difference for special circumstances.
Step 20：Intercept first area.
The first area is not comprising the following region of any one or more：Scale, mark and non-interesting region.
General, other instruments can be used to carry out best region selection processing to original image, can also be in the step
Appropriate area is flexibly intercepted according to the actual requirements.Picture shown in the present embodiment have passed through reasonable interval and intercept, removal scale,
The interference regions such as mark.
It can be selected to use the image in the first area or without using Denoising Algorithm according to practical situation；As selected
Using dry algorithm is removed, Gauss Denoising Algorithm is can be used but not limited to, the influence of random noise is removed.The present embodiment is not used
Denoising Algorithm.
Step 30：Image in the first area is carried out along line orientations handling averagely, obtain line edge picture
Plain distribution curve.
It is described to refer to and added up all pixels values along line orientations along line orientations handling averagely, then divided by pixel number,
With the lines pixel distribution curve after obtaining averagely.The effect of the step is to remove the signal noise produced in measurement process, is obtained
Smooth border is taken to be distributed, so as to determine that basic borderline region provides accurate foundation for next step.Particularly, before for assessment
The influence of layer/background pixel distribution, often averages processing along perpendicular to line orientations to underlying pixel data value, obtains background
Pixel distribution curve, as shown in Fig. 2 in the present embodiment.
Step 40：According to the line edge pixel distribution curve, the first borderline region is determined.
It is described that first borderline region is determined according to the line edge pixel distribution curve, including：
Region in the range of the selection extreme value of pixel first is used as basic borderline region；
The first width is expanded to the basic frontier district is overseas, the basic borderline region and first width constitute institute
State the first borderline region.
For example, the situation distorted for lines, the pixel extreme value scope obtained along the method for lines average treatment is often
Special distortion lines can not be covered, it is therefore desirable to outwards appropriate to expand, i.e., expand the first width to the basic frontier district is overseas.
Wherein, the extreme value of pixel first ranges preferably from the 20%~80% of pixel extreme value correspondence width.
, can also be to described after determining the first borderline region described according to the line edge pixel distribution curve
Line edge pixel distribution curve derivation, obtains the maximum of slope absolute value, and common factor inspection is carried out with first borderline region
Look into, exclusive PCR region, to determine accurate bounds.
Step 50：Local pixel analysis is carried out to the image in first borderline region, border distribution is obtained.
The image in first borderline region carries out local pixel analysis, obtains border distribution, including：
Select border localized area scope；
Screen or remove unreasonable pixel；
To equalize the maximum value minimum of local area as according to calculating boundary position.
Can reduce background pixel by local pixel analysis influences, and obtains accurate boundary threshold distribution.
Wherein, the reasonable selection method of border localized area scope usually requires to take into account background pixel distribution situation.
Less border local scope can effectively reduce the influence that smoothing processing is found to optimal boundary, but increase
Influence of noise；More border local scope can effectively suppress influence of noise, but strengthen the influence of background pixel simultaneously,
Actual boundary position is set to deviate actual position.
General, the border localized area scope is covering at least one pixel region, the side along in line orientations
Boundary's localized area scope includes 1/2nd of pixel in the maximum pixel number along line orientations no more than background useful information.
Can be by equalizing local pixel value, or the isolated pixel value of addition filtering algorithm analysis along lines distribution arrangement
Independent noise whether is evident as, or data processing is carried out using the method for best-fitting of the curve, to screen or remove unreasonable picture
Vegetarian refreshments.
To equalize the maximum value minimum of local area as according to calculating boundary position.Wherein, optimal boundary position is calculated
When putting, maximum and minimum after being equalized using local area, boundary threshold are fixed pixel hundred-mark system threshold value.
In the present embodiment, even variation trend is presented along line orientations pixel distribution, therefore local scope is along line orientations
Larger pixel region can be selected, 11 pixels that such as the present embodiment is used are as local treatment region, the side thereby determined that
Boundary's distribution is as shown in Fig. 3 (b).Contrast, the border distribution that original method is determined is as shown in Fig. 3 (a), it will be apparent that, original method
Real border is deviateed on the border of determination in the Y direction, so as to cause larger quantities to survey error.
Step 60：It is distributed according to the border, the width and roughness of the calculating lines to be measured, survey line is treated described in extraction
The width numerical value and roughness value of bar.
The line thickness and the method for roughness of calculating includes：Normal scatter analytic approach, or power spectral-density analysis method.
In the present embodiment, using normal scatter method calculate respectively original method determination border and the inventive method it is true
The mean breadth on fixed border, both are respectively 31.4 (nanometer or pixels) and 31.2 (nanometer or pixels), the i.e. present invention
The use of method reduces 0.2 (nanometer or pixel) to mean breadth.
In the present embodiment, the lines that original method and the inventive method are obtained are obtained using power spectral density method respectively
Width roughness power spectral density plot, as shown in figure 4, line thickness roughness can be effectively reduced using the inventive method,
The particularly power spectral density value of low-frequency range.Width roughness is reduced to the inventive method from 3.6 nanometers of original method
1.6 nanometers, drastically increase the accuracy of measurement line thickness and its uniformity scope.
Embodiment two：
Embodiment two and embodiment one are identical in most steps, and difference is only illustrated here.
Step 10：Obtain the scanning electron microscopy picture of linear to be measured.
In the present embodiment, it is the top view comprising double-decker to treat geodesic structure, as shown in figure 5, wherein, current Rotating fields
Electron beam patterning brightness is high, is distributed and (is distributed up and down) in north and south；The electron beam patterning brightness of preceding Rotating fields is relatively low, is distributed in thing
(left and right distribution).Due to the presence of preceding Rotating fields, its mean pixel distribution difference is up to 40 pixel values.
One pixel of the present embodiment represents 1 nanometer, and Denoising Algorithm is not used.
Step 30：Image in the first area is carried out along line orientations handling averagely, obtain line edge picture
Plain distribution curve.
In the present embodiment, we obtain edge pixel distribution curve of the measurement current layer along line orientations, such as Fig. 5 respectively
Shown in figure below, the equalization pixel distribution curve effectively defines the basic borderline region of current layer lines；It is simultaneously assessment
The interference pixel signal intensities of front layer figure layer, averages pixels processing has been carried out along front layer line orientations, obtains front layer interference
The pixel distribution change curve of signal, as shown in Fig. 5 left figures, lines distribution contributes to assessment front layer figure layer interference signal strong
Degree, and with the optimal localization pixel coverage of this Rational choice.
Step 50：Local pixel analysis is carried out to the image in first borderline region, border distribution is obtained.
In the present embodiment, along current layer line orientations, the electron beam patterning result of preceding Rotating fields has stronger influence, because
This identified local scope should be as small as possible, and 3 pixels that such as the present embodiment is used are thereby determined that as local treatment region
Border distribution as shown in Fig. 6 (b).Contrast, shown in border distribution curve such as Fig. 6 (a) that original method is determined, it will be apparent that,
In the region overlapping with preceding Rotating fields, the border that original method is determined obviously is influenceed, and lines border is expanded to both sides
；The border that the inventive method is determined only has slight fluctuation, and large change is not presented.
Step 60：It is distributed according to the border, the width and roughness of the calculating lines to be measured, survey line is treated described in extraction
The width numerical value and roughness value of bar.
In the present embodiment, using normal scatter method calculate respectively original method determination border and the inventive method it is true
The mean breadth on fixed border, both are respectively 37.6 (nanometer or pixels) and 37.3 (nanometer or pixels).Present invention side
The use of method reduces 0.3 (nanometer or pixel) to mean breadth.
In the present embodiment, the lines that original method and the inventive method are obtained are obtained using power spectral density method respectively
Width roughness power spectral density plot, as shown in fig. 7, the figure is shown, it is wide effectively to reduce lines using the inventive method
Roughness is spent, particularly the power spectral density plot of original method determination is in 0.02nm-1There is prominent peak value in position, corresponding to original
There is 50nm cyclic swing in beginning image, the border distribution curve of intensity profile and Fig. 6 (a) with Fig. 5 along Y-direction is consistent.
The border width roughness power spectral density plot determined using the inventive method significantly reduces the power in middle low-frequency range
Spectral density value, that is, the interference of Rotating fields before reducing.Numerically, the width roughness (3 σ) that original method is determined is 9.0
Nanometer, and the width roughness (3 σ) that the inventive method is determined is reduced to 6.5 nanometers.
In particular, method of the invention is not limited to the linear width that accurate measurement includes background influence
With the measurement of roughness, while can be with accurate measurement line edge roughness.
The inventive method be applicable not only to si-substrate integrated circuit manufacture in advanced measurement, be also applied for opto-electronic device,
The linear formed in any technical process in SiGe integrated circuit, III-V integrated morphology or mems structure
Interfacial roughness measurement.
The measuring method of accurate Characterization electron micrograph image line thickness and roughness, is not limited disclosed in the embodiment of the present invention
The accurate measurement to critical size roughness during IC-components research and development and volume production, other are any with one-dimensional square
Method and its prolong that the optical imagery or electron beam patterning image of device or structure to feature can be provided using the present invention
Stretching method is analyzed and handled.
The measuring method of a kind of electron micrograph image line thickness provided in an embodiment of the present invention and roughness at least includes
Following technique effect：
In the embodiment of the present application, the method being combined using borderline region and local scope, the former is by along lines side
To handling averagely, line edge pixel distribution curve is obtained, it is then determined that the first borderline region, so as to effectively define border
Scope；The latter obtains border distribution, so that by setting rational local scope to effectively reduce the back of the body by local pixel analysis
Scene element influence, makes boundary alignment more accurate.The inventive method can effectively reduce existing method it is determined that electron beam patterning
Limitation during figure, improves the accuracy and reliability of measurement, and dramatically saves on time of the actual measurement of engineer with
Cost.
It should be noted last that, above embodiment is merely illustrative of the technical solution of the present invention and unrestricted,
Although the present invention is described in detail with reference to example, it will be understood by those within the art that, can be to the present invention
Technical scheme modify or equivalent substitution, without departing from the spirit and scope of technical solution of the present invention, it all should cover
Among scope of the presently claimed invention.
Claims (10)
1. the measuring method of a kind of electron micrograph image line thickness and roughness, it is characterised in that including：
Obtain the scanning electron microscopy picture of linear to be measured；
Intercept first area；
Image in the first area is carried out along line orientations handling averagely, obtain line edge pixel distribution curve；
According to the line edge pixel distribution curve, the first borderline region is determined；
Local pixel analysis is carried out to the image in first borderline region, border distribution is obtained；
It is distributed according to the border, calculates the width and roughness of the lines to be measured, extract the width number of the lines to be measured
Value and roughness value.
2. the measuring method of electron micrograph image line thickness according to claim 1 and roughness, it is characterised in that
After the scanning electron microscopy picture for obtaining linear to be measured, in addition to：
Determine the actual physics length representated by each horizontal and vertical pixel.
3. the measuring method of electron micrograph image line thickness according to claim 1 and roughness, it is characterised in that institute
It is not comprising the following region of any one or more to state first area：Scale, mark and non-interesting region.
4. the measuring method of electron micrograph image line thickness according to claim 1 and roughness, it is characterised in that institute
State according to the line edge pixel distribution curve, determine the first borderline region, including：
Region in the range of the selection extreme value of pixel first is used as basic borderline region；
The first width is expanded to the basic frontier district is overseas, and the basic borderline region and first width constitute described the
One borderline region.
5. the measuring method of electron micrograph image line thickness according to claim 4 and roughness, it is characterised in that institute
It is the 20%~80% of pixel extreme value correspondence width to state the first extreme value of pixel scope.
6. the measuring method of electron micrograph image line thickness according to claim 1 and roughness, it is characterised in that
It is described according to the line edge pixel distribution curve, after determining the first borderline region, in addition to：
To the line edge pixel distribution curve derivation, the maximum of slope absolute value is obtained, with first borderline region
Carry out common factor inspection, exclusive PCR region.
7. the measuring method of electron micrograph image line thickness according to claim 1 and roughness, it is characterised in that institute
State and local pixel analysis is carried out to the image in first borderline region, obtain border distribution, including：
Select border localized area scope；
Screen or remove unreasonable pixel；
To equalize the maximum value minimum of local area as according to calculating boundary position.
8. the measuring method of electron micrograph image line thickness according to claim 7 and roughness, it is characterised in that institute
State border localized area scope and at least one pixel region is being covered along in line orientations, the border localized area scope is on edge
The maximum pixel number of line orientations includes 1/2nd of pixel no more than background useful information.
9. the measuring method of electron micrograph image line thickness according to claim 7 and roughness, it is characterised in that institute
State screening or remove unreasonable pixel, including：
Local pixel value is equalized along lines distribution arrangement, or adds whether the isolated pixel value of filtering algorithm analysis is evident as solely
Vertical noise, or data processing is carried out using the method for best-fitting of the curve, to screen or remove unreasonable pixel.
10. the measuring method of electron micrograph image line thickness according to claim 1 and roughness, it is characterised in that
The line thickness and the method for roughness of calculating includes：
Normal scatter analytic approach, or power spectral-density analysis method.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108335990A (en) * | 2018-01-31 | 2018-07-27 | 中国科学院微电子研究所 | Method and device for positioning process defects |
| CN110006374A (en) * | 2019-04-28 | 2019-07-12 | 大连理工大学 | A kind of CFRP roughness measurement method obtaining image benchmark by multi-dimensional interpolation |
| CN110553581A (en) * | 2018-06-01 | 2019-12-10 | 华邦电子股份有限公司 | critical dimension measuring method and image processing device for measuring critical dimension |
| CN118196101A (en) * | 2024-05-17 | 2024-06-14 | 深圳市旗云智能科技有限公司 | Cable category detection method and detection system based on image processing |
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| CN110553581B (en) * | 2018-06-01 | 2022-01-14 | 华邦电子股份有限公司 | Critical dimension measuring method and image processing device for measuring critical dimension |
| CN110006374A (en) * | 2019-04-28 | 2019-07-12 | 大连理工大学 | A kind of CFRP roughness measurement method obtaining image benchmark by multi-dimensional interpolation |
| CN118196101A (en) * | 2024-05-17 | 2024-06-14 | 深圳市旗云智能科技有限公司 | Cable category detection method and detection system based on image processing |
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