CN102543793A - Wafer focusing image quality feedback system and method therefor - Google Patents

Abstract

The invention discloses a wafer focusing image quality feedback system and a method therefor. The system comprises a mechanical motion platform capable of translating around an X axis, a Y axis and a Z axis and rotating around the Z axis, a wafer pallet connected with the mechanical motion platform, an industrial camera with one or more optical lenses, a lighting device, a measuring device and a host computer for controlling the above devices, wherein the host computer comprises an input device and an output device; and a software module comprises a user interface module, an image acquisition module, an image processing module, an equipment control module and an equipment control fixer controlled thereby. The system can acquire target images on the surfaces of wafers on the mechanical motion platform; and after processing of established algorithm in the software system, a plurality of normalized characteristics related to self-focusing are extracted from images or sub-images and weighted to form comprehensive image quality assessment, and the comprehensive image quality assessment is displayed on a user interface for users to refer.

Description

A kind of picture quality reponse system and method that is used for wafer focusing

Technical field

The present invention relates to image processing and semiconductor equipment, relate in particular on the semiconductor equipment wafer is focused on the evaluation of used picture quality and feedback in real time.

Background technology

Manufacturing of semiconductor large scale integrated circuit or technology detect many equipment, and mostly system is that optical system comprises visible light, infrared light; Ultraviolet light; X ray, even electron-optical system such as ESEM system, when need guaranteeing system works to the focusing in wafer work zone.The depth of focus of these complication systems is often limited; When but similar different wafer is put on the mechanical movement platform; Because the error that the varied in thickness of wafer own, bending and mechanical movement cause, all must need to carry out self focusing again and could carry out other work to it and for example aim at and defects detection.After the crystal column surface position that is used to focus on (just obtaining the target of image) confirmed, be that equipment is accomplished automatically in the whole focusing process, therefore be called self focusing.A typical self-focusing comprises the steps:

Equipment is on set wafer plane position; Be the X of wafer place mechanical movement platform; Y coordinate constant (promptly not having the displacement on the horizontal plane); And change to focus on the Z axle (if not industrial camera but other measuring systems then have other can change the variable of system in focus in addition) of variable such as mechanical movement platform within the specific limits, just change wafer for the relative distance between measuring system; Gather the image that focuses under variable a series of variations within limits; Ask the degree of focus of the image that obtains under these different situations according to set algorithm computation, therefrom find out the pairing focusing variable of (usually using curve fit) optimum focusing degree then, system is set as system's optimal accumulated variate-value and with it.

In case workflow (recipe) is set up and through after the check, just can it be kept in the master computer.And equipment can automatically perform this flow process to a large amount of similar wafers later on.Used wafer position of self focusing and optimum focusing variable all can be retained in the workflow (recipe) (being retained in the hard disc of computer as file usually); In the time of will doing self focusing during equipment execution work in future flow process; System just moves to this crystal column surface position; And be starting point with the optimum focusing variate-value of preserving, doing the self focusing of system in an interval around it to this wafer.

The problem that faces in the current practicality is that most users can not select the self focusing image well in creating the equipment work flow process.Normally because the user does not generally possess darker image processing knowledge, more can not only select the required optimized image of self focusing with naked eyes.Following undesirable condition is so often just arranged:

Comprise the global feature deficiency in the image, particularly when the higher or visual field of imaging systemic resolution hour;

Image on a certain direction for example on level or the vertical direction characteristic not enough (degree of focus of system such as ESEM is not isotropic, promptly possibly have astigmatic effect, so that the focusing of influence on this direction;

Picture contrast is not enough, so that influences the accurate Calculation of image focusing degree;

Image brightness is improper, too weak or too strong (saturated) so that influence the accurate Calculation of image focusing degree;

Picture noise is stronger, also can influence the accurate Calculation of image focusing degree;

These factors alone or add together all cause failure of equipment self focusing engineering or result inaccurate easily, influences the operate as normal fully that semiconductor is established, and cause damage.During user's building work flow process (recipe creation) on certain single wafer; Possibly not have prediction problem in the future, and equipment occurs just when automatically performing workflow (recipe execution) finally, causes the system in focus failure; System stops operate as normal, causes damage.

When therefore being necessary in user's building work flow process (recipe creation), to select image; System just can feed back the picture quality information relevant with self focusing in real time, quantitatively and give the user, to guarantee the success of wafer self focusing when carrying out flow process (recipe execution) in the future.

Summary of the invention

The purpose of this invention is to provide a kind of picture quality reponse system and method that wafer focuses on that be used for; To help the user to select to be used for the crystal column surface position (image capture position just) of self focusing best; Guarantee related semiconductor equipment is made the reliability of self focusing when the execution work task; Reduce failure, also improve equipment easy applied performance simultaneously.

One aspect of the present invention proposes a kind of picture quality reponse system that wafer focuses on that is used for, and this system includes:

Can be along X, Y, Z three direction of principal axis translations and the mechanical movement platform that rotates around the Z axle, and be connected the wafer pallet on the mechanical movement platform;

Be used for gathering in real time the industrial camera of target image, this industrial camera is provided with one or several optical lens, and said optical lens can be provided with different apertures and visual field, and optical lens points to said wafer pallet;

Lighting device is for the wafer pallet provides illumination;

Measurement mechanism, and the master computer that is used to control mechanical motion platform, industrial camera, lighting device and measurement mechanism;

In addition, said master computer comprises its input unit and output device, and its software module comprises that subscriber interface module, image capture module, image processing module and device control module are its Equipment Control firmware of arranging.

Another aspect of the present invention is to propose to adopt said system to carry out the method for the picture quality feedback of wafer focusing, may further comprise the steps:

1) industrial camera is gathered the realtime graphic of target wafer, then through software and set algorithm in the master computer, from image, extracts the relevant all normalization characteristics of wafer self focusing;

2) with these characteristics partly or entirely, according to set weight calculation, draw the synthetic image quality evaluation;

3) with the result of synthetic image quality evaluation; On the user interface of master computer, show; Can let the user; Particularly can not need with the naked eye to judge for the uncomprehending user of image processing whether this image is applicable to the wafer self focusing, and only need to decide this image whether available according to this synthetic image qualitative data of feedback.

Judge whether given image is fit to make the self focusing image, be based on according to serial of methods (algorithm), the characteristic of extraction a series of images.

In one embodiment, said method further comprises the characteristic of calculating and using image brightness and contrast, also comprises the normalized method with this brightness and contrast.

In one embodiment, said method further comprises to be calculated and use image saturation characteristic, also comprises the normalized method of this saturation.

In one embodiment, said method further comprises the characteristic of calculating and using the moisture gentle vertical direction top edge pixel number of image packets, also comprises the normalized method of edge pixel number.

In one embodiment, said method further comprises to be calculated and use picture noise characteristic, also comprises the normalized method of this noise characteristic.

In one embodiment, further comprise a kind of method that will go up the quality overall merit that each independently normalized characteristics of image weighted comprehensive obtains, consequently normalized; The characteristic that this method also allows the user to increase or reduces wherein to be comprised.

The invention has the advantages that; This system can gather the target image of crystal column surface on the mechanical motion platform in real time; After the processing through set algorithm in the software systems; From this image or wherein extract the subimage from self focusing relevant a plurality of normalized characteristic and weighting and constitute the synthetic image quality evaluation, be presented in real time and supply user's reference on the user interface.

Description of drawings

Fig. 1 is the structural representation of the picture quality reponse system that is used for the wafer self focusing that proposes of the present invention;

Fig. 2 is the user interface sketch map of this system.

Embodiment

For technological means, creation characteristic that the present invention is realized, reach purpose and effect and be easy to understand and understand, below in conjunction with diagram and specific embodiment, further set forth the present invention.

The picture quality reponse system that is used for wafer focusing that the present invention proposes relates to the part in manufacturing of semiconductor large scale integrated circuit and the technology checkout equipment, promptly wherein is used for the subsystem that wafer is focused on.The method that the present invention includes this subsystem and on this subsystem platform, work.During work; This method also will be used certain concrete semiconductor large scale integrated circuit equipment at subsystem of the present invention place unavoidably; The mechanical movement platform on it for example; Measuring system on industrial camera or the equipment, shared master computer and soft, hardware thereof etc., so some parts are shared with its place semiconductor large scale integrated circuit equipment among the present invention.

According to one of embodiment of the present invention, as shown in Figure 1, components of system as directed of the present invention comprises:

One can be along X axle 110, Y axle 120, and 130 translations of Z axle and the mechanical movement platform 100 that rotates around Z axle 130 are connected with wafer pallet 140 on it, can place wafer 200 on the dish, and they also are the part of semiconductor large scale integrated circuit equipment usually;

Industrial camera 300 and the optical lens 310 on it; Camera can be monochromatic or colored, and not limitting is CDD or CMOS, does not limit resolution; Also not limitting is analog or digital, and the camera front end can be equipped with the camera lens (even can have a plurality of camera lenses to switch) of decision visual field size;

Lighting device 400, for example broadband light-emitting diode (LED) battle array;

Measurement mechanism 500, the for example electron-optical system of ESEM or other optical measuring systems;

Master computer 600; Comprise its input, output device, for example mouse, keyboard, display etc., the working software on the master computer 600 comprises its subscriber interface module 630; And some application and control module; Comprise image capture module 610, image processing module 620, device control module 640 and for its Equipment Control firmware 641 of arranging.

The present invention relates to equipment such as large scale integrated circuit manufacturing and technology detection, be used for the subsystem part of wafer self focusing on it.According to one embodiment of the invention, subsystem involved in the present invention is as shown in Figure 1, comprises industrial camera 300 and the optical lens 310 on it.If digital camera; Usually can obtain image continuously and directly be transferred to computer, for example use USB (USB) or IEEE1394 line, if analogue camera; Then earlier with analog signal; For example pass to the image pick-up card (Frame Grabber) on the computer, obtain by it that digital picture is passed to computer so that successive image is handled again, and image is presented on the computer screen with the Camera-Link line.Industrial camera 300 can be that black and white has gray scale, also can be colored, and its red, green, blue (RGB) component is arranged.Generally speaking, coloured image can convert into monochrome image come for self focusing used, one of for example desirable red, green, blue picture content or remove their mean value.There is camera lens decision on it focal length of camera, visual field, and resolution can have multiple setting, is set to 640 (wide) pixel * 480 (height) pixel, 1024 higher pixels * 1024 pixels like minimum VGA.Camera CCD type normally also can be high-end CMOS type in addition, does not limit in the present invention.

According to one embodiment of the invention; Also include master computer 600 in the system, have image capture module 610 on it, image processing module 620 (comprising image recognition/template matches); Subscriber interface module 630, device control module 640 and for its Equipment Control firmware 641 of arranging.The system in focus variable is also by device control module 640 dominations.

No matter the work of wafer on equipment is production of integrated circuits such as photoetching, or technology detects like defects detection, all is divided into two stages usually, i.e. workflow establishing stage and workflow execution phase.At the workflow establishing stage, the person of being to use uses the software on the master computer 600, carries out with interactive mode.At first be to be workflow with single wafer creation task, it comprises how carrying out wafer alignment, where does which kind of processing or measurement in what unit of wafer, how to data analyze, show, preservation etc.In case workflow has been created well; In the workflow execution phase; Automatically by set workflow, manipulator is got similar wafer from wafer cassette to equipment automatically, carries out that each task comprises wafer alignment in whole workflows; Then wafer is put back to wafer cassette, get next wafer again and do same work.Many places all will focus on wafer inevitably in the work.

The present invention relates to a committed step of workflow establishing stage, promptly wafer is focused on from (moving), be called for short self focusing.

When the wafer work flow process was created, manipulator was positioned over a wafer on the mechanical movement platform, supposed and accomplished wafer alignment (being generally the first step), and the user begins moving movement platform and the image of observing the camera real time shooting.Periodic integrated circuit unit 210 is arranged on the semiconductor crystal wafer 200 among Fig. 1, have on the edge one be used for prealignment short slot.The user selects the image (being used to extract degree of focus) when certain zone is as self focusing on the wafer 200 according to need of work.Focus on variable during self focusing, for example the Z axle can change within the specific limits.

Subscriber interface module 630 is responsible for the graphic user interface (GUI) 602 on the display screen 601 among Fig. 2, and this graphic user interface is the inlet of functions such as all devices control, system works, result's demonstration and information management.The user can go up mechanical movement platform mobile controller 603 through GUI and move horizontally wafer.Image display area 604 is arranged in the user interface 602.If it is to do self focusing with subimage among the figure that the user selects, then stack sign frame shows subimage zone as 605 on the image.

The core that the present invention relates to is exactly to select on the wafer certain to sentence when doing self focusing with its image the user; Should locate image by image capture module 610 collections; From this image, extract the normalization characteristic of relevant all images with self focusing by set algorithm by the software of master computer 600; Constitute total image quality evaluation 606, be shown in real time on the display screen 601 of master computer 600.

Describe the detailed algorithm of various characteristics of the present invention and total quality evaluation algorithm below in detail:

The picture contrast algorithm

Usually whole or most target images are participated in computing when pattern matching, therefore ask the contrast of entire image usually.Picture contrast can obtain through calculating.

$c=\frac{\mathrm{Max}\left(I\right)-\mathrm{Min}\left(I\right)}{\mathrm{Max}\left(I\right)+\mathrm{Min}\left(I\right)}$ Formula (1)

I presentation video wherein, then pixel maximum and the minimum value in max (I) and min (I) the expression gray level image.Also having a kind of method that more influenced by picture noise is that x% does on average near getting near x% of image histogram peak and minimum point, replaces max (I) and min (I) calculating contrast c in the following formula, and x can be 0.5 or 1 usually here.

The image brightness algorithm

Usually whole or most target images are participated in computing when pattern matching, therefore ask the brightness of entire image usually.Image brightness can be through calculating

$b=\frac{\mathrm{\Σ\; I}}{\mathrm{NM}}$ Formula (2)

I presentation video grey scale pixel value wherein, the whole pixels of summation traversal.Total number of pixels in the N presentation video, M representes the maximum gradation value of single pixel, the meaning of b is a mean flow rate.The expression of image brightness can have multiple, and for example brightness also can be got the pixel average gray value of the higher x% of gray value and represent that for example x can be 50 by in total pixel.

The image saturation algorithm

Image saturation s can calculate with following formula simply.

$s=\frac{\mathrm{\Σ}I\mathrm{Max}}{N}$ Formula (3)

Wherein, Imax representes that gray value reaches peaked pixel, summation traversal all images, and N is the total numbers of the whole pixels of image.Usually the pixel maximum gradation value determines that by the computer data type of expressing pixel for example using the grey scale pixel value scope of the data type (unsigned char) of the no sign of 8 bits (bit) is 0～255, and promptly maximum is 255.A kind of simple method for normalizing is to see whether above image saturation s surpasses a certain set threshold value Smax,

$s=\left\{\begin{array}{cc}1,& s>s_{\mathrm{Max}}\\ 0,& s\≤s_{\mathrm{Max}}\end{array}\right.$ Formula (4)

Certainly also have other ways that image saturation s is described as a function, for example when s≤smax with a piecewise function gradual change description s along with image in the increase of saturated pixel, from 1 to 0 change procedure.

The picture edge characteristic algorithm

Edge in the image, i.e. the extraction of the shade of gray of neighbor can be tried to achieve with the partial derivative of X and Y direction.The intensity of gradient (mould) does

$\▿I=|{\mathrm{Gx}}^2+{\mathrm{Gy}}^2|$ Formula (5)

The direction of gradient does

α (x, y)=tan ^-1(G _x/ G _y) formula (6)

Wherein, the I presentation video is at the gray value of certain pixel, and Gx and Gy difference presentation video are at the directions X of certain point and the partial derivative of Y direction.Thereby the partial derivative as for how asking digital picture is asked gradient, and many algorithms are arranged.Sobel operator method for example, its Gx and the Gy form of expression when 3 * 3 yardsticks is two matrixes

$\mathrm{Gx}=\left(\begin{array}{ccc}-1& 0& 1\\ -2& 0& 2\\ -1& 0& 1\end{array}\right)$ Formula (7)

With

$\mathrm{Gy}=\left(\begin{array}{ccc}-1& -2& -1\\ 0& 0& 0\\ 1& 2& 1\end{array}\right)$ Formula (8)

The extraction at the edge in the image also has many other algorithms, as asks the Laplacian algorithm of second-order partial differential coefficient.Sobel operator method also is not necessarily 3 * 3 in addition.Usually also Preprocessing Algorithm such as denoising can be arranged before the edge extracting.Post-processing algorithm such as threshold test (removing the edge pixel that is lower than set threshold value) and normalization again also can be arranged after the edge extracting usually.

Further have

$g_x=\frac{\mathrm{\Σ\; Exi}}{N}$ Formula (9)

With

$g_y=\frac{\mathrm{\Σ}{\mathrm{Ex}}_i}{N}$ Formula (10)

Wherein, Exi representes that i edge detection value Gx reaches the edge pixel of the directions X of set threshold value, and Eyi representes that i edge detection value Gy reaches the edge pixel of the Y direction of set threshold value, and N representes all images pixel sum.Normalized like this directions X edge feature can be expressed as

$e_x=\left\{\begin{array}{c}1,g_x\&GreaterEqual;G_{\mathrm{Max}}\\ {\mathrm{Ag}}_x+b,G_{\mathrm{Min}}<g_x<G_{\mathrm{Max}}\\ 0,g_x<G_{\mathrm{Min}}\end{array}\right.$ Formula (11)

$a=\frac{1}{G_{\max }-G_{\min }}$

B=-aG _MinFormula (12)

In like manner, normalized Y direction edge feature can be expressed as

$e_y=\left\{\begin{array}{c}1,g_y\&GreaterEqual;G_{\mathrm{Max}}\\ {\mathrm{Ag}}_y+b,G_{\mathrm{Min}}<g_y<G_{\mathrm{Max}}\\ 0,g_y<G_{\mathrm{Min}}\end{array}\right.$ Formula (13)

$a=\frac{1}{G_{\max }-G_{\min }}$

B=-aG _MinFormula (12)

Wherein Gmax and Gmin represent the last lower threshold value in set X and the Y edge image respectively.Total edge feature should comprise the edge feature of X and Y direction.Because sometimes maybe a certain direction edge feature obvious, and perpendicular other direction edge feature very a little less than, this moment, imaging system had astigmatism.

The picture noise algorithm for estimating

The Noise Estimation of single-frame images also has many methods.For example affact on the image with the Sobel edge detection operator in formula (9) and (10) earlier.Use following Laplacian (Laplace) then

$L=\left(\begin{array}{ccc}1& -2& 1\\ -2& 4& -2\\ 1& -2& 1\end{array}\right)$ Formula (14)

Affact on the image, promptly with the image convolution.Use then local smoothing operator for example two-dimensional Gaussian function/template action to image, ask the total average variance of image to come estimating noise of input image at last.Normalized picture noise characteristic n can be

$n=\left\{\begin{array}{cc}1,& \mathrm{\&sigma;}\&le;{\mathrm{\&sigma;}}_{\mathrm{Max}}\\ 0& \mathrm{\&sigma;}>{\mathrm{\&sigma;}}_{\mathrm{Max}}\end{array}\right.$ Formula (15)

Wherein, σ is the average variance that image obtains through said handling process, and σ max is the maximum average variance that allows.

Also have a lot of other picture noise algorithm for estimating in addition.For example can use image is the power spectrum (Power Spectrum) of frequency space in Fourier (Fourier) space, and promptly modulus/intensity of in Fourier space, being worth on each frequency of image is come estimate sheet two field picture noise.Specifically, earlier two dimensional image power spectrum (Power Spectrum) is made angle and on average obtain one-dimensional data (curve), its direct current (DC) is arranged, low frequency and medium-high frequency part.Usually the average image energy spectral curve of angle is in medium-high frequency, increases and sharply reduces with frequency, reduces gently then.This power spectrum reduces part gently can be considered to noise basically, and its average in the medium-high frequency scope just can be a kind of measurement of picture noise.

The image synthesis quality evaluating method

According to one embodiment of the invention,, be necessary that with above-mentioned whole normalized characteristics of image aggregations be an overall image synthesis quality evaluation for convenient to the user.The user can select individual characteristics, does not participate in the overview image quality evaluation, can also offer the user separately in real time simultaneously.

The image synthesis quality evaluation is that above-mentioned each normalized characteristics of image comprises contrast metric c, brightness b, saturation characteristic s, the weighted average of edge feature e and noise characteristic n.A kind of method of overall assessment t of simply asking does,

$T=\left\{\begin{array}{cc}0,& \mathrm{\&Pi;}{T}_i=0\\ \mathrm{\&Sigma;}{w}_i{T}_i,& \mathrm{\&Pi;}{T}_i\&NotEqual;0\end{array}\right.$

∑ w ₁=1 formula (16)

Wherein Ti representes that i above-mentioned characteristic is contrast metric c, brightness b, and saturation characteristic s, directions X edge feature ex, one of Y direction edge feature ey and noise characteristic n, and wi is the set weight of this characteristic.Connect long-pending, the whole above-mentioned characteristics of summation traversal in the formula.Can find out by formula (16); If there is one above-mentionedly to be characterized as zero; Then the image synthesis quality evaluation is zero; Its expression does not allow any one index not meet the demands, otherwise possibly cause the wafer work flow process to create (recipe creation), or more serious be wafer self focusing failure when workflow is carried out (recipe execution).Obviously, this total image quality evaluation expression formula allows to add in the future new individual image characteristic or removes the individual image characteristic.

The template image quality is fed back in real time

According to one embodiment of the invention; Utilize above-mentioned template image comprehensive quality evaluation method; The user is when creating wafer self focusing flow process; At first go up control 703 mechanically moving motion platforms 20 through GUI and select the wafer somewhere, camera 40 obtains wafer image in real time, and is shown on the user interface 702 of computer 70 softwares.Computer software is more according to method once, calculates this image and the quality overall evaluation 706 of template wherein, is shown on the user interface in real time.

Degree of focus

Degree of focus is divided into 1 dimension degree of focus and 2 dimension degree of focus.Some optical system or type optical system isotropic are relatively poor; Not as having astigmatism, lens promptly can not reach best focusing simultaneously on two vertical direction (for example X and Y direction); Therefore be necessary to calculate respectively the degree of focus of two mutual vertical direction; How need know 2 dimension degree of focus this moment, it can be the average of these two vertical direction degree of focus.Degree of focus is basically for signal in the image (not comprising noise) medium-high frequency part, in the spatial domain also just corresponding to zones such as edges in the image.In frequency domain, can use two Butterworth filters, high pass of a low pass is formed a band pass filter, comes filtering image, at the absolute value that goes this filtering image with the difference of original image.Can use edge extracting operator (filtering) in the spatial domain; And X and Y direction are made edge extracting respectively; Like cotype (9), (10); Collect these edge pixel sums then respectively as X and Y direction focusing degree value, also can use normalized (11), (13) formula to come to represent respectively the degree of focus value of X and Y direction.As an example; (9), (10), (11), (13) formula are all from the Sobel operator of 3 pixels; In the practical application according to the frequency of useful signal part in the image; The operator of available more pixels extracts picture edge characteristic, the Laplce's (second order gradient) and the image convolution of 1 dimension Gaussian function of a for example available length-specific:

$I=I\&CircleTimes;\mathrm{\&Delta;\; G}$ Formula (17)

I representative image wherein; G represents a Gaussian function; Δ is represented Laplace's operation, and

represents convolution algorithm.Its main points are that Gaussian function G works as length (number of pixels, the density of just on the continuous Gaussian function, taking a sample) and can change with concrete application.Remove this and also have many algorithms that can be used for describing the image focusing degree, no longer give an example.The few of meaning of the degree of focus of single image because it is not the amount of a normalizing usually, and just has comparativity in the degree of focus of the last image of under difference focusing variable, gathering of same object (the for example same place of crystal column surface).Usually system's self focusing also all is the still image pickup area, and this has also explained the selection in this zone very important, and that the present invention does the real-time feedback system of the picture quality information that relates to is helpful for the selection ten minutes in this zone with method.

Other

Semiconductor equipment is done the wafer self focusing has a plurality of camera lenses often, promptly a plurality of multiplication factors or a plurality of image resolution ratio.Image is not only optical imagery, possibly be electron beam, beam of charged ions etc., and these can not influence above-mentioned image and the wherein characteristics algorithm or the above-mentioned image synthesis quality evaluation of subimage.Because under the setting of each multiplication factor or a plurality of image resolution ratios, above-mentioned image the and wherein characteristics algorithm or the above-mentioned image synthesis quality evaluation of template are all set up.Said method is equally for different equipments unit such as manipulator, prealigner, and the mechanical movement platform, camera or other imageing sensors, lighting sources etc. are all set up.

More than show and described basic principle of the present invention, principal character and advantage of the present invention.The technical staff of the industry should understand; The present invention is not restricted to the described embodiments; That describes in the foregoing description and the specification just explains principle of the present invention; The present invention also has various changes and modifications under the prerequisite that does not break away from spirit and scope of the invention, and these variations and improvement all fall in the scope of the invention that requires protection.The present invention requires protection range to be defined by appending claims and equivalent thereof.

Claims (9)

1. one kind is used for the picture quality reponse system that wafer focuses on, and it is characterized in that said system comprises:

Can be along X, Y, Z three direction of principal axis translations and the mechanical movement platform that rotates around the Z axle, and be connected the wafer pallet on the mechanical movement platform;

Be used for gathering in real time the industrial camera of target image, this industrial camera is provided with one or several optical lens, and said optical lens can be provided with different apertures and visual field, and optical lens points to said wafer pallet;

Lighting device is for the wafer pallet provides illumination;

Measurement mechanism, and the master computer that is used to control mechanical motion platform, industrial camera, lighting device and measurement mechanism.

2. a kind of picture quality reponse system that wafer focuses on that is used for according to claim 1; It is characterized in that; Said master computer comprises its input unit and output device, and its software module comprises that subscriber interface module, image capture module, image processing module and device control module are its Equipment Control firmware of arranging.

3. adopt the described system of claim 1 to carry out the method for the picture quality feedback of wafer focusing, may further comprise the steps:

1) utilize industrial camera or measuring system to gather the realtime graphic of target wafer, then through set algorithm and software in the master computer, from image or wherein extract the relevant all normalization characteristics of self focusing the subimage;

2) with these characteristics partly or entirely, according to set weight calculation, draw the synthetic image quality evaluation;

3) with the result of image template quality evaluation; On the user interface of master computer, show in real time; Let the user; Whether particularly those can not judge with naked eyes whether selected image is applicable to the wafer self focusing for the uncomprehending user of image processing, and only decide this image available or on wafer, select the better pictures position according to these synthetic image quality feedback data.

4. the picture quality feedback method that is used for wafer focusing as claimed in claim 3 is characterized in that, said method further comprises to be calculated and use image brightness characteristic, also comprises the normalized method of this brightness.

5. the picture quality feedback method that is used for wafer focusing as claimed in claim 3 is characterized in that said method further comprises the characteristic of calculating and using contrast, also comprises the normalized method of this contrast.

6. the picture quality feedback method that is used for wafer focusing as claimed in claim 3 is characterized in that, said method further comprises to be calculated and use image saturation characteristic, also comprises the normalized method of this saturation.

7. the picture quality feedback method that is used for wafer focusing as claimed in claim 3; It is characterized in that; Said method further comprises the characteristic of calculating and using the moisture gentle vertical direction top edge pixel number of image packets, also comprises the normalized method of edge pixel number numerical value.

8. the picture quality feedback method that is used for wafer focusing as claimed in claim 3 is characterized in that, said method further comprises to be calculated and use picture noise characteristic, also comprises the normalized method of this noise characteristic.

9. as claimed in claim 3ly be used for the picture quality feedback method that wafer focuses on, it is characterized in that, further comprise a kind of method that will go up the quality overall merit that each independently normalized characteristic weighing comprehensively obtains, consequently normalized; The characteristic that this method also allows the user to increase or reduces wherein to be comprised.

Images