DD251847A1 - METHOD AND ARRANGEMENT FOR IMAGE COMPARISON - Google Patents

Abstract

The object of the invention is to provide a method and an arrangement for the exact and effective control of stencils or intermediate stencils which are required for the production of integrated circuits. The object is achieved in that a serial, binary actual image is generated by the templates or intermediate templates, that a serial, binary target image is generated on the basis of the data record which describes the structure of the templates during the production of these templates or intermediate templates in that deviations between desired and actual image are recognized as defects of the actual image, that the parameters tonal value, number of determined contour sections and the presence of undetermined contour sections are successively determined for the defects and the defects corresponding to said parameters are clearly new Types types. It is essential that the entire process, including the determination of the specific defect parameters, takes place in real time, independent of the structural and defect density. It is also important that data are used for target image acquisition, which take into account determinate, device-related pseudo-deviations and locally-oriented structural tolerances.

Description

For this 7 pages drawings

Field of application of the invention

The invention relates to a method and arrangement for the exact comparison of an objectified, two-dimensional image with the CAD data set used to produce the image as a template.

The invention finds particular application in the control of stencil products required for integrated circuit fabrication. Other applications are in the context of control processes on printed circuit boards, printing, textile, cartographic u.a. Products and optical and opto-electronic imaging equipment.

Characteristic of the known technical solutions

The Offenlegungsschrift DE 3336471 A1 describes a method and an arrangement with which deviations of an image from desired data are determined and classified. This method and this arrangement has the following disadvantages compared to the present invention:

- The determination of the parameters required for classification takes place in a two-stage process. Defective locations of the object to be assessed must be scanned a second time for the actual analysis.

The classification-specific parameters are determined by a method that is not real-time capable.

- Only six types of defects are distinguished.

- The arrangement does not allow during a control run such target data are used for comparison, taking into account both positive and negative tolerances, in particular locally oriented tolerances.

- Too high defect density causes misclassifications.

German Offenlegungsschrift DE 3336470 A1 describes a method and an arrangement whereby differences of a first image with respect to a second image can be determined, characterized in that the differences along edges present in the first image are suppressed.

This method realizes the consideration of strictly edge-oriented tolerances. Locally oriented tolerances that take into account the relationship of adjacent features can not be processed using this technique.

Object of the invention

The object of the invention is to provide a method and an arrangement which enable an accurate determination of the defect in real-time operation, irrespective of the structure of the image and the frequency of the defects, and thus increase the good yield in the production of integrated circuits.

Essence of the invention

The invention has for its object to avoid the disadvantages of the prior art described.

This object is achieved by the given in the characterizing part of claims 1 and 6 teaching. Preferred developments are described in the subclaims.

The objectified image and the data used to produce it are made comparable by opto-electronically scanning the objectified image and generating a binary actual image by thresholding and by using a computer in accordance with the data used to produce the objectified image or an electronic circuit, a binary target image is generated. Thus, two sets of data are available for the exact comparison, which describe images that are composed of structural elements with the tone values one and zero.

In this case, a target image adapted to the actual image is generated in order to suppress the determined pseudo-deviations. This is accomplished by taking into account, on the one hand, the deterministic, pictorial changes caused by the equipment required to produce the objectified images and the control related scan and, on the other hand, the threshold set for the binarization of the actual images.

The line-by-line oriented pixels of the actual and target images are provided serially and synchronously for defect detection. Whether the pixel belongs to a defect is determined by antivalence analysis.

By means of delay elements on the one hand next to the defect information of the current point of the neighboring points in the current and previous line and on the other hand next to the target image information of the current point the der8 neighboring points are provided simultaneously.

With the help of this information, a log. Circuit the parameters describing a defect. It is essential that in addition to the area, the circumference and the extreme coordinates, the parameters Tonwertinformation, number of deterministic contour sections and presence of nondeterministic contour sections, the starting points for a type classification are determined.

The tonal information is determined separately according to tone value one and tone value zero, whereby the indication of mixed. Tonal values is possible. The tone value information of the defect is oriented on the actual image.

A deterministic contour section of a defect is defined by a contour of a structure present in the target image. Corresponding to the tonal value of the defect at the considered contour point, a deterministic contour section is identical or adjacent to the desired contour.

The number of determined contour sections is obtained by the number of changes between deterministic and undetermined contour sections. The number of changes indicates twice the number of determinate contour sections, except in the case where there is no undetermined contour section. To solve these problems, the presence of undetermined contour points is determined.

The change between a deterministic and nondeterministic contour section is made known by the fact that the contour points, which are characterized by the presence of at least one non-defective pixel neighbors, are detected and that the status with respect to the determination of adjacent contour points is evaluated. A defect contour point is determined precisely if, depending on its tone value, either the current target image point is a contour point or one of the 8 target image point neighbors.

The named log. Circuit also has controlling function. It organizes the unambiguous summarization of partial results of a defect, so that each defect is represented by a resulting parameter set. It is essential that the parameter determination for a defect for the pixel clocks, for which a defect is displayed in the current or previous line without interruption, is activated, that subsequently the determined parameters with possibly already existing parameters that belong to this defect, can be summarized that the problems of unifying defect parts are solved by combining the parameter sets and branching defects by assignment and that the end of the parameter determination for a defect by zero indication of a count, which begins with the reopening of a defect at Ei ns, with each Branch is incremented by one and decreased by one with each partial closure.

The intermediate and final results of a defect are stored in a defect memory. A defect is assigned a fixed memory address. Free memory addresses are taken from an availability memory. If defect parts are combined, the freed memory address is made available again in the availability memory. The defects processed in one line are registered by their memory addresses in an allocation memory. A second allocation memory contains the memory addresses of the defects processed in the previous line. If a defect is completely detected, the log informs. Circuit whose address via a transmission memory a computer with,. which can then retrieve the parameter set from the defect memory and makes the address available again in the availability memory. The log. Circuit suppresses this process when the defect falls below a predetermined limit for the area and provides the previously specified address in the availability memory again. The computer divides the defects into 9 classes as a function of the parameters tone value information, number of determined contour segments and presence of nondeterminable contour segments: An example of a classification into 9 classes is shown in the following table:

Tone value zero Yes No Yes Tone value one No Yes Yes To be available Number ofdetermin. nichtdetermin. Konturabschn. contour sections

Yes 0 hole additional, undefined structure element global defect Yes 1 indentation bulge global defect Yes greater than 1 interruption bridge global defect

No

any

missing structure.with tone value one

missing structure. with tone value zero

global defect

embodiments

The invention is explained in more detail below with reference to exemplary embodiments. The pictures show in detail:

Fig. 1: Arrangement for detecting and classifying deviations of objectified images against the in the production of these images as a template serving and the Bildin ha It defining record.

FIG. 2: Arrangement for recognizing and classifying deviations of objectified images from the data set used in the production of these images as a template and defining the image content, taking into account locally oriented, permissible tolerances.

Fig. 3a: Example of a desired structure

Fig. 3b: Determined deviation from the structure shown in Fig. 3a by the transfer function of the equipment used in the manufacture of the object images and their scanning for control.

Fig.4a: Example of a target image

FIG. 4 b: Possible actual image according to the desired structure shown in FIG. 4 a

Fig. 4c: Extracted defect

FIG. 5a: Determined contour section of a defect with tone value

FIG. 5 b: Determined contour section of a defect with tone value. FIG

Fig. 6a: - target image

FIG. 6 b: Possible actual image according to the desired structure shown in FIG. 6 a

Fig. 6c: Extracted defect indicating essential processing lines and columns

Fig. 7 a: target image.

7 b: actual image with a defect of the "hole" type

8a: target image

8b: actual image with a defect of the type "indentation"

Fig.9a: target image

9 b: actual image with a defect of the type "interruption"

Fig. 10a: target image

10 b: actual image with a defect of the type "missing structure element with tone value one"

Fig. 11a: target image

11 b: actual image with a defect of the type "additional, undefined structural element"

Fig. 12a: target image

12 b: actual image with a defect of the type "bulge"

Fig. 13a: target image

FIG. 13 b: actual image with a defect of the type "bridge"

Fig. 14a: target image

14 b: actual image with a defect of the type "missing structure element with tone value zero"

Fig. 15a: target image

FIG. 15b: actual image with a defect of the type "global defect"

Fig. 16: Target structure with representation of the locally oriented, permissible tolerance ranges

In Fig. 1, an arrangement for detecting and classifying deviations of objectified images against the in the production of these images as a template serving and the image content defining data set is shown.

A device 1 opto-electronically scans the objectified image, eliminates sampling-related errors, performs binarization of the pixel-characteristic information by means of a threshold value and outputs the pixel information serially.

A device 2, consisting of a computer with a corresponding data memory or a log. Circuit with corresponding data memory or a combination of both generates a binary target image matched to the actual image and outputs the pixel information serially.

The target image deviates meaningfully from the data set used to produce the objectified image in accordance with the determined pictorial changes which are caused on the one hand by the production process and on the other hand by the control process. 3a shows a section of an image serving as a template. In Figure 3b, the resulting visual change is recognizable, which, as is known, can be determined by folding the output image with the respective apparatus functions. The positional deviations between the structure edges actually displayed in the binarized actual image and actually present in the objectified image also belong to the determined pictorial changes.

The position deviations depend on the threshold value prescribed for binarizing the actual image, the transmission parameters of the scanning device and the geometric conditions.

While the generation of the target image must be done online in real time, the transformation, which generates a target image data record adapted to the actual image in accordance with the determined visual changes from the data set used to produce the objectified image, can advantageously take place offline. Through a logic circuit,

z. B. Antivalence circuit 3, a difference between the respective target and actual image is detected.

A delay circuit 4 realized by shift registers provides at 6 outputs the information determined by the exclusive-OR circuit from a pixel to be currently designated, from its left and right neighbor pixels in the row, and the neighbors to those pixels in the previous row simultaneously.

A delay circuit 5, also realized by shift registers, provides at 9 outputs the target image information from a pixel to be designated as being current and its 8 surrounding neighbors.

A logic circuit 6 processes the information offered by the delay circuits 4 and 5 and determines for each detector the parameters area, circumference, extreme coordinates, tonal information, number of determinate contour sections and presence of undetermined contour sections.

The log. Circuit 6 is connected to a memory 11 which receives the intermediate and final results for the defects.

There is one storage space for each defect. The address of the memory location is taken at Erstkontaktierung with a defect in a memory 7, which contains all unused addresses of the memory 11. A memory 8 records the addresses of the defects processed in the respective current line in chronological order. In order to solve the assignment problem, the addresses of the defects processed in the preceding line are stored in a memory 9 in chronological order. Line by line, memories 8 and 9 change their function.

In a memory 10, the addresses of the fully detected defects are stored, if they do not fall below the area specified in the register 12 limit. If the limit is exceeded, the log. Circuit, the address that was provided for the detected defect, free again by this is stored in the memory 7 again.

A computer 13 takes from the memory 10 the addresses of the fully detected defects, accordingly takes from the memory 11 the final parameters of a defect, performs a typing and a classification. The computer 13 outputs the result data and, if necessary, generates control data for a repair station. A clock generation unit 14 controls the operating regimes of the logical processing units.

By way of example, the parameters describing a defect are explained.

FIG. 4c illustrates a defect 21 which results from the comparison between the target image 4 a and the actual image 4 b. The area of the defect is equivalent to the number of its pixels. The extent of the defect is determined by the sum of the lengths of lines 22, 23, 24 and 25.

The extreme coordinates of the defect are given by the points 26, 27, 28 and 29 on the coordinate axes 30 and 31.

The tonal information results from the tonal value of the defect-matching section 32 of the actual image Fig.4b.

As a result, the tone is one. The defect has two determinate contour sections 24 and 25 defined by the structural edges 33 and 34. With the contour sections 22 and 23 undetermined contour sections are present.

5a shows the relationship between a deterministic contour section 35 of a defect 36 with the tonal value zero and the nominal contour 37. The determined contour section and the corresponding section of the target contour are congruent.

FIG. 5 b demonstrates the relationship analogously for a defect 38 with the tone value one. The determined contour section 39 and the corresponding section of the target contour 40 are adjacent.

The function of the logic circuit 6 will be explained using the example of a defect 41, FIG. 6c. The defect results from the comparison between a target image Fig.6a and an actual image Fig.6b.

The pixel information including the above-mentioned environmental information is read line by line and within the line column by column by the upstream, o.g. Elements provided.

In a row 43 and column 58 begins contacting the defect, thereby determined that in the previous column 57 was not a defect. The registers required for the parameter determination via a contact are deleted.

The column value associated with column 58 is recorded as the minimum and maximum column values of the current contact.

The area is increased by one. The contour length does not experience any increase, since there is no contour relation to either the preceding line 42 or the preceding column 57. The tone value is equal to one, since the pixel projected into the actual image has the tone value one. There is an undetermined contour point since the pixel projected into the target image has no contour point as a neighbor.

With the next clock, the pixel information associated with row 43 and column 59, including the o.g.

Environment information provided. Since the pixel information indicates a defect, the contacting is maintained. The area is again increased one and the column value as maxi painter columns festgeh old. The contour length is also increased by one, since there is a contour relationship to the previous column 58. There is no new information for the tonal value. This applies to the entire defect. There is also an undetermined contour point. A change between a densely determined and determined contour point is not counted.

The pixel information associated with row 43 and column 60 causes a repetition of the foregoing, but the determinant analysis yields a determinate contour point because the pixel projected into the sol image has at least one contour point as a neighbor. A change between an undetermined and a determined contour point is counted.

With the next clock, column 61 is reached. The contacting of the defect is canceled. Since in the course of contacting no connection to defect points of the previous line 42 has been registered, the row value associated with line 43 is recorded as a minimum line value, a branching parameter for defect end detection is set to one and a new defect-related feature set is placed in memory 11, FIG. For this purpose, an address is taken from the memory 7, assigned to the defect and the intermediate result stored in the memory 11 on the provided address. In addition, the address is held in a memory 8 to allow recognition in the next line.

The next contact is made in line 44 from column 57. The registers are deleted again. The column value associated with column 57 is recorded as the minimum and maximum column values of the current contact. The area is increased by one. The contour length is extended by V2, since there is an adjacent contour point in the previous contacting of the row 43 in the column 58. There is an undetermined contour point. A change in the determinant analysis did not take place with reference to the contour point just cited.

The next two points of contact increase only the area value and update the maximum column value. The processing of column 58 also includes recognizing the previous contact in line 43 and providing the address from memory 8. The intermediate result pertaining to this contact is taken from memory 11 according to the provided address, in order to obtain it with the result of the current contact in column 61, Here, the end of the current contact is signaled to summarize and store in the memory 11 under the same address again.

The point of column 60 of the current contact provides an increase in area by one and a new maximum column value. The contour length is also increased by one, since there is an adjacent contour point in the previous contacting of the row 43 in the column 60. There is a determinate contour point. This also applies to the contour point just quoted. There was no change between determinate and undetermined contour points.

With the next clock is signaled that the contact is completed. The intermediate result of contacting from line 43 is combined with the last obtained by determining the absolute extreme values, adding the surface parts, adding the contour length, adopting the tonal value information, adding the number of changes between determined and undetermined contour points, and assuming the presence of undetermined contour points and the branch parameter is added. This summarized intermediate result is, as already mentioned, stored in the memory 11.

The next contact results from the line 44 in column 66. At this time it is not clear that the points belong to the same defect. It is created as in the first contact a new defect-related feature set with its own memory space in the memory 11. For this contacting, a change between deterministic and undetermined contour points was registered.

The processing of contacting the line 45 runs in the first section analogous to the first contacting of the line 44. From column 60 deterministic contour points are registered. However, a change between deterministic and undetermined contour points does not take place, since the contour section in column 66 terminates in a determined contour point of the preceding line.

From column 66, the current contact overlaps with a further contacting of the previous line 44. The repetitive overlap signals that this contacting is not an independent defect. The intermediate results are summarized in the manner already indicated. In addition, the resulting branch parameter is reduced by one, which now again indicates the value one. The address of the second defect is made available again in the memory 7. This ignores the intermediate result of the second defect.

The next lines of the defect are processed in the manner described.

In line 50 there is a repetitive overlap with a previous contact. In column 61, the first contact is summarized with the previous intermediate result. Column 68 summarizes the second contact with the new intermediate result. In addition, the branch parameter is incremented by one and now displays the value two. In order to guarantee an unambiguous defect affiliation in the next line to be processed, the address assigned to the defect in the current recognition memory, which in the meantime is the memory 9, is stored both after completion of the first contacting and the second contacting of the line 50.

In line 53, no contact takes place up to column 61. However, according to the previous contacting of the contour length, the number of changes between deterministic and undetermined contour points and the presence of undetermined contour points is updated. The branch parameter is decremented by one and now displays the value one.

In line 55, the defect is completed because the branching parameter, after decreasing by one, indicates the value zero.

Thereby, the logic circuit is caused to perform the aforementioned area significance test.

The log. Circuit 6 can both work in such a way that each pixel clock, the Inform ation is fully processed, the log.

Circuit is controlled with a clock frequency corresponding to an integral multiple of the pixel repetition frequency, as well as in such a way that the processing over at least two pixel clocks away takes place (pipelining).

A clock generation unit 14 generates control clocks which ensure a synchronous flow of image scanning, image generation, pixel delay and pixel processing.

The classification of the defects may e.g. be made in nine types. Examples of 9 types are shown in FIGS. 7 to 15 by comparison of desired and actual image.

2, an arrangement is shown which has two channels A and B for defect detection. The comparison between the target image and the actual image data is performed so that the channel A only processes the defects with the tone value one and the channel B those with the tone value zero. This has the advantage that two target images can be generated, both of which correspond to the data set which was used to produce the objectified images and describe the image content, but differ in terms of permissible tolerances due to on the one hand thickened and, on the other hand, thinned structures Value for the thickening or dilution is not constant, but much flour depends on the local conditions.

FIG. 16 shows two interrelated structural elements whose edges 69 and 70 are determined by the data record used to produce the objectified images and defining the image content. Due to possible tolerances, on the one hand a target image can be generated, which corresponds to thickened structures according to the edge layers 71 and 72, respectively, and on the other hand, one corresponding to thinned structures according to the edge layers 73 and 74, respectively.

The arrangement shown in Fig. 2 is composed essentially of the components of the arrangement shown in Fig. 1.

The binary actual image is generated by a device 1 in the manner described and output pixel by pixel.

With the aid of a gate 19, the channel A conjoins the direct actual image information conjunctively with the target image information negated by means of a gate 17, which corresponds to the thickened structures and is generated by a device 15. The delay devices 4a and 5a provide the required environmental information about the current pixel and the log. Circuit 6a, in conjunction with the memories 7a, 8a, 9a, 10a and 11a and register 12a, determines the parameters describing a defect. In this case, the tone value can be omitted as a parameter, of which this channel only defects with the tone value one are processed and the memory 11a therefore only contains these feature sets.

The channel B works analogously here. The actual image information negated with the aid of a gate 18 is conjunctively linked to the direct target image information, which corresponds to the thinned structures and is generated by a device 16, by means of a gate 20. The delay devices 4 b and 5 b provide the required environmental information to the current pixel and the log. Circuit 6b, in conjunction with the memories 7b, 8b, 9b, 10b and 11b and register 12b, determines the parameters describing a defect. In this case, the tone value can also be omitted as a parameter, since only defects with the tone value zero are processed by this channel and consequently the memory 11b only contains these feature sets.

The computer 13 takes the memory 10a or 10b, the addresses of the fully detected defects and takes according to the addresses the memories 11 a and 11 b, the parameter sets describing the defects and processes them in the specified manner.

The clock controller 14 synchronizes the processing in the channels A and B.

Claims (6)

A method for the exact image matching of an objectified image consisting of pixels with tone values of one and zero, which form structures with contours, with a CAD data set used to produce this image, wherein a binary ACTUAL image is generated by means of clocked scanning of the objectified image in synchronism with the generation of a target image adapted to the actual image from the CAD data set and corresponding pixels of target and actual image with respect to their tone values are compared with each other and thus a defect information is determined which determines defects in the actual image which are composed of pixels each having opposite tonal values to the corresponding points of the SETPOINT image, detecting the coordinates of each defect point and constructing and storing pixel arrays comprising, on the one hand, a SHOT frame and, on the other hand, corresponding pixel related defect information, and Pse udofehler be suppressed, as well as defects, if they fall below a predetermined limit and that sampling, generation and pixel processing are controlled by a pixel follower clock, characterized in that - That a defect information-containing image field from 6 pixels is formed, corresponding to one considered to be current IST pixel and according to his lying in the currently considered line two immediate neighboring points and corresponding to those 3 points immediately adjacent lying in the previous line 3 Points and - That an image field of the desired image of 9 pixels is formed by a, to be considered as current actual pixel, corresponding target pixel and its immediate, surrounding him neighboring points and - That the contour points of a defect in the current or previous line are determined by comparing the defect information of the current to be designated as the pixel of the current or previous line, each with its neighboring points of the defined image field and - That the Deferminiertheit a contour point of a defect by comparing the corresponding target pixel with its immediate target image neighbor points of the defined image field is determined and that there is determinant, if depending on the Defekttonwertes either the contour point of the defect corresponding target pixel or at least one of his immediate target image neighbor points is a contour point in the target image, and - That contiguous contour sections are detected, which differ by their determinateness and - That the number of changes between different contour sections of a defect, which correspond to the number of determinate contour sections, determined and the presence of undetermined contour sections is determined and with these two parameters and the Tonwertinformation a classification of the defects. 2. The method according to claim 1, characterized in that from the CAD data set according to approved global upper and lower error limits two target images are generated, with a target image taken into account the lower error limit and thus a diluted target image is created and SOLL-BiId considered the upper error limit and thus a thickened target image is created and that on the one hand in a data channel, the actual image data with the negated target image data of the thickened target image are linked and processed in this data channel only defects with the tone value 1 and that, on the other hand, in a second data channel, the negated actual image data are combined with the desired image data of the diluted target image, and only defects with the tone value O are further processed in this data channel. 3. The method according to claim 2, characterized in that the error limits are locally oriented. 4. The method of claim 1, 2 and 3, characterized in that the pixel processing takes place in at least two time stages and the time stages are fixed by a control clock, the clock sequence is an integer, the number of time increments corresponding multiple of the pixel follower clock. 5. The method according to claim 1, 2 and 3, characterized in that the pixel processing takes place in at least two time stages, each comprising exactly one pixel cycle clock and which are counted starting with the current pixel follow-up cycle. 6. Arrangement for image comparison with a sampling and at least one desired image generating device and at least one data processing channel, which consists of logic computing elements and memories, characterized in that the actual image is recorded by a scanning device whose output flows into at least one processing channel, in that an output of the sampling device is the input of a logic circuit whose second input is connected to an output of a target image generator, as well as the input of a first delay circuit whose 9 outputs lead to a logical processing unit and where the output of the logic circuit is the input of a second delay circuit forms whose 6 outputs also open into the logic processing circuit to which memory and a limit value register are connected and that these arrangement elements of a processing channel via a computer and a clock be controlled generating unit.