JP3111563B2 - Inspection equipment for printed wiring boards - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an inspection apparatus for detecting a defect shape of a wiring pattern on a printed wiring board.

[0002]

2. Description of the Related Art In a manufacturing process of a wiring pattern on a printed wiring board, a defect shape due to disconnection, short circuit, chipping, adhesion of dust and the like may occur. Therefore, various inspection devices for detecting such a defect shape have been proposed. Such an inspection device includes an imaging device such as a CCD camera that reads a wiring pattern on a printed wiring board, an A / D converter that converts an analog signal of the imaging device into a digital signal, and a defect shape from the digital image signal. There is an inspection apparatus having defect detection means for detecting. As this defect detection means, there is one using a feature extraction method as an inspection algorithm.

In the inspection apparatus using the above-described inspection algorithm, the pseudo defect shape may be output as a false report. Therefore, the pseudo defect shape is image-recognized by using a non-defective standard substrate, and a mask is set at a conforming point. A mask for performing the above-described process is prepared, and the true defect data is detected by comparing the mask with defect candidate data from the substrate to be inspected. That is, as shown in FIGS. 13 and 14, in the inspection of the wiring pattern 90, the inspection device may determine the fragmented portion 91 and the short-circuited portion 92 to have a defect shape. However, actually, the fragment portion 91 is an open end of a normal pattern even if it looks like a disconnection, and the short-circuit portion 92 is a normal connection portion.

Therefore, in such a case, a defect detecting means for selecting whether or not the data is true defect data is required. Conventionally,
Inspection equipment for this purpose is to inspect the wiring pattern of a normal standard board,
That is, there is a device that registers pseudo defect data in a memory and verifies the data at the time of actual inspection. That is, during the actual inspection, when inspecting the wiring pattern of the substrate to be inspected, the pseudo defect data in the memory is read out and compared with the defect candidate data detected from the wiring pattern. If the defect candidate data matches the pseudo defect data, the defect candidate data is determined to be not true defect data, and if not, it is determined to be true defect data. In the comparison, a mask table in which a mask is applied to a portion of the pseudo defect data is used.

FIG. 15 shows the above-mentioned determination method. That is, the pseudo defect data obtained from the normal wiring pattern is registered in the mask table 96. The cells 961 and 969 are masked as pseudo defect data in the mask table (this is referred to as mask data). Cells 962 to 967 that are not pseudo defect data are not masked. On the other hand, in the data table 95 obtained from the inspected wiring pattern, defect candidate data detected as a defect shape are stored in cells 951, 953, and 959. Therefore, the mask table 96 and the data table 95
Are compared, the defect candidate data of the cells 951 and 959 among the three defect candidate data coincide with the cells 961 and 969 of the pseudo defect data. Therefore, it is determined that the two data are not the defect shapes. On the other hand, the cell 953 of the defect candidate data is determined to be true defect data 973 because there is no matching pseudo defect data.

In the above inspection, the position of the standard substrate at the time of registering the pseudo defect data is made to coincide with the position of the substrate to be inspected. However, a slight displacement actually occurs. For this reason, the position of the mask based on the pseudo defect data is shifted, and accurate inspection cannot be performed. For example, if the mask dimension is 200 μm and the variation in the positioning between the standard substrate and the substrate to be inspected is ± 50 μm, the conforming point recognized as the defect candidate shape on the substrate to be inspected may deviate from the mask position. is there.

Therefore, in the above inspection method, in order to prevent false defect leakage in the collation processing, that is, to prevent the defect data from being judged as true defect data despite being originally pseudo defect data, masking of the data table is performed. Position correction is required. Therefore, the following two means are generally used as the position correcting means. One of them is an enlarged mask method in which a large mask is provided. Another method is to add alignment by image processing to improve positioning accuracy.

In the above-mentioned enlarged mask method, as shown in FIG. 16, a masking range is set in the mask table 81 with the cell 815 of the pseudo defect data as the center and the cells 811 to 814 and 816 to 819 adjacent thereto. 9 times as large as. Then, as shown in FIG. 17, in the data table 82, the defect candidate data cell 828 obtained in the inspection object is compared with the enlarged mask cells 811 to 819 in the mask table 81. As a result of the comparison, since the defect candidate data cell 828 is in the enlarged mask cells 811 to 819, it is determined that it is not true defect data. Further, a method of adding alignment by one image processing is a method of performing image processing of another system and correcting positional deviation.

[0009]

However, in the above-described enlarged mask method, when the printed wiring board has a fine (precision) pattern, defect candidate data close to a position corresponding to a mask cell is a true defect due to the enlarged mask. It is determined that it is not data. Therefore, there is a problem that the true defect data may be missed. Also,
The latter alignment method requires an image processing apparatus of another system, so that the cost of the apparatus is high, and the time required for alignment is long and the productivity is low. SUMMARY OF THE INVENTION The present invention has been made in view of the above circumstances, and an object of the present invention is to provide an inspection apparatus for a printed wiring board which can perform an accurate inspection without overlooking true defect data and does not require a positional deviation correction.

[0010]

An inspection apparatus according to the present invention comprises: an imaging device for reading a wiring pattern on a printed wiring board; and a defect detection device for selecting whether or not the data is true defect data based on an image signal of the imaging device. And data counting means for counting the true defect data selected by the defect detection means. The defect detection means is a rule for recognizing a defect shape from a binary image obtained from the imaging device. The defect point recognition algorithm data is written into the inspection algorithm part, and the conforming point enlargement algorithm data for arbitrarily expanding the number of shape conforming points in the input data two-dimensionally at the time of mask creation for the conforming data enlarging part. Algorithm for writing conforming point output algorithm data that simply outputs input data during inspection At the time of mask creation or inspection, the setting CPU unit recognizes the shape of a binary image of a standard substrate or a substrate to be inspected based on the defect shape recognition algorithm data set by the algorithm setting CPU unit, and generates pseudo defect data or defects. Inspection algorithm section that outputs the conforming data of the candidate data, and two-dimensional arbitrary expansion of the conforming point of pseudo defect data at the time of mask creation among the conforming data from the inspecting algorithm section according to the instruction from the algorithm setting CPU section. On the other hand, for the defect candidate data at the time of inspection, the conforming data enlarging section that does not expand the defect candidate data and the above conforming data from the conforming data enlarging section are respectively corrected in units of mask resolution, and the corrected defect shape conforming data The conforming data correction unit to be output and the conforming data A mask memory unit for storing the corrected defect shape conforming data from the unit as mask data, and checking the corrected defect shape conforming data from the conforming data correcting unit with the mask data from the mask memory unit during inspection. A printed wiring board inspection apparatus characterized by comprising a mask collation unit.

In the present invention, the most remarkable thing is
The above algorithm setting CPU for sending an instruction signal to an inspection algorithm unit and a conforming data enlarging unit as a defect detection unit
Unit, an inspection algorithm unit, a conforming data enlarging unit, a conforming data correcting unit, a mask memory unit, and a mask collating unit.

The pseudo defect data is data generated by recognizing the shape of a binary image of a standard substrate based on the defect shape recognition algorithm data from the algorithm setting CPU unit for mask generation. The algorithm data is set in advance as a rule for recognizing a defect shape. That is, the pseudo defect data is pseudo data that is inspected using a normal wiring pattern of a standard substrate and is recognized as a pseudo defect shape as if it were a defect shape, although it is originally a normal shape. .

The pseudo defect data is arbitrarily expanded two-dimensionally in a conforming data expanding section in a conforming data expanding section.
Further, it is corrected as described later in the adaptation data correction unit,
It is recorded in the mask memory unit as mask data. On the other hand, the defect candidate data is data created by recognizing the shape of the binary image of the substrate to be inspected based on the defect shape recognition algorithm data from the algorithm setting CPU unit. That is, the defect candidate data is a shape that is temporarily detected as a defect shape when inspecting a wiring pattern of a printed wiring board that is an object to be inspected, that is, data that is recognized as a defect candidate shape.

The defect candidate data is not enlarged in the conforming data enlarging section, but is sent to the conforming data correcting section as it is, where it is corrected as described later and collated with a mask based on the pseudo defect data. The resolution unit of the mask refers to the size of an image of the mask stored in one memory cell of the mask memory unit. The data tabulation unit is a unit that tabulates and records the data determined by the defect detection unit. In addition, since an image signal output from an imaging device is generally an analog signal, it is converted into a digital signal by an A / D converter to obtain a binary image.

In the inspection using the inspection apparatus of the present invention, there are a stage when a mask is created based on a standard substrate and an inspection stage for a substrate to be inspected. First, in the mask creation stage, the algorithm setting CPU reads out the defect shape recognition algorithm data from the dedicated ROM or the like, writes it in the inspection algorithm, and stores the matching point enlargement algorithm data in the dedicated RO.
M, etc., and write it to the compatible data enlargement unit. The enlargement ratio of the enlargement algorithm takes into account the positioning accuracy of the substrate, the pattern formation accuracy, and the like. Of course, an arbitrary enlargement ratio can be obtained by creating algorithm data of several stages of enlargement ratios and storing them in a ROM or the like.

In the inspection algorithm section, a binary image of the standard substrate is input, and a defect shape matching the internally set defect shape recognition algorithm data is searched from the input image (shape recognition). . Then, the presence / absence of a point (conforming point) conforming to the defect shape recognition algorithm data is signalized and output to the conforming data enlarging unit as pseudo defect data.

The conforming data enlargement section enlarges the area of the conforming point group in the inputted pseudo defect data in accordance with the previously set conforming point enlarging algorithm data. That is, the number of matching points is increased two-dimensionally around one point. Then, the enlarged pseudo defect data is output to the matching data correction unit. The conforming data correction unit corrects the enlarged pseudo defect data in units of mask resolution and outputs the corrected defect shape conforming data. This data is stored in the mask memory unit as mask data.

On the other hand, in the inspection stage, the algorithm setting CPU reads out the defect shape recognition algorithm data from its dedicated ROM or the like and writes it into the inspection algorithm. Similarly, the matching point output algorithm data is read out and written into the matching data expanding section. The conforming point output algorithm data at the inspection stage is an enlargement algorithm having an enlargement ratio of 1 and has no enlargement effect. In the inspection algorithm section, the 2
A value image is input, and a defect shape that matches the defect shape recognition algorithm data is searched from the input image. Then, when there is an algorithm matching point, it is output to the matching data expanding unit as defect candidate data.

The matching data expanding section outputs the input signal according to the matching point output algorithm data set before, without changing the logic of the input signal at all, that is, without expanding the mask as when creating a mask. Therefore, a signal that is logically the same as the input defect candidate data is output to the matching data correction unit. However, there is a time difference between the input signal and the input signal because the signal passes through the spatial filter constituting the enlargement unit. However, this is a necessary process for synchronizing with the enlarged pseudo defect data at the time of the previous mask creation. The conforming data correcting unit corrects the defect candidate data without the enlargement processing in units of mask resolution, and outputs the corrected defect shape conforming data to the mask matching unit.

The mask collation unit inputs the corrected defect shape conforming data of the defect candidate data,
The mask data in the mask memory section is read, and both are compared. Here, when the corrected defect shape conformance data of the defect candidate data is not included in the mask data, the defect candidate data is determined to be true defect data,
Sent to the data tabulation unit. If the defect candidate data is in the mask, it is determined that the data is not true defect data.

[0021]

Operation and Effect In the present invention, as means for providing a large effect, as described above, there is a process of enlarging a conforming point in pseudo defect data of a conforming data enlarging section at the time of mask creation. Therefore, a mask having an optimum size can be registered at an optimum position without applying an enlarged mask in mask cell units as in the related art.

That is, in the present invention, the area of the conforming point for the defect shape recognition algorithm data at the time of registering the mask is processed by using the conforming data enlarging unit so as to be larger than that at the time of the inspection. The enlargement unit at this time is a pixel unit or several pixel units, and is a fraction to one-tenth of the size of the mask cell. Therefore, when the center of the conforming point is located near the boundary of the mask cell, the conforming point surely reaches only the adjacent mask by the enlargement process, and is optimal enough to absorb the variation in the positioning accuracy of the work (printed wiring board). Dimension mask data can be created.

On the other hand, the above-described conventional enlarged mask method in units of mask cells expands the mask range to eight cells (a total of nine cells) adjacent to the mask cell of the pseudo defect data (FIGS. 3C to 3E, 16 and 17). for that reason,
Even if there is true defect data, the mask is too large and is masked, so that the true defect data may be missed. Further, once the mask data is registered for each mask cell as in the conventional method, only coarse correction can be performed in the subsequent mask processing. For this reason, in the present invention, before registering a mask, processing is performed on a pixel-by-pixel basis or on a pixel-by-pixel basis to create an optimal mask.

As described above, according to the present invention, since the minimum mask enlargement is performed only in the optimum direction, true defect data is not missed as in the above-described conventional case. Further, since the false defect shape is not erroneously detected, there is no need for a device for correcting the positional deviation of the substrate as in the conventional case. Therefore, according to the present invention, it is possible to provide an inspection apparatus for a printed wiring board which can perform an accurate inspection without overlooking true defect data and does not require a board position shift correcting apparatus.

[0025]

【Example】

First Embodiment A printed wiring board inspection apparatus according to an embodiment of the present invention will be described with reference to FIGS. As shown in FIG. 1, the inspection apparatus according to the present embodiment includes an imaging device 2 including a CCD camera for reading a wiring pattern 11 on a printed wiring board 10.
1, an A / D converter 22 for converting an analog signal of the imaging device 21 into a digital signal, a defect detection unit 23,
It comprises a data totaling master CPU unit 24 and a terminal 25.

The defect detecting means 23 comprises an inspection algorithm unit 3, a conforming data expanding unit 31, a conforming data correcting unit 33, a mask collating unit 34, and a defect data memory unit 35. Part 3
7. It comprises a mask memory section 38. The defect detecting means 23 is for detecting disconnection, and as shown in FIG.
In addition, it has defect detecting means such as a defect detecting means 301 for detecting a short circuit and a defect detecting means 302 for detecting a chip.

In the inspection by the above apparatus, first, mask data is created based on a standard substrate. At the stage of creating the mask, the master CPU for data aggregation is used.
Upon receiving an instruction from the section 24, the algorithm setting CPU section 3
In step 7, the defect shape recognition algorithm data is read from the dedicated ROM or the like, and is written to the spatial filter of the inspection algorithm unit 3. Also, the algorithm setting CPU unit 37 writes arbitrary matching point expansion algorithm data to the spatial filter of the matching data expansion unit 31.

In the inspection algorithm section 3,
An imager 21 and an A / D converter 2
2, and from this input image, a defect shape conforming to the defect shape recognition algorithm data written as described above is recognized. Then, the state of the presence / absence of a conforming point conforming to the algorithm data is signalized and output to the conforming data enlarging unit 31 as pseudo defect data.
The algorithm setting C
According to the matching point expansion algorithm data set by the PU unit 37, the area of the matching point group in the pseudo defect data is expanded and output to the matching data correction unit 33.

The conforming data correcting section 33 corrects the pseudo defect data in units of the resolution of the mask, and outputs the corrected data as the corrected defect shape conforming data. The corrected defect shape conformance data is stored in the mask memory unit 38 as mask data. Next, it enters the inspection stage. In this case, upon receiving a command from the master CPU unit 24, the algorithm setting CPU unit 37 reads out the defect shape recognition algorithm data from its dedicated ROM or the like and writes it into the spatial filter of the inspection algorithm unit 3.
Also, the algorithm setting CPU unit 37 writes into the spatial filter of the conforming data expanding unit 31 the conforming point output algorithm data that simply outputs the input data.

In the inspection algorithm section 3,
A binary image of the substrate to be inspected is input, and a defect shape conforming to the defect shape recognition algorithm data set internally as described above is recognized from the input image. Then, the state of the presence / absence of a conforming point conforming to the algorithm data is signaled, and if there is defect candidate data, this is output to the conforming data expanding section 31. Then, the matching data expanding unit 31 outputs the matching data of the defect candidate data to the matching data correcting unit 3 without expanding the area of the matching point group in the defect candidate data.

The conforming data correcting unit 33 corrects the defect candidate data in units of the resolution of the mask, and outputs the corrected data to the mask comparing unit 34 as corrected defect shape conforming data. The mask collation unit 34 inputs the corrected defect shape conformance data of the defect candidate data, reads the mask data in the mask memory unit 38, and compares them.

Here, when the corrected defect shape conformance data of the defect candidate data is not included in the mask data, the defect candidate data is determined to be true defect data and enters the defect data memory unit 35. The data is further sent to the data totaling master CPU 24 and displayed on the terminal 25. On the other hand, when the defect candidate data is in the mask, it is determined that the defect candidate data is not true defect data.

Next, the outline of the data processing of the conforming data expanding section 31 and the conforming data correcting section 33 will be described with reference to FIG. First, a case where defect shape recognition algorithm data is set in the inspection algorithm unit 3 will be described with reference to FIG. And
In the figure, a binary image having a disconnection shape in the vertical direction (represented by 1 and 0).
1 indicates a wiring pattern, and 0 indicates a substrate portion. Further, the above-described disconnection shape is recognized by the inspection algorithm unit 3.

In FIG. 2A, the dashed line shows the absolute position of the mask on the mask coordinates for reference, and shows mask cells 41 to 44. The size of the mask cells 41 to 44 is 10 pixels of the basic pixel of the binary image.
It is set to double. Next, the black circles shown in FIG. 2A are conforming points to which the rule of the inspection algorithm data of the disconnection shape conforms in the inspection algorithm section, and the group is referred to as a conforming point group 4. This matching point is the size of a basic image unit of the binary image.
The presence or absence of the matching point indicates the presence or absence of shape recognition.

Here, when focusing on the above-mentioned group 4 of conforming points, a plurality of conforming points forming a group can be seen. This is because a plurality of conformity points are derived when looking at the conformity while shifting to. In the inspection algorithm unit 3, the state of the presence or absence of the conforming point, that is,
Output as conforming data. Next, FIG. 2B shows a spatial filter in the conforming data enlargement unit 31, and a rule for enlarging and outputting if one of the conforming points shown in FIG. 2A matches the designated point shown in FIG. Is shown. FIG. 2C shows the matching points enlarged based on the above rule, that is, the enlarged matching points of the pseudo defect data.

Next, in the adaptation data correction unit 33,
The correction is performed in mask cell units based on the enlarged matching point of the pseudo defect data. At this time, as shown in FIG. 4C, the enlarged matching point is also included in the cells 42, 43, and 44. Therefore, when the above-described correction is performed on a mask cell basis, the cell is expanded as shown in FIG. The information 41 to 44 are all changed from “0 to 1” to form a mask, which is registered in the mask memory unit as mask data. Cell 4
5, 46 are not masked because they do not have enlarged matching points. That is, the information thus obtained is the corrected defect shape conformance data of the pseudo defect data, and is sent to the mask memory unit.

On the other hand, FIG. 2E shows a case where the conforming point is not enlarged in the conforming data expanding section 31 during the inspection, that is, a state where the conforming point of the defect candidate data is not enlarged. In this case, since the matching point group 4 of the defect candidate data exists only in the cell 41, the correction in the mask cell unit in the matching data correcting unit 33 is only the cell 41. Then, at the time of mask collation, FIG.
The corrected conformity data (inspection data) of the defect candidate data shown in FIG. 7 is compared with the mask data shown in FIG. At this time, the inspection data (cell 4 in FIG.
1), even if there is a position shift based on a slight position shift of the inspection substrate, the inspection data is mask data (FIG. 2).
(D) cells 41 to 44). Therefore, it is not determined as true defect data, and no false information is generated.

If this point is added a little more, what should be noted in FIG. 2 is the position of the matching point group 4 in the cell 41 at the time of inspection (FIGS. 2A and 2E). The matching point group 4 is shifted to the upper right of the cell 41, and the cell 4
It is located near 2,43,44. If there is no true defect data at the time of inspection due to a positioning error of the substrate to be inspected, etching unevenness, or the like, the matching point group 4 may enter the cells 42 to 44.
At this time, if the mask is an area of only the cell 41, since there are matching points in the other cells 41 to 44, an erroneous report is issued as true defect data.

However, in this embodiment, as described above, the conforming data of the pseudo defect data obtained by the inspection algorithm unit is enlarged by the conforming data expanding unit, and the mask data is created by the conforming data correcting unit. Therefore, the above-mentioned misinformation does not occur. Further, in the present invention, only four times as many mask cells are required. On the other hand, the conventional magnifying mask method uses 9
Requires twice as many mask cells. Further, the above will be described with reference to FIG. 3A and 3B show the present invention, and FIGS. 3C to 3E show the conventional enlarged mask method. These show the open end 910 of the disconnection pseudo defect shape in the pattern 90 (see FIG. 13) shown in FIG.

FIGS. 3A and 3C show superimposition diagrams of the conforming point of the defect shape recognition algorithm data and the coordinates of the mask memory, and FIGS.
(E) shows the state of the mask inside the mask memory. First, according to the present invention, as shown in FIGS.
01 is in the cells 41-44. Reference numeral 405
Is a fragment portion 91 of the pattern.

Therefore, as shown in FIG. 2, when the correction is performed by the relevant data correction unit, the relevant point
3B, masks are registered in the four mask cells 41 to 44, as shown in FIG. On the other hand, in the conventional enlarged mask method, as shown in FIGS.
02 is different from the above-mentioned FIG. 3A and is contained in one mask cell. Then, as shown in FIG. 3D, the registered mask cell 41 remains as it is when registered in the mask memory. Therefore, before matching in the mask matching unit,
The mask is enlarged to all the cells 42 to 49 adjacent to the cell 41. As a result, the size of the mask cell becomes nine times as large as the initial size.

As is known from the above, in the conventional enlarged mask method, the mask enlargement based on the pseudo defect data is 9 times. Therefore, as described above, there is a possibility that the true defect data is missed. On the other hand, in the present invention, the area of the conforming point is enlarged, and only the four cells 41 to 44 where the conforming point is located are used as mask cells. Therefore, it is possible to create a mask enlarged to a minimum corresponding to the displacement of the substrate, and it is almost impossible to miss true defect data.
Therefore, accurate inspection can be performed, and a device for correcting the positional deviation of the substrate is not required unlike the above-mentioned conventional device.

In the above example, as shown in FIG. 3A, the center of the enlarged conforming point 401 of the pseudo defect data is located at the upper right part of the cell 41, and this conforming point is included in four mask cells. The mask is registered. However,
When the center of the expanded conforming point 401 of the pseudo defect data is near the right center of the cell 41, the conforming point only extends over two mask cells 41 and 44, and the mask cell to be registered as a mask is 2 (cell 4
1 and 44).

Embodiment 2 Next, signal processing in the device shown in Embodiment 1 will be described.
This will be described with reference to the flowcharts of FIGS. First,
FIG. 4 shows a process of registering pseudo defect data at the time of creating a mask, that is, a process of creating mask data. In the figure, in step (hereinafter abbreviated) 501, it is determined whether or not a pattern of a target printed wiring board has a pseudo defect shape, and if there is no such pattern, the process ends.

On the other hand, when there is a pseudo defect shape, 50
In step 2, upon receiving a command from the data totaling master CPU unit 24, the algorithm setting CPU unit 37 sets arbitrary defect shape recognition algorithm data in the spatial filter of the inspection algorithm unit 3. Similarly, at 503, the algorithm setting CPU unit 37 sets arbitrary matching point expansion algorithm data in the spatial filter of the matching data expansion unit 31. Next, in step 504, a non-defective standard board is fixed on the inspection table. In step 505, the image is taken by the image pickup device 21 (one-dimensional CCD camera). Get.

Next, at 506, the inspection algorithm unit 3 recognizes a pseudo defect shape in the binary image, and
Generate pseudo defect data. Next, at 507, the conforming data enlargement unit 31 enlarges the conforming point of the input pseudo defect data based on the rules of the above-mentioned enlargement algorithm data, and outputs the conforming data. next,
In step 508, the adapted data correction unit 33 corrects the enlarged conformed data in units of mask cells, and registers the mask data in the mask memory unit 38.

Next, as shown in FIGS. 5 and 6, an inspection process is started. That is, at 601 in FIG.
Upon receiving a command from the U unit 24, the algorithm setting CPU
The unit 37 sets arbitrary defect shape recognition algorithm data in the spatial filter in the inspection algorithm 3. At 602, the algorithm setting C is performed in the same manner as described above.
The PU unit 37 sets algorithm data that does not expand the input to the spatial filter of the adaptive data expanding unit 31.

Next, at 603, the substrate to be inspected is fixed on the inspection table, and at 604, the substrate to be inspected is imaged by the one-dimensional CCD camera, and a binary digital image signal is obtained by the A / D converter. . Next, at 605, the inspection algorithm unit 3 recognizes a defect candidate shape in the binary image and generates matching data of the defect candidate data. next,
In 606, the conforming data expanding unit 31 outputs the same data as the input to the conforming data correcting unit 33 without expanding the conforming data.

Next, the process proceeds to 607 in FIG. 6, where the adaptation data correction unit 33 corrects the adaptation data to the size of a mask cell unit and outputs it to the mask comparison unit. Then, the process proceeds to 609, where the mask data is read from the mask memory unit, and the mask matching unit 34 checks the matching data of the defect candidate data against the mask data. Then, as a result of the comparison, only the conforming data of the unmasked portion is determined as true defect data and recorded in the defect data memory unit 35. Then, at 610, the data in the defect data memory unit 35 is read out by the master CPU unit 24, the data is totaled, and the result is displayed on the terminal 25. Then, in 611, it is determined whether or not the inspection has been completed. If the inspection has been completed, the inspection ends. To continue, the process returns to 603 again.

Third Embodiment As shown in FIG. 7, this embodiment shows a case where a spatial filter of 3 × 3 pixels is used for the basic configuration of the inspection algorithm unit shown in the first embodiment. In the example of the input image on the left side of the figure, as indicated by a broken line 50, 3 × 3 pixels are set as the input image here. Then, eight spatial filters are connected to the OR circuit. Then, the defect shape recognition algorithm data applied to these eight spatial filters recognizes the pseudo defect data or the defect candidate data, and outputs the matching data.

Fourth Embodiment As shown in FIG. 8, this embodiment shows a block diagram in the inspection algorithm unit 3 using the spatial filter shown in the third embodiment. The binary image input from the A / D converter is supplied to a shift register 51, a multiplexer 5
2. Processed by the RAM 53 and output as pseudo defect data via the OR circuit.

An address bus from the algorithm setting CPU section 37 to the multiplexer 52,
A data bus is connected to the state buffer. A system clock that drives the inspection algorithm unit 3 is a pixel clock, and drives a line memory and a shift register. A one-dimensional binary image is developed two-dimensionally by a combination of a line memory and a shift register. Then, the shape of the two-dimensional binary image is recognized by the RAM 53, and the result is output to the matching data enlargement unit via the OR circuit.

Fifth Embodiment As shown in FIGS. 9 and 10, this embodiment exemplifies the adapted data expanding section shown in the first embodiment. First, FIG.
Shows a block diagram of the adaptation data enlargement unit 31. The conforming data output from the inspection algorithm unit 3 is a shift register 511, a multiplexer 521, and a RAM.
531 respectively. That is, at the time of mask creation, the pseudo defect data is enlarged two-dimensionally.
On the other hand, during inspection, the defect candidate data is not enlarged.

The multiplexer 521 is connected to nine address buses from the algorithm setting CPU section 37 and one data bus to the three-state buffer. The system clock for driving the adaptive data expansion unit 31 is a pixel clock, and drives the line memory and the shift register 511. In this example, since there are nine address buses, the expansion rule of the 3 × 3 filter is set by the algorithm setting CPU unit.
It can be freely changed and set.

Next, FIG. 10 shows the principle of the matching data expanding unit. First, as shown in FIG. 10 (a), one input matching point data is enlarged (approximately 9 times) as enlarged matching point data and output to the matching data correction unit. FIG. 10B shows a principle circuit. In this circuit, two stages of line memories and three shift registers are used to form a 3 × 3 spatial filter. The output of the shift register is ORed for enlargement.

In order to further increase the size, the number of line memories and shift registers is increased. In order to make the enlargement ratio variable, a method of replacing the OR portion with a memory is conceivable (look-up table method).
By rewriting the contents of the memory, the input to be ORed can be selected (specified point setting), so that the enlargement ratio and enlargement pattern can be freely changed.

Embodiment 6 This embodiment shows, as shown in FIGS. 11 and 12, a circuit example and a timing chart of a suitable data correction unit when the size of a mask cell is 10.times.10 pixels. The pseudo defect data from the inspection algorithm unit 3 is stored in a shift register (10
(Shift by the number of pixels) 56, and through an OR circuit, enters a D flip-flop 57. Then, the mask data whose mask cell interval has been corrected enters the mask comparison unit 34 or the mask memory unit 38.

The pixel clock 581 enters the shift register 56. When the mask cell has a width of 10 pixels, the pixel clock 581 is a 1/10 frequency dividing circuit 58.
, And enters the D flip-flop 57 at the rate of latch once every ten times. The pixel clock is input by one pixel clock. Then, the section of the mask width (10 in this example)
If even one pixel has pseudo defect data in one pixel, the state "H" is maintained between one mask cell with a delay of one mask cell. FIG. 12 shows a timing chart and its inputs and outputs in the circuit of FIG. The pseudo defect data after the mask cell interval correction is the mask cell image width (10 clocks). At time 2 on the output side, it can be seen that the defect shape conformance data exists during this time.

[Brief description of the drawings]

FIG. 1 is a block diagram of an inspection apparatus according to a first embodiment.

FIG. 2 is a view for explaining expansion of the area of a conforming point in the first embodiment.

FIG. 3 is a comparative explanatory diagram of a mask memory according to a first embodiment of the present invention and a mask memory according to a conventional example.

FIG. 4 is a flowchart of a mask creation process according to a second embodiment.

FIG. 5 is a flowchart of an inspection process according to the second embodiment.

FIG. 6 is a flowchart of an inspection process continued from FIG. 5;

FIG. 7 is an explanatory diagram illustrating the operation of an inspection algorithm unit according to a third embodiment.

FIG. 8 is a block diagram of an inspection algorithm unit according to a fourth embodiment.

FIG. 9 is a block diagram of a matching data expanding unit according to a fifth embodiment.

FIG. 10 is a view for explaining the principle of expanding a conforming point in the fifth embodiment.

FIG. 11 is a block diagram of a matching data correction unit according to a sixth embodiment.

FIG. 12 is a timing chart at the time of inspection in the sixth embodiment.

FIG. 13 is an explanatory diagram of a pseudo defect shape in a pattern of a printed wiring board.

FIG. 14 is an explanatory diagram of a pseudo defect shape in a pattern of a printed wiring board.

FIG. 15 is an explanatory diagram showing a relationship between defect candidate data and true defect data.

FIG. 16 is an explanatory view of a conventional enlarged mask method.

FIG. 17 is an explanatory view showing a problem of the conventional enlarged mask method.

[Explanation of symbols]

 10. . . Printed wiring board, 11. . . Pattern, 4. . . Conformity points, 41-49. . . cell,

──────────────────────────────────────────────────続 き Continued on the front page (58) Fields surveyed (Int. Cl. ⁷ , DB name) G01N 21/84-21/958 G01B 11/00-11/30 G06T 1/00-9/40

Claims (1)

(57) [Claims] An imaging device for reading a wiring pattern on a printed wiring board; a defect detection unit for selecting whether or not the data is true defect data based on an image signal of the imaging device;
Data collection means for totalizing the true defect data selected by the defect detection means, wherein the defect detection means has a defect shape which is a rule for recognizing a defect shape from a binary image obtained from the imaging device. Recognition algorithm data is written into the inspection algorithm section, and the adaptive data enlargement section uses adaptive point enlargement algorithm data for arbitrarily two-dimensionally increasing the number of shape adaptation points in the input data when creating a mask. An algorithm setting CPU unit for writing matching point output algorithm data that simply outputs input data as it is, and a standard board based on the defect shape recognition algorithm data set by the algorithm setting CPU unit during mask creation or inspection. Or, the shape of the binary image An inspection algorithm unit for outputting matching data of the pseudo defect data or defect candidate data,
In accordance with the instruction from the algorithm setting CPU unit, of the conforming data from the inspection algorithm unit, for the pseudo defect data at the time of mask creation, the conforming point is two-dimensionally arbitrarily enlarged, while for defect candidate data at the time of inspection, A conforming data enlargement unit that does not perform enlargement, a conforming data correcting unit that corrects both the conforming data from the conforming data expanding unit in units of a mask resolution and outputs the corrected defect shape conforming data, A mask memory unit for storing the corrected defect shape adaptation data from the adaptation data correction unit as mask data; and a corrected defect shape adaptation data from the adaptation data correction unit during inspection and the mask data from the mask memory unit. A print characterized by comprising a mask matching unit for matching Inspection apparatus of the line board.