JP2002310630A - Pattern inspecting device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To correctly detect a pattern by using a high sensitivity pattern by reducing the influence due to positional dislocation of an inspection pattern and contraction of a base material in a pattern inspecting device. SOLUTION: The inspection pattern of an IC package 1 is captured in by a camera 3. A captured image is held in an image memory 5 and is binarized by a binarizing circuit 6. A characteristics extracting operator, having a characteristic extracting pattern including defects which are to be detected in advance are held by a characteristic extracting circuit 7A, and defects are detected by scanning this operator. A nondefective characteristics extracting pattern is stored in a characteristics extracting circuit 7B, and an inspection excluding area is detected by scanning this pattern. A defect image being not an inspection excluding defect is selected, and the overall defect is detected by discriminating an image on the basis of this defect image.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a pattern inspection apparatus for precisely inspecting a pattern of an IC package, a printed circuit board or the like.

[0002]

2. Description of the Related Art In IC packages and printed circuit boards,
Various patterns are formed by a method such as print plating. These are becoming smaller year by year due to the miniaturization of electronic components,
The wiring has also been miniaturized. Since these patterns may be partially missing or partially bulged, pattern inspection is required. In the inspection at the time of pattern formation of an IC package, a short circuit or a disconnection of the inspection pattern is inspected by a continuity test called a continuity checker. Defects with large protrusions due to manufacturing defects and insufficient insulation spacing, and defects in which the wiring portion of the pattern is thinner than the design value and lacks strength, cannot be inspected by a continuity inspection, but has a significant effect on quality. Is a defect. Although there is no short circuit or disconnection, it is necessary to optically detect these defects. Due to the miniaturization of electronic components, such inspections have shifted from visual inspections to mechanical inspections using television cameras, and various inspection methods have been proposed.

The following inspection methods have been proposed as conventional inspection methods. First, there is an inspection method called a perfect comparison method in which an inspection pattern is read and its position and width are compared with a reference master pattern and detected.

A method called cluster comparison for checking the number of test patterns and the area and position of each test pattern has been proposed. In the cluster comparison, it is possible to increase the detection sensitivity of a short circuit or a disconnection of a long wiring.

Further, the detected inspection pattern is binarized,
A feature extraction method is known in which a binarized image is calculated using a feature extraction operator to calculate a defective area.
The operator for feature extraction is an image pattern of a predetermined size smaller than the detected image, and a pattern predetermined so that a predetermined pixel has a detection or non-detection level so as to have a defect feature. . This operator scans over the entire surface of the inspection pattern, and detects a chip in the width direction, a protrusion, or the like depending on whether or not the operator matches the feature extraction operator. According to this method, a defect can be effectively detected even if there is a relative displacement due to a pattern displacement or a contraction of the base material forming the pattern.

[0006]

In the pattern inspection, the positional accuracy of the wiring and the accuracy of the line width may be poor, but
Even when the area is small, the chipping in the width direction or the protrusion or short-circuit when the space between the cutting patterns is at a narrow position becomes a serious defect.
Therefore, even when the inspection pattern is slightly thinner than the master pattern as a whole, the matching is not good, but it should be handled as a good product. If there is a chip or a protrusion in the width direction, the chip area is small but it must be defective. However, the conventional inspection method using the perfect comparison method has a drawback that it is difficult to determine whether such a defect is good or not effectively, and the defect is easily affected by shrinkage of the base material. Further, if the detection sensitivity is increased, a false report is likely to occur, and if the false detection is to be reduced, the sensitivity is lowered.

The above-described cluster comparison method has a drawback that it is difficult to detect a chip, a break, or a protrusion at an end of an inspection pattern.

In the method based on the feature extraction method, it is necessary to exclude the inspection position from the inspection area in order to invalidate the detection of a specific shape such as a good shape resembling a defective shape.
However, it is difficult to determine the absolute position due to the relative displacement due to the contraction of the base material, and it is difficult to flexibly cope with the method using the area memory. For this reason, even if a feature extraction pattern having high detection sensitivity is prepared, a false report of a positional shift is likely to occur, and there is a drawback that a false report is generated when the detection sensitivity is increased in an inspection of a green sheet or the like with low positional accuracy. Further, there is a drawback that the detection sensitivity is reduced in order to reduce false reports.

SUMMARY OF THE INVENTION The present invention has been made in view of the above-described problems caused by the conventional pattern inspection, and reduces the influence of the positional deviation of the inspection pattern and the relative deviation due to shrinkage of the base material on which the inspection pattern is formed. It is another object of the present invention to reduce the number of false reports and detect defects.

[0010]

According to a first aspect of the present invention, there is provided an image pickup apparatus for picking up an inspection pattern, and a binarization for binarizing an image picked up by the image pickup apparatus into a pattern portion and other portions. And a first feature extraction unit that scans a binarized image obtained by the binarization unit with a specific extraction pattern for defect detection, and detects a defective pixel by detecting a position of a matching image. Scanning a binarized image obtained by the binarizing unit with a feature extraction pattern for determining a predetermined non-inspection region, and detecting a non-inspection region by detecting a position of a matching image. A feature extraction unit,
A discriminating unit for discriminating a pattern abnormality based on a defective pixel extracted by the first feature extracting unit excluding a region extracted by the second feature extracting unit. It is.

According to a second aspect of the present invention, there is provided an image pickup apparatus for picking up an inspection pattern, a binarizing section for binarizing an image picked up by the image pickup apparatus into a pattern portion and other portions,
A first feature extraction unit that scans a binarized image obtained by the binarization unit with a specific defect detection extraction pattern and detects a defective pixel by detecting a position of a matching image; Second feature extraction for detecting a non-inspection area by scanning a binarized image obtained by the binarization unit with a feature extraction pattern for determining a predetermined non-inspection area and detecting a position of a matching image Unit, a discriminating unit for discriminating a defective pixel extracted by the first feature extracting unit excluding an area extracted by the second feature extracting unit, and a first predetermined pixel An expansion / contraction unit that expands the image expanded by the number of pixels by a second number of pixels, and determines an abnormality of the pattern based on the output of the expansion / contraction unit. .

The invention of claim 3 of the present application is directed to claim 1 or 2
Wherein the first and second feature extraction units scan only a predetermined inspection area in the binarized image taken and binarized to detect defective pixels. Things.

[0013]

(First Embodiment) FIG. 1 is a block diagram showing the configuration of a pattern inspection apparatus according to a first embodiment of the present invention. In this figure, IC package 1
Is an inspection target, the inspection pattern is imaged by the camera 3 while being illuminated by the illumination 2. The camera 3 is a camera such as a two-dimensional CCD camera or a line drive type CCD camera that can capture image data at high resolution, and is, for example, 1024 × 1024 or 4000 × 4000.
Having the following resolution. The signal from the camera 3 is temporarily stored in the image memory 5 via the preprocessing circuit 4. The image memory 5 is cascaded with a binarization circuit 6 and first and second feature extraction circuits 7A and 7B. The determination circuit 8 determines a defective pixel based on the output from the feature extraction circuit, and the counting circuit 9 counts the result. The control CPU 10 is a CPU for performing each of these processes, and is connected to an output unit 11 for outputting a result of pass / fail determination and an operation unit 12 for advancing settings and operations.

The binarizing circuit 6 binarizes the image data of the inspection pattern based on the luminance level of one screen held in the image memory 5. Image memory 5 for binarization
Are statistically processed, a threshold value is calculated and binarized. For example, if the frequency of the luminance level is different between the part with copper foil and the part without copper foil, by setting a threshold value in the middle, the optimal binarization according to the detection target and the lighting condition at that time Processing can be performed. The feature extraction circuit 7A extracts a defective portion of the inspection pattern from the binarized image data using a feature extraction operator described later. Also feature extraction circuit 7
B scans the image data using an exclusion feature extraction operator that excludes inspection and extracts a portion that is not determined as a defect in the inspection pattern.

The judging circuit 8 discriminates the area extracted by the feature extracting circuit 7A as a defective pixel except for the area detected by the feature extracting circuit 7B, and outputs it to the counting circuit 9. The counting circuit 9 determines the number of pixels remaining as defects thus detected for each defect, counts the number of defective pixels, and if the number exceeds a predetermined threshold value, the output unit 11 determines that the pattern is defective. Output via

If the feature extraction operator used in the first feature extraction circuit 7A detects, for example, a terminal portion of a copper foil pattern of a wiring board of the IC package 1, the feature extraction operator matches a defect of the inspection pattern. Pattern.
FIG. 2 (a) shows an example of this, which is composed of 33 × 33 pixels, of which a copper foil pattern is detected at a predetermined pixel position indicated by a white circle and a copper foil pattern is detected at a predetermined pixel position indicated by a black circle. This is to extract patterns that match those that are not performed. Here, the center pixel indicates the target pixel. It is assumed that a desired number of such feature operators are set in advance based on various patterns formed on the IC package 1. For example, for an inspection pattern of an IC package composed of only horizontal and vertical patterns, the inspection pattern shown in FIG.
As shown in (b), this is 90 °, 180 °, 270 °
Only the rotated one is sufficient.

On the other hand, the feature extraction operator used in the second feature extraction circuit 7B is a feature extraction pattern for detecting a feature pattern excluding inspection from among those having a defect feature detected by the feature extraction circuit 7A. FIG. 3 (a) shows an example of this, which is composed of 33 × 33 pixels, of which a copper foil pattern is detected at a predetermined pixel position indicated by a black circle and a copper foil pattern is detected at a predetermined pixel position indicated by a white circle. This is to extract patterns that match those that are not performed.
Here, the center pixel indicates the target pixel. It is assumed that a desired number of such feature operators are set in advance based on various patterns formed on the package 1. For example, for an IC package inspection pattern composed of only horizontal and vertical patterns, FIG.
Based on the structure shown in FIG. 3A, only the structure obtained by rotating the structure by 90 °, 180 °, and 270 ° as shown in FIG.

Next, the operation of this embodiment will be described with reference to inspection patterns and flowcharts. FIG.
Is a flowchart showing this operation. First, in step 21, a pattern formed of ceramic is illuminated by the illumination 2, and the camera 3 is used to image the copper foil pattern of the IC package 1. The captured image is pre-processed by the pre-processing circuit 4 and written into the image memory 5 (step 22). In the binarization circuit 6, the frequency of luminance is shown in FIG.
As shown in (b), a binarization process is performed using the intermediate value between the two peak values of the frequency with respect to the luminance as the threshold Th (step 23). The binarized image is stored in the image memory 5 again. Next, in step 24, a feature extraction process is performed by the feature extraction circuit 7A.

FIG. 5A shows an image of a part of the inspection pattern of the inspection object held in the image memory 5. Here, it is assumed that there are two small patterns on the upper, lower, left, and right sides of the substantially square pattern at the center, respectively, and that there is a large defect on the left side of the center pattern. When a defect is detected from the inspection pattern by the feature extraction circuit 7A using the feature extraction pattern shown in FIG. 2B, a defect as shown in FIG. 5B is detected. This is because not only the defects D1 and D2 detected around the left side of the central pattern, but also the corners of the central substantially square pattern and the six square patterns around it are detected. Such a defect is based on the fact that the periphery of the corner is formed round, and there is no need to detect it as a defect. Therefore, the image memory 5 is scanned by the feature extraction circuit 7B according to the feature extraction pattern as shown in FIG. 3B (step 25). FIG. 6A shows a defect pattern thus detected from the feature extraction circuit 7B.

The judgment circuit 8 extracts the area detected by the feature extraction circuit 7A except for the portion detected by the feature extraction circuit 7B. In this case, as shown in FIG.
Only the detected defects D1 and D2 in the peripheral portion of the defective pixel can be extracted from the detected patterns. The number of extracted pixels is totalized by the totalizing circuit 9, and the quality of the inspection pattern is determined based on the total number. In this way, unnecessary defects such as patterns are not detected in a ceramic base or the like having rounded corners, and the sensitivity of defects that need to be detected can be improved.

(Second Embodiment) Next, a second embodiment of the present invention will be described with reference to FIG. The same parts as those in the above-described first embodiment are denoted by the same reference numerals, and detailed description is omitted. In this embodiment, a pattern as shown in FIG. 6B is extracted by the determination circuit 8 except for an uninteresting pattern detected by the feature extraction circuit 7B, and the extracted image is input to the expansion / contraction circuit 13. You. The expansion / contraction circuit 13 expands the defective pixel obtained here by a predetermined pixel, and then contracts the defective pixel. The expansion is performed by expanding, for example, three pixels in all directions with respect to the detected defective pixel. In this way, for example, the X-axis, Y
Thus, a square defect image of 7 pixels on both axes is obtained. At the time of contraction, a predetermined number for this expanded pixel,
For example, the defect image is contracted inward by four pixels. In this way, when a plurality of defects are united due to expansion, the defects do not disappear even when contracted, so that a defective portion can be extracted. The number of reduced pixels may be greater than or equal to the number of expanded pixels, or less than or equal to the number of expanded pixels. The output of the expansion / contraction circuit 13 is input to the counting circuit 9.

Next, the operation of the present embodiment will be described with respect to portions different from the first embodiment. The determination circuit 8 extracts the defective pixels extracted by the feature extraction circuit 7A except for the unquestionable patterns as described above. Expansion / contraction circuit 1
3 expands the remaining defect by three pixels in all directions, and then contracts the defect image inward by four pixels. In this way, the remaining defects are detected, and the counting circuit 9 counts the number of pixels of the defects. If it is equal to or less than the predetermined number of pixels, it is determined that there is no abnormality. In this way, even if the wiring arrangement accuracy and the line width accuracy are poor, the defect can be detected without being affected by the relative displacement due to the displacement of the inspection pattern or the contraction of the base material. In addition, since the expansion ratio, the contraction ratio, and the number of pixels for quality determination can be arbitrarily selected, flexible detection sensitivity can be set according to the intended use.

In this embodiment, all the detected images are binarized and inspected by using a specific feature extraction operator. However, an area memory is provided, and an area to be inspected is set. It goes without saying that only the area can be the object of inspection. In addition to the feature extraction patterns, not only the lack of patterns but also the feature extraction patterns corresponding to various defects such as protrusions, intervals between patterns, and pattern thickness are set in advance, and each of the feature extraction patterns is set in the inspection area. It goes without saying that it can be applied to detect defects or to exclude certain patterns from defects.

[0024]

As described in detail above, according to the first to third aspects of the present invention, since inspection is performed except for a part that can be erroneously detected, a high-sensitivity feature pattern is used to achieve high sensitivity. Defects can be detected, and unnecessary portions are not detected as defects even if the pattern is used. Even if the wiring position accuracy and line width accuracy are poor, it is determined to be a good product.If the area is small, if the height in the width direction or the position between the patterns is narrow, it can be determined to be a serious defect. The effect of being less susceptible to relative displacement due to shrinkage of the base material forming the pattern and reducing malfunctions is obtained.

[Brief description of the drawings]

FIG. 1 is a block diagram showing a configuration of a pattern inspection apparatus according to a first embodiment of the present invention.

FIG. 2 is a diagram showing an example of a feature extraction operator used in the present embodiment.

FIG. 3 is a diagram illustrating an example of a pattern for detecting an inspection exclusion area.

FIG. 4 is a flowchart showing an operation of the pattern inspection apparatus according to the present embodiment.

5A is a diagram illustrating a pattern to be inspected, and FIG. 5B is a diagram illustrating a detected defect detection pattern;

FIG. 6A is a diagram illustrating an exclusion area detected by an inspection exclusion detection pattern, and FIG. 6B is a diagram that is selected as a final defect detection.

FIG. 7 is a block diagram illustrating a configuration of a pattern inspection apparatus according to a second embodiment of the present invention.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 IC package 2 Lighting 3 Camera 4 Preprocessing circuit 5 Image memory 6 Binarization circuit 7A, 7B Feature extraction circuit 8 Judgment circuit 10 Control CPU 11 Output unit 12 Operation unit 13 Expansion / contraction circuit

 ──────────────────────────────────────────────────続 き Continuing on the front page F term (reference) 2F065 AA49 AA56 BB02 BB24 CC01 CC17 DD04 FF04 JJ03 JJ26 QQ08 QQ24 QQ31 QQ39 SS04 UU05 2G051 AA61 AA65 AB07 CA03 CB01 EA11 EA12 EA14 EB01 A03B02 A03 EB09 ED09 BA02 CA08 CA12 CA16 CB06 CB12 CB16 CC01 CE09 CE12 DA03 DA16 DB02 DB05 DB08 DC01 DC33

Claims (3)

[Claims] 1. An imaging device for imaging an inspection pattern, a binarization unit for binarizing an image captured by the imaging device into a pattern part and another part, and a binary obtained from the binarization unit A first feature extraction unit that scans a digitized image with a specific extraction pattern for defect detection and detects a defective pixel by detecting a position of a matching image; and a binarization obtained by the binarization unit. A second feature extraction unit that scans the image with a feature extraction pattern that determines a predetermined non-inspection area, and detects a non-inspection area by detecting a position of a matching image; and a second feature extraction unit. And a determining unit for determining a pattern abnormality based on the defective pixels extracted by the first feature extracting unit excluding the region extracted in step (a). 2. An image pickup device for picking up an inspection pattern, a binarizing unit for binarizing an image picked up by the image pickup device into a pattern part and another part, and a binary value obtained from the binarizing unit. A first feature extraction unit that scans a digitized image with a specific extraction pattern for defect detection and detects a defective pixel by detecting a position of a matching image; and a binarization obtained by the binarization unit. A second feature extraction unit that scans the image with a feature extraction pattern that determines a predetermined non-inspection area, and detects a non-inspection area by detecting a position of a matching image; and a second feature extraction unit. A determination unit for determining a defective pixel extracted by the first feature extraction unit excluding the region extracted in the above, and expanding the detected defective pixel by a first predetermined number of pixels,
A dilation unit that reduces an image dilated by a second number of pixels to the inside, and determines a pattern abnormality based on an output of the dilation unit. 3. The method according to claim 1, wherein the first and second feature extraction units scan only a predetermined inspection area in the binarized image that has been imaged and binarized to detect a defective pixel. 3. The pattern inspection apparatus according to claim 1, wherein: