JP2691794B2 - Defect inspection equipment - Google Patents

Description

Description: TECHNICAL FIELD The present invention relates to a defect inspection apparatus for inspecting the presence or absence of a defect using a density signal obtained by digitizing an image signal obtained by scanning an inspection object. .

(Technical background of the invention) A defect inspection apparatus is known which optically scans the surface of a steel plate, a plastic film, paper or the like to detect scratches on the surface or internal defects. Heretofore, the image signal obtained by scanning the inspection object is compared with a preset threshold value, and if the image signal is larger or smaller than this threshold value, it is determined to be a defect.

However, in this method, when the image signal contains a noise component, the noise component may be determined to be a defect, and there is a problem that the defect inspection accuracy is lowered.

(Object of the Invention) The present invention has been made in view of such circumstances,
An object of the present invention is to provide a defect inspection apparatus capable of eliminating the influence of these noises and increasing the defect detection accuracy when the image signal obtained by scanning the inspection target contains noises.

(Structure of the Invention) According to the present invention, an object of the present invention is to provide a defect inspection apparatus for detecting a defect of an inspection object by using a density signal obtained by digitizing an image signal obtained by scanning the inspection object. Table means for selecting and outputting one of a plurality of density gradation conversion tables for converting a predetermined density range to a constant density, and density conversion for converting the density signal using the density gradation conversion table Means, multi-valued means for multi-valued density signals after the density conversion, and defect detection means for detecting an image portion in which the multi-valued density signal exceeds a predetermined density level as a defect and outputting a defect signal. A defect inspection apparatus comprising:

If the density signal after density conversion is subjected to spatial filtering by a differential filter and then multivalued, the contour of the image of the defect is emphasized, and the defect detection accuracy is further improved. If the image smoothing process is performed after the spatial filtering process by the differential filter, the detection by noise is further reduced and the defect detection accuracy is further improved.

Further, it is more convenient if the density signal converted in density or the multi-valued density signal can be displayed on the monitor because the defect can be visually recognized.

A plurality of density gradation tables having different settings are previously stored in the memory, and a table to be used is selected manually or automatically according to the inspection target. When the setting is changed or the usage table is selected automatically, the background density can be obtained by using the density histogram in the predetermined image area.

(Function) Since the digitized density signal is converted into a constant density in which the noise included in the predetermined density range including the background density becomes the background density by the density gradation conversion table, the density signal after the density conversion has the background There is no noise in the part. Therefore, noise disappears from the background of the image, and the defect detection accuracy is improved. Even if the density signal after the density conversion is subjected to the spatial filtering process by the differential filter, the noise in the background portion is not emphasized, and the defect detection accuracy is improved.

(Embodiment) FIG. 1 is a block diagram showing the configuration of an embodiment of the present invention.
FIG. 2 is a diagram showing an embodiment of a density gradation conversion table and input / output density signals.

In this embodiment, the setting of the conversion table can be manually changed while watching the image displayed on the monitor.

In FIG. 1, reference numeral 10 is an object to be inspected, such as a steel plate, a plastic film or paper, which is wound from a supply roll 12 to a winding roll 14. 16 is a laser light source. This light source
Laser light 18 emitted from 16 is a polygonal mirror that rotates.
It is guided to the main scanning line 22 of the inspection object 10 by 20 and scans on the main scanning line 22 from left to right. A light guide rod 24 is disposed in the vicinity of the main scanning line 22 so as to face it, and the reflected light of the surface of the inspection object 10 of the laser light 18 scanned on the main scanning line 22 enters the light guiding rod 24. Photomultiplier tubes (photomultipliers) 26 (26a, 26b) are attached to both ends of the light guide rod 24, and the intensity of the reflected light entering the light guide rod 24 is detected by these photomultiplier tubes 26. It

The outputs of both photomultiplier tubes 26a and 26b are added by adder 30 via a preamplifier (not shown) to obtain analog image signal x. This analog image signal x is a grayscale signal corresponding to the property of the surface of the inspection object 10 or inside.

The analog signal x is converted by the A / D converter 32 into a digital density signal y having a predetermined gradation (for example, 256 gradations). The density signal y is converted in density gradation by the density converting means 34 and displayed on the television monitor 36. Here, for the density gradation conversion, for example, a table of characteristics shown in FIG. 2 is used as one of the plurality of tables stored in the table means 38. In FIG. 2, the horizontal axis represents the density of the input density signal y, and the vertical axis represents the output density signal Y after density conversion. These density signals y and Y are, for example, 25
There are 6 gradations. In addition, this table shows a constant density (for example, an intermediate density) within a constant density width a on both sides of the background density c.
128) and outside this width a with a slope b of maximum (25
5) and the minimum density (0).

In this embodiment, the setting values a, b, c of this table can be changed by the manual setting means 40. That is, the operator operates this setting means 40 while observing the image on the television monitor 36 so that the noise in the background area disappears.

Further, the density signal after density conversion is compared with a predetermined threshold value in the multi-value quantization means 42 to be multi-valued, for example, binarized,
When the threshold value is larger or smaller than a predetermined threshold value, the defect detection means 44 determines that the defect is present and outputs a defect signal. The result is the defect recording means 46 such as a printer together with the coordinates of the defect.
Will be recorded. This defect signal may be sent to another device and used for another process. Further, a multi-valued image of a certain area including a portion determined to be defective by the defect detecting means 44 may be output to the monitor 36.

FIG. 3 is a block diagram of the second embodiment, and FIG. 4 is a density histogram diagram. The table means 38A of this embodiment is such that the conversion table to be used is automatically set using the density histogram. That is, based on the A / D converted density signal y, the histogram means 50 obtains a density histogram of the density signal y on a certain image area, for example, one scanning line, as shown in FIG. Then, from this histogram, the background density discrimination means 52 sets the density at which the maximum frequency is obtained as the background density c. Also, from this histogram, the second
The set values a and b described in the figure can also be obtained. For example, the setting value a corresponding to the level of noise included in the background and the setting value b corresponding to the density level distribution of defects are obtained from the extent of the density distribution. Maximum frequency n _{0 in} this case
Setting value a, for example, from the frequency n _0/2 to become a concentration range of half
And also it is possible to determine the slope b, for example, from the mean slope or maximum slope between concentrations of a frequency n _0/10 of the n _0/2 and 1/10.

When the set values a, b, and c are thus obtained, the table creating means 54 first finds the pattern of the conversion table by the set values a and b, and then matches the set value c corresponding to the background density level of this pattern. Second table to let
Translate in the left-right direction in the figure. The density converting means 34 uses the conversion table thus determined to input the density signal y
Is converted to obtain the density signal Y and displayed on the television monitor 36. Alternatively, a and b may be set in advance, and a conversion table may be set together with c obtained from the histogram.

The density signal Y is spatially filtered by the differential filter 56 to emphasize the contour of the defect. In this processing, as shown in FIG. 5, for each pixel of the image to be processed, a spatial filter F is superimposed on, for example, a 3x3 area centered on this pixel, the product of corresponding pixels is obtained, and the sum of them is output value. And This operation is performed in the raster scanning order from the upper left pixel to the lower right pixel.

As the spatial filter used for this filtering processing, for example, a filter having a weighting coefficient as shown in FIG. 6 can be adopted. This uses two filters, a filter for row-direction differentiation Δ _x f and a filter for column-direction differentiation Δ _y f, and has the sum of the absolute values of the outputs of both filters or the larger value of the outputs of both filters. This is the final output value.

As a result of such filtering processing, the contours of the image in the x and y directions are emphasized, and the defect detection accuracy in the subsequent multi-value quantization processing 42 is improved. Moreover, since the noise in the background area is erased by the density converting means 34, the noise is not emphasized.

FIG. 7 is a block diagram of the third embodiment. In this embodiment, a table means 38 in which a plurality of density gradation conversion tables of different patterns are stored in a memory (table memory) in advance.
B is provided so that the table to be used can be manually selected by the selection means 40B. That is, the operator is a TV monitor
By looking at the image appearing at 36, the conversion table that makes it easy to see the defects because the noise disappears from the background is found manually.

Further, in this embodiment, the density signal is multivalued through the differential filter 56 and the smoothing means 58. Here, the smoothing means 58 removes the isolated point noise which has not been erased by the density conversion means 34 and which has been differentiated by the differentiation filter 56 and emphasized, thereby further clarifying the distinction between the background and the defect. That is, in this smoothing processing, for example, as shown in FIG. 8, for example, a 3x3 window centering on each pixel is first provided for each pixel, and a density threshold value (for example, 3
128). If the number of pixels exceeding the density threshold value (pixel number threshold value) is a certain number (for example, 4) or more, the value of the pixel to be processed is set to 1, otherwise it is set to 0. By doing so, it is binarized.

The smoothing means of FIG. 8 performs smoothing and binarization at the same time by comparing with a predetermined threshold value.
This may be done separately. For example, the median value of the densities of the pixels in the window shown in FIG. 8 may be used as the density of the pixel to be processed (median filter), or the average value of the densities of the pixels may be used as the density of the target pixel. In this case, it is necessary to further process this by the multi-value quantization means 42.

FIG. 9 is a block diagram of the fourth embodiment. In this embodiment, the conversion table in FIG. 7 is automatically determined. That is, the selecting means 40C obtains at least the set value of the background density c by the background density discriminating means 52 by using the histogram means 50 described with reference to FIGS. The conversion table closest to the obtained setting condition is read from the table means 38C that stores a large number of conversion tables, and the density conversion is performed using this table.

The above examples are those of the flying spot system in which the surface of the inspection object is scanned with laser light, but the inspection object is irradiated with a rod-shaped light source arranged in the width direction, and the reflected light is received by a light receiver via a rotating mirror. It may be a flying image type of reading, a type of reading an image by a line sensor or an area sensor, or the like.

The density conversion table may be stored as a two-dimensional map, but may be stored in the form of a linear or multidimensional equation. It is desirable that the quantization level of the A / D converter, the size and weighting coefficient of the differential filter, the threshold value of the smoothing means, etc. can be freely set according to the inspection target.

In the above embodiment, the detected defect information is recorded in the recording means such as a printer. However, the recording medium such as a floppy disk or a magneto-optical disk, a visual system such as a lamp or a buzzer, a contact signal, a computer or other The defect information may be output to a signal processing device or the like after being converted into an appropriate format and level.

Although each of the above embodiments is described as detecting a defect appearing on the surface of the inspection object, the present invention includes a method of detecting an internal defect by scanning the surface.
For example, an internal defect of a steel plate may be detected using the magneto-optical effect. This is to detect a leakage magnetic field from a defect when a test material is magnetized by an AC magnetic field as a change in polarization of reflected light.

(Effects of the Invention) As described above, the present invention converts the predetermined density range including the background density into the constant density, so that the noise included in the background can be removed without being affected by the noise. Defects can be accurately identified. (Claim (1)).

A plurality of conversion tables used here are stored in advance, and one of them is selected and used according to the inspection target. Therefore, the optimum table for the inspection target can be used for the inspection, and the reliability is improved. The table to be used may be manually selected (Claim (2)), or may be automatically selected using the density histogram (Claim (3)).

Further, by performing spatial filtering processing by a differential filter on the density signal whose density has been converted, it is possible to emphasize the contour of the defect and improve the defect detection accuracy. (Claim (4)). Furthermore, if the density signal after this spatial filtering processing is further smoothed, it is possible to remove the isolated point noise that remains without being removed by the density converting means 34 and is emphasized by the subsequent differential processing, and defect detection The accuracy is further improved (claim (5)). If the density signal converted in density or the multi-valued density signal is displayed on the monitor, it is convenient to view the defect image at the same time (claims (6) and (7)).

[Brief description of the drawings]

FIG. 1 is a block diagram showing the configuration of an embodiment of the present invention, and FIG. 2 is a diagram showing an embodiment of a density gradation conversion table and input / output density signals. FIG. 3 is a block diagram of the second embodiment, and FIG. 4 is a density histogram diagram. FIG. 5 is an explanatory diagram of the spatial filtering process, FIG. 6 is a diagram showing an example of the differential filter, FIG. 7 is a block diagram of the third embodiment, FIG. 8 is an explanatory diagram of the smoothing process, and FIG. It is a block diagram of a 4th example. 10 ... Inspected object, 34 ... Density conversion means, 36 ... Monitor, 38, 38
A to C ... Table means, 40 ... Setting means, 40B, 40C ... Selection means, 42 ... Multi-value conversion means, 44 ... Defect detection means, 56 ... Spatial filtering means, 58 ... Smoothing means.

Claims (7)

(57) [Claims] 1. A defect inspection apparatus for detecting a defect of an inspection object using a density signal obtained by digitizing an image signal obtained by scanning an inspection object, wherein a predetermined density range including at least background density is converted into a constant density. Table means for selecting and outputting one of a plurality of density gradation conversion tables, density converting means for density converting the density signal using the density gradation conversion table, and density after the density conversion. Defect inspection characterized by comprising multi-value converting means for converting the signal into multi-value and defect detecting means for detecting an image portion in which the multi-valued density signal exceeds a predetermined density level as a defect and outputting a defect signal. apparatus. 2. The defect inspection apparatus according to claim 1, wherein the table means manually selects the density gradation conversion table. 3. The defect inspection apparatus according to claim 1, wherein the table means selects one of the density gradation conversion tables by using a density histogram of a density signal for a predetermined image area. 4. The defect inspection apparatus according to any one of claims (1) to (3), further comprising: spatial filtering means for performing spatial filtering processing by a differential filter on the density signal density-converted by the density converting means. A defect inspection apparatus that multi-values by using the processed density signal. 5. The defect inspection apparatus according to claim 4, further comprising a smoothing unit that further smoothes the density signal after the spatial filtering process, and multi-values using the smoothed density signal. 6. The defect inspection apparatus according to claim 1, further comprising a monitor for displaying a density signal whose density has been converted by the density conversion means so that a defect image can be visually observed. 7. The defect according to any one of claims 1 to 5, further comprising a monitor for displaying a density signal obtained by converting the density signal converted by the density converting means into a multi-valued image, so that an image of the defect can be visually observed. Inspection device.