JP2006208187A - Shape pass / fail judgment device and shape pass / fail judgment method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a shape pass / fail judgment device and a shape pass / fail judgment method capable of accurately judging pass / fail.
In The present invention, by using an approximate expression F represented by formula (1), the brightness value B _a, by calculating the tilt angle theta _{a, b} from _b, the inclination angle of the test object theta _{a , b} can be estimated accurately. Tilt angle theta _{a, b} are to be calculated pixel P _a, each _b, it is possible to estimate the pixel P _a, and the arrangement of the _b, and the shape of the inspection object from an inclination angle θ _{a, b.} Then, by determining whether the estimated shape is a shape similar to a non-defective product / defective product, the quality of the inspection object can be determined.
[Selection] Figure 7

Description

  The present invention relates to a shape pass / fail determination device and a shape pass / fail determination method for determining pass / fail of a shape to be examined.

2. Description of the Related Art Conventionally, it is known to detect a light / dark change point from image data obtained by picking up an image of solder with an image pickup camera, and to determine the quality of the solder shape from the detection result of the light / dark change point (see, for example, Patent Document 1). ).
According to such a configuration, since the solder shape can be estimated based on the position and shape of the light and dark change points obtained from the imaging data, it was possible to determine whether the solder shape was good or bad.
JP-A-8-15171

However, according to the light-dark change point, only the shape of a predetermined ridge line in which the light-dark change can occur in the solder shape can be specified, and the quality determination cannot be performed with accuracy based on the continuous shape of the entire solder. There was a problem.
The present invention has been made in view of the above problems, and an object of the present invention is to provide a shape quality determination device and a shape quality determination method that can perform quality determination with high accuracy.

  In order to achieve the above object, according to the first aspect of the present invention, an irradiating means for irradiating the inspection object with inspection light at a predetermined incident angle and a reflected image of the inspection light with respect to the inspection object are captured. Thus, for each pixel from the correspondence relationship between the imaging means for obtaining the captured image expressed by the luminance value of the reflected light for each pixel, and the inclination angle of the inspection object from which the reflected light is reflected Inclination angle acquisition means for acquiring the same inclination angle, shape estimation for estimating the shape of the inspection object based on the inclination angle of each pixel acquired by the inclination angle acquisition means and arrangement information of the same pixel And a pass / fail determination unit that performs pass / fail determination based on the shape estimated by the shape estimation unit.

  In the invention of claim 1 configured as described above, the irradiating means irradiates the inspection object with the inspection light at a predetermined incident angle. The imaging means captures a reflection image of the inspection light with respect to the inspection object, and acquires an imaging image expressed by a luminance value of the reflected light for each pixel. The inclination angle acquisition means is provided with a correspondence relationship between the luminance value and the inclination angle of the inspection object on which the reflected light is reflected in advance, and the luminance value of the captured image is obtained using this correspondence relationship. To obtain the tilt angle for each pixel. The shape estimation means estimates the shape of the inspection object based on the inclination angle and arrangement information of each pixel. Further, the pass / fail determination means performs pass / fail determination based on the shape estimated by the shape estimation means. Since the tilt angle is acquired for each pixel, the shape of the inspection object can be acquired based on the arrangement information of the pixels. Therefore, it is possible to estimate the shape of the inspection object included in the imaging area imaged by the imaging means.

Furthermore, the invention according to claim 2 is configured such that the correspondence relationship is defined by an approximate expression in which at least specular reflection and diffuse reflection when the inspection light is reflected by the inspection object are taken into account.
In the invention of claim 2 configured as described above, the brightness value and the inclination angle are approximated by an approximate expression in which specular reflection and diffuse reflection when at least the inspection light is reflected by the inspection object are added. The above correspondence is defined. The correspondence relationship may be that in which the correspondence between the luminance value and the tilt angle is defined by a table, or may be the approximate expression itself. In any case, the inclination angle acquisition means can acquire the inclination angle based on the luminance value.

The invention according to claim 3 is configured such that at least the incident angle, the amount of the inspection light, and the physical property value of the inspection object are given as constants in the approximate expression.
In the invention of claim 3 configured as described above, the luminance value and the inclination angle are calculated by calculating the approximate expression in consideration of the incident angle, the amount of the inspection light, and the physical property value of the inspection object. Can be accurately defined.

Further, in the invention according to claim 4, the irradiating means irradiates the inspection object with inspection light at a plurality of incident angles, and the inclination angle acquiring means applies to the plurality of incident angles. The tilt angle is obtained for each pixel based on the plurality of corresponding relationships defined respectively.
In the invention of claim 4 configured as described above, the irradiation unit irradiates the inspection object with inspection light at a plurality of incident angles. The above correspondence is defined for each incident angle. And the said inclination-angle acquisition means acquires the said inclination-angle from the said luminance value for every said pixel based on the said some correspondence. That is, even when the inclination angle cannot be specified from the luminance value only by the correspondence relation at a certain incident angle, the inclination angle can be obtained from the luminance value based on the correspondence relation at another incident angle. it can.

According to a fifth aspect of the present invention, the inclination angle acquisition means is configured to obtain a difference between the other luminance value and the inclination angle based on a correspondence relationship between the representative representative luminance value and the inclination angle. The correspondence relationship is estimated.
In the invention of claim 5 configured as described above, the correspondence between the representative luminance value and the inclination angle is defined in advance. Then, other correspondence relationships between the luminance value and the tilt angle are acquired by estimation based on the correspondence relationship between the representative luminance value and the tilt angle. For example, by using linear interpolation or the like, it is possible to easily estimate the correspondence between the other luminance values and the tilt angle. Thereby, it is not necessary to investigate and define all the correspondence relationships in advance.

According to a sixth aspect of the present invention, the inclination angle acquisition means includes the other luminance values based on fuzzy inference using a membership function for the luminance value and a membership function for the inclination angle. The correspondence relationship with the inclination angle is estimated.
In the invention of claim 6 configured as described above, fuzzy inference is performed using a membership function for the luminance value and a membership function for the tilt angle. Thereby, it is possible to estimate the correspondence relationship between the other luminance values and the inclination angle based on fuzzy inference.

The invention according to claim 7 is configured such that the pass / fail judgment means calculates a γ function that approximates the shape estimated by the shape estimation means, and judges pass / fail based on the γ value of the γ function. It is as.
In the invention of claim 7 configured as described above, the quality determination unit calculates a γ function that approximates the shape estimated by the shape estimation unit. Then, pass / fail judgment is performed by evaluating the γ value of the calculated γ function. Since the degree of unevenness of the shape can be determined according to the γ value, a suitable index for evaluating the shape can be obtained.

  The above-described method can also be applied as a method for realizing such an apparatus, and the invention according to claim 8 basically has the same effect. Of course, it is also possible to make the structure described in claims 2 to 7 correspond to the method of claim 8.

As described above, according to the first and eighth aspects of the invention, it is possible to provide a shape pass / fail determination apparatus and a shape pass / fail determination method capable of accurately determining pass / fail.
According to the invention of claim 2, it is possible to accurately estimate the luminance value of the reflected light.
According to the invention of claim 3, it is possible to calculate an approximate expression suitable for each condition.
According to the invention of claim 4, it is possible to reliably specify the inclination angle from the luminance value.
According to the fifth aspect of the present invention, it is not necessary to investigate in advance the correspondence relationship for all luminance values.
According to the invention of claim 6, it is possible to estimate the correspondence based on fuzzy inference.
According to the seventh aspect of the invention, the degree of unevenness of the shape can be determined.

Here, embodiments of the present invention will be described in the following order.
(1) Configuration of shape pass / fail judgment device:
(2) Pass / fail judgment processing:
(3) About the approximate expression:
(4) Modification:
(5) Modification using fuzzy inference:
(6) Summary:

(1) Configuration of shape pass / fail judgment device:
FIG. 1 shows the configuration of a shape pass / fail judgment apparatus according to the present invention. In the figure, the shape pass / fail judgment apparatus 10 is composed of an imaging unit 20 and a computer 30 which are connected to each other. The imaging unit 20 images the mounting board 50 of the inspection object to generate a captured image, and outputs the captured image to the computer 30. The computer 30 inputs the captured image and analyzes the captured image to determine whether the mounted substrate 50 that has captured the image is acceptable. In FIG. 1, the imaging unit 20 includes an XY stage 23 on which a mounting board 50 is placed at a fixed position and movable in the XY (horizontal) direction based on a command from the controller 21. The camera 22 has an optical system 22a composed of a predetermined optical lens oriented vertically downward so that an image vertically below can be input. A CCD image pickup plate 22b is provided inside the camera 22, and the optical system 22a can form an image vertically below the CCD image pickup plate 22b.

  The CCD imaging plate 22b is composed of a plurality of CCD imaging elements arranged in a dot matrix. The CCD image sensor is a photoelectric element that generates a charge according to each input light, and temporarily stores the generated charge. The electric charges generated by the CCD image pickup device are sequentially transferred to the controller 21 while being converted into digital signals. The controller 21 stores the transferred digital signal in an image memory (VRAM) 21a while associating it with each address of the CCD image pickup device on the CCD image pickup plate 22b. That is, image data having the gradation of the digital signal is generated for each pixel corresponding to the CCD image sensor in the VRAM 21a. In the present embodiment, the digital signal represents the luminance of light input to the CCD image sensor. That is, image data having a luminance value for each pixel is stored in the VRAM 21a.

  The image data stored in the VRAM 21a as described above is output to the computer 30. Further, new image data is stored in the VRAM 21a every time the camera 22 performs imaging. The controller 21 outputs a drive signal to the XY stage 23, and the XY stage 23 is driven in the horizontal direction according to the drive signal. Of course, the mounting board 50 placed at a fixed position on the XY stage 23 also moves horizontally. In this way, the field of view of the camera 22 can be moved to any position on the mounting board 50 without moving the camera 22. Note that when the camera 22 captures an image, the XY stage 23 is stopped, so that a still image is captured.

  A ring light 24a is held above the XY stage 23 by a predetermined amount. The ring light 24 includes an LED as a light emitting element. The LED is formed in an annular shape, and the center position thereof is matched with the center position of the optical system 22a of the camera 22 when viewed from above. That is, the ring light 24 can irradiate the visual field of the camera 22 from the outside at a certain angle. Since the field of view of the camera 22 is sufficiently smaller than the size of the ring light 24 and the distance to the mounting substrate 50, it is assumed that errors in the incident angle and light quantity of the inspection light within the field of view can be ignored. By doing so, it is possible to generate two-dimensional image data obtained by capturing the reflection image of the mounting board 50 by the ring light 24 with the camera 22. The image data captured by the camera 22 is referred to as a captured image.

  FIG. 2 is a block diagram showing the internal configuration of the computer 30. In FIG. 1, a computer 30 includes a CPU 31, a RAM 32, a video memory (VRAM) 33, and a hard disk (HDD) 34 as main components. The CPU 31 is an arithmetic unit that executes processing based on an operating system (O / S) 34a, a pass / fail determination program 34b, and the like stored in the HDD 34, and uses the RAM 32 as a work area when executing the processing. The VRAM 33 is a memory specialized for storing image data, and stores a captured image 33a and an angle image 33b. The captured image 33a is image data transferred from the VRAM 21a of the controller 21.

  As another configuration, the computer 30 includes a video interface (I / F) 35, an input interface (I / F) 37, and an I / O 39. A display 36 is connected to the video I / F 35, a keyboard 38 a and a mouse 38 b are connected to the input I / F 37, and the controller 21 of the imaging unit 20 is connected to the I / O 39. The I / O 39 outputs a signal for driving the XY stage 23 to the controller 21, a signal for executing imaging by the camera 22, and the like, and receives an input of a captured image from the controller 21. Yes.

  FIG. 3 shows the configuration of software implemented by the computer 30 and the data flow. In the CPU 31 and the RAM 32, an O / S 34a and a pass / fail determination program 34b are executed, and its module configuration is shown. The pass / fail determination program M includes an imaging execution unit M1, a captured image acquisition unit M2, an inclination angle acquisition unit M3, a shape estimation unit M4, and a pass / fail determination unit M5.

  The imaging execution unit M1 acquires the board data 34c stored in the HDD 34, and causes the imaging unit 20 to execute imaging based on the board data 34c. Specifically, the board data 34c stores information such as the size of the mounting board 50 and the position, size, shape, and number of mounted components, and the XY stage 23 is driven based on these information. . Therefore, the visual field of the camera 22 can be moved to a desired position on the mounting board 50, and pass / fail judgment can be performed on the desired position on the mounting board 50.

  The captured image acquisition unit M <b> 2 receives the captured image from the controller 21 and stores the captured image 33 a in the VRAM 33. The tilt angle acquisition unit M3 calculates the tilt angle for each pixel by substituting the luminance value of each pixel in the captured image 33a into the approximate expression F stored in the HDD 34. As a result, an angle image 33 b is generated as new image data in which each pixel is expressed by an inclination angle, and the same angle image 33 b is stored in the VRAM 33.

  In the present embodiment, only the shape of the solder on the mounting substrate 50 is judged as good or bad, so that the inclination angle acquisition unit M3 calculates the inclination angle only for the pixel region corresponding to the solder portion in the captured image 33a. . Position information indicating where the solder portion is arranged in the field of view of the camera 22 can be acquired from the board data 34c. When a plurality of solder portions are included in a single captured image 33a, an angle image 33b is calculated for each.

  The shape estimation unit M4 receives the angle image 33b from the VRAM 33, generates shape data 34d based on the angle image 33b, and stores it in the HDD 34. Since each pixel has an inclination angle in the angle image 33b, the shape of the solder can be estimated based on the arrangement information of each pixel and the inclination angle. The pass / fail judgment unit M5 acquires the shape data 34d and makes a pass / fail judgment based on the shape data 34d. The result of pass / fail judgment may be output to an output device such as the display 36 or a printer, or may be stored in the HDD 34. In the present embodiment, all processes are performed by a single computer 30. However, a plurality of computers may be communicably connected, and the processes may be distributed among the computers.

(2) Pass / fail judgment processing:
FIG. 4 shows the flow of the pass / fail judgment process. In the figure, the camera 22 takes an image in step S100. In step S110, a captured image 33a is generated, and the captured image acquisition unit M2 stores the captured image 33a in the VRAM 33. FIG. 5 shows the field of view S of the camera 22. In the figure, the visual field S imaged by the camera 22 includes a plurality of mounting components and solder on the mounting substrate 50. However, in this embodiment, the quality determination about the shape of the solder 52 of the chip component 51 indicated by a solid line will be described. In step S110, a captured image 33a is generated as image data representing the entire visual field S. In the captured image 33a, each pixel has a luminance value.

  In step S120, only pixel data including the solder 52 is extracted from the captured image 33a. That is, only the pixel data inside the evaluation region T in which the periphery of the solder 52 is surrounded by a solid line in FIG. 5 is extracted. In step S <b> 120, the CPU 31 specifies where in the field of view S the solder 52 subject to pass / fail determination is arranged based on the board data 34 c stored in the HDD 34. Then, an evaluation area T having an appropriate shape is set, and pixel data belonging to the evaluation area T is extracted.

FIG. 6 schematically shows the state of the evaluation region T. In the figure, the evaluation area T is composed of _a large number of pixels Pa _{, b} divided by broken lines. In the figure, for the sake of simplification, the pixel Pa _{, b} is shown large, but actually, the pixel Pa _{, b} is very small. The pixels Pa _{, b} correspond to the CCD image pickup devices on the CCD image pickup plate 22b. Depending on the dot matrix arrangement of the CCD image pickup devices on the CCD image pickup plate 22b, each CCD is connected via the optical system 22a. The position on the mounting substrate 50 where the image is input to the image sensor is different. Further, the luminance value B _{a, b} of each pixel Pa _{, b} means the average luminance of the area where each CCD image sensor on the mounting substrate 50 is in charge of image input. The arrangement of each CCD image sensor is not limited to a dot matrix.

In step S130, the inclination angle acquisition unit M3 generates an angle image 33b from pixel data inside the evaluation region T in the captured image 33a. Specifically, each pixel P _a, the luminance value B _a of _b, and _b are substituted into the following equation (1), by solving for the inclination angle theta, the tilt angle theta _{a, b} for each pixel P _{a, b} Is calculated.
B _{a, b} = k · {l _i · (1−c) · sin ^m (γ + 2θ _{a, b} )
+ L _i · c · sin (γ + θ _{a, b} )} (1)

The parameters k, l _i , c, m, and γ in the above formula (1) are condition values at the time of imaging and physical property values of the solder 52, and details will be described later. The parameters k, l _i , c, m, and γ in the above formula (1) are constants, and appropriate values are set in advance. Also, the above equation (1) is stored in the HDD 34 as the approximate equation F, and is read out and used as appropriate by the CPU 31.

In the angle image 33b in which the luminance value B _{a, b} is converted into the corresponding inclination angle θ _{a, b} as described above, each pixel Pa _{, b in} FIG. 6 is not the luminance value B _{a, b} but the position. The inclination angle θ _{a, b according} to The lower part of FIG. 6 schematically shows a converted angle image 33b having an inclination angle θ _{a, b} for each pixel Pa _{, b} . Note that the inclination angle θ _{a, b} is calculated based on the luminance value B _{a, b} which means average luminance, and thus means an average inclination angle for the pixel Pa _{, b} .

In step S140, the shape estimation unit M4 generates shape data 34d based on the angle image 33b. Here, a case where the shape data 34d is created for the center of the solder 52 indicated by the straight line D in FIG. 6 will be described. FIG. 7 shows how the shape of the solder 52 is specified based on the angle image 33b. In the drawing, based on the arrangement of the pixels Pa _{, b} on the straight line D, the central cross-sectional shape of the solder 52 is reproduced from the continuity of the solder curved surface.

  In addition, the width of the area where each CCD image sensor on the mounting substrate 50 is in charge of image input is expressed as a width W. The width W can be specified by the arrangement pitch of the CCD image pickup devices and the set magnification of the optical system 22a.

For each pixel Pa _{, b} , the height _{ha, b} is calculated by the following equation (2).
h _{a, b} = W × tan θ _{a, b} (2)
Each pixel P _a, the height h _a of _b, the pixel _b P _a, by adding to the arrangement order of _b, the pixel P _a, it is possible to specify the height of the boundary _b. As a result, it is possible to generate the shape data 34d in which the central cross-sectional shape of the solder 52 is expressed by the height of the boundary between the pixels Pa _{, b} .

  In step S150, the quality determination unit M5 determines whether the shape data 34d indicates the shape of a non-defective product. In FIG. 8, a normal solder shape, a solder large, a solder wettability defect, and a solder small solder shape are compared. In the figure, it can be seen that the height of the solder monotonously increases in normal solder. On the other hand, in a solder shape having a large solder and poor solder wettability, there is an apex of the solder, and the inclination of the solder surface is 0 at the apex. Accordingly, when the shape data 34d is generated for these defects, a curved shape as shown in the right column is obtained. That is, it can be seen that a point at which the inclination is 0 at a predetermined position is detected and does not increase monotonously. As described above, whether or not the shape data 34d has a monotonous increase tendency can be determined in step S150.

  In the above, only an example of pass / fail determination is shown, and other pass / fail criteria can be applied. For example, a γ function may be fitted to the shape data 34d, and the pass / fail judgment may be performed based on the magnitude of the γ value. As shown in FIG. 8, the γ value is close to 1 for a non-defective product. On the other hand, when the amount of solder is small, the γ value decreases, and when the amount of solder is large, the γ value increases. Therefore, when the γ value is close to 1, it is determined that the solder shape is normal. Can do. Therefore, although the solder small defect shown in FIG. 8 is monotonously increasing, the solder has a feature of a concave shape, and therefore can be determined by a small γ value. Further, a function approximating the shape data 34d may be calculated, and the coefficient or the like may be used as a criterion for pass / fail judgment. In any case, the captured image 33a can acquire the continuous shape of the surface of the solder 52, and can perform pass / fail determination with high accuracy.

In the present embodiment, the shape data 34d along the straight line D is generated from the angle image 33b. However, the shape data 34d in another direction may be generated. Of course, a plane satisfying the inclination angle θ _{a, b} is formed for the pixels Pa, _{b at} each position, and a shape in which these planes are continuously connected in the vertical (b) direction and the horizontal direction (a) is estimated. Thus, the shape data 34d may be generated. According to this method, the shape data 34d that can represent a three-dimensional shape can be generated. By doing in this way, since the shape of the whole solder 52 can be specified, it becomes possible to perform quality determination with higher accuracy. If the shape data 34d for one direction is generated, the calculation load on the CPU 31 can be reduced, and the CCD imaging plate 22b can be replaced with a one-dimensional line sensor.

(3) About the approximate expression:
Next, the approximate expression F will be described. The approximate expression F is a function that can calculate the tilt angle of each pixel from the luminance value of each pixel, and is stored in the HDD 34 in advance. FIG. 9 schematically shows a state in which the inspection light is irradiated from the ring light 24 onto the visual field S of the camera 22. In the drawing, the diameter r of the ring light 24 and the distance d between the ring light 24 and the mounting substrate 50 are shown. From the relationship shown in the figure, the incident angle γ can be expressed as the following formula (3) by the diameter r and the distance d.
γ = arctan (d / r) (3)

  The field of view S is 2 cm × 2 cm, which is sufficiently smaller than the diameter r and the distance d, so that the incident angle γ can be considered to be uniform in the field of view S. Further, although the solder protrudes upward in the field of view S, the height of the solder is also sufficiently smaller than the diameter r and the distance d, so that the incident angle γ does not depend on the height of the solder. Can be thought of as

FIG. 10 virtually shows a state in which the inspection light emitted from the ring light 24 enters the solder. In the figure, the CCD image pickup device of the CCD image pickup plate 22b picks up the reflected image of the inspection light with respect to the solder 52 from above. The inspection light C _i collides with the surface of the solder 52 and is reflected on the surface. At this time, specular reflection light C _s radiated only in a direction symmetrical to the incident light C _i and diffuse reflection light C _d radiated uniformly in all directions are generated. The direction of the specular reflected light C _s is deviated from the vertical direction that the CCD imaging plate 22b waits at an angle β, and a cosine component C _s ′ having the same angle β reaches the CCD imaging plate 22b. The amount of light l _s ′ of the cosine component C _s ′ reaching the CCD image pickup plate 22b can be expressed by the following equation (4).
l _s ′ = l _i · (1−c) · cos ^m β (4)

In the above formula (4), l _i represents the amount of inspection light, c (0 to 1) represents the roughness of the solder surface, and m represents the degree of localization of the specular reflection. The degree of localization m is a coefficient representing the clarity of the specular reflection contour, and depends on the surface state of the solder. For example, in the case of eutectic solder, the contour of specular reflection is clear, and it can be said that the degree of localization m is high. On the other hand, in the case of lead-free solder, it can be said that the degree of localization m is low because the contour of specular reflection is blurred. In the above formula (4), 'quantity l _s of' cosine component C _s is proportional to a power of the cosine of the specular reflection light C _s and cosine component C _s' and the angle beta. Further, regarding the angle β, the following relationships (5) and (6) are established geometrically.
α = π / 2−γ−θ _{a, b} (5)
β = θ _{a, b} −α = −π / 2 + γ + 2θ _{a, b} (6)
In the above formulas (5) and (6), α represents an angle formed by the normal of the solder surface and the inspection light C _i . By substituting the above equation (4) into the above equation (2), the following equation (7) can be obtained.
l _s ′ = l _i · (1−c) · cos ^m (−π / 2 + γ + 2θ _{a, b} ) (7)
As described above, the light quantity l _s ′ of the cosine component C _s ′ of the specular reflection light is calculated from the light quantity l _{i of the} incident light, the roughness c of the solder surface, the localization degree m of the specular reflection, the incident angle γ, and the inclination angle θ. can do.

On the other hand, the light quantity l _d of the diffuse reflected light C _d can be expressed as the following formula (8).
l _d = l _i · c · cos α (8)
That is, the light quantity l _d of the diffuse reflected light C _d is proportional to the cosine of the angle α formed by the normal of the solder surface and the incident light C _i . Further, the diffuse reflected light C _d is reflected light generated by the irregular reflection of the incident light C _{i on} the surface of the solder 52, and can be considered to be reflected with a uniform light amount in all directions. Accordingly, the light amount l _d ′ of the light ray C _d ′ incident on the CCD image sensor is the same as the light amount l _d . Furthermore, the following formula (9) can be obtained by substituting the above formula (5) into the above formula (8).
l _d = l _i · c · cos (π / 2−γ−θ _{a, b} ) (9)

In the above equation (9), the amount of light l _d ′ of the light ray C _d ′ reaching the CCD image sensor derived from diffuse reflection is also equal to the amount of incident light l _i , the roughness c of the solder surface, the incident angle γ, and the average tilt angle. It can be calculated from θ. Further, the total amount of light reaching l _o reaching the CCD image sensor is calculated by superimposing the amount of light l _s ′ derived from specular reflection and the amount of light l _d ′ derived from diffuse reflection by the following equation (10). can do.
l _o = l _s '+ l _d ' (10)

Furthermore, the above formula (1) can be obtained by substituting the above formula (7) and the above formula (9) into the above formula (10), and further multiplying by a constant k that converts the light amount into luminance. . In the above formula (1), the first term is a specular reflection term, and the second term is a diffuse reflection term. According to the above equation (1), the correspondence relationship between the amount of light reaching l _o reaching the CCD image sensor and the inclination angle θ can be expressed by an approximate equation having predetermined parameters l _i , c, m, and γ as constants. . The above equation (1) is stored in the HDD 34 as the approximate equation F. Since the luminance value B _{a, b} and the light quantity l _o are in a proportional relationship, the luminance value B _{a, b} can be obtained by multiplying by a constant k. Further, it is possible to align the luminance value B _a, the range of _b brightness values B _a in the imaging image _33a, a gradation width _b by the constant k.

The parameters k, l _i , c, m, and γ used in the above equation (1) are numerical values that can be obtained from imaging conditions, physical property values, etc., but the optimum parameters k, l _i , c, You may calculate m and (gamma) by experiment. For example, a plurality of samples are prepared in advance, and the shape of the solder 52 is measured using an X-ray shape measuring device or the like, and an actually measured inclination angle θ _{a, b} is calculated for each pixel Pa _{, b.} Keep it. Then, these samples are imaged by the camera 22, and the brightness value B _{a, b} is obtained for each pixel Pa _{, b} . Further, the correspondence relationship between the inclination angle θ _{a, b} and the luminance value B _{a, b} is investigated for each pixel Pa _{, b} .

FIG. 11 is a graph plotting the correspondence between the inclination angle θ _{a, b} and the luminance value B _{a, b} . In the figure, the horizontal axis indicates the inclination angle θ _{a, b} and the vertical axis indicates the luminance value B _{a, b} . As described above, there is some correlation between the inclination angle θ _{a, b} and the luminance value B _{a, b,} and this correlation conforms to the approximate expression F in the above formula (1) based on the light reflection characteristics. it is conceivable that. Therefore, various curve shapes satisfying the approximate expression F are created by changing the values of the parameters c and m for determining the curve shape represented by the approximate expression F into a brute force expression.

Then, the values of the parameters c and m are calculated such that the curve shape has the highest correlation coefficient between the inclination angle θ _{a, b} and the distribution tendency of the luminance values B _{a, b} shown in FIG. Next, the values of the parameters l and k that define the range of the luminance value B _{a, b} of the approximate expression F are changed to a round-robin expression, and the inclination angle θ _{a, b} and the distribution tendency of the luminance value B _{a, b} are changed. The parameters l and k that minimize the error are specified. That is, by optimizing (l _i × k), it is possible to set an appropriate similarity factor for the curve shape of the approximate expression F. For the incident angle γ, the value calculated by the above equation (3) is applied. Thus, by determining the parameters k, l _i , c, m based on the actually measured inclination angles θ _{a, b} , it is possible to calculate the approximate expression F with higher reliability.

(4) Modification:
By the way, depending on the values of the parameters c and m, the curve drawn by the approximate expression F may have a shape as shown in FIG. In this case, the inclination angle θ _{a, b} cannot be calculated uniquely in step S130. That is, a single luminance value B _a, for the inclination angle theta _{a, b} that satisfies _b there are a plurality of the pixel _a, be uniquely calculate the average tilt angle theta _{a, b and b} There is a problem that you can not. This modification is made to solve such a problem.

13 and 14 show configurations of the imaging unit 20 and the computer 30 according to this modification. In the figure, an upper ring light 24a and a lower ring light 24b are provided at different heights. The upper ring light 24a is formed with a smaller diameter than the lower ring light 24b, and the inspection light emitted from the upper ring light 24a can reach the visual field S without being obstructed by the lower ring light 24b. Thus, by providing the ring lights 24a and 24b at different positions, it is possible to image the solder 52 at the incident angles γ ₁ and γ _{2 of} the two types of inspection light corresponding to the ring lights 24a and 24b.

In this modified example, in step S100 shown in FIG. 4, imaging is performed once according to the incident angles γ ₁ and γ _{2 of} the inspection light. Then, in step S120 the incident angle gamma _1, 2 pieces of imaging the image 33b corresponding to gamma _{2 1,} 33b ₂ are generated. In step S130, the approximate expression F is used to generate the angle image 33b. However, since the approximate expression F has the incident angle γ as a parameter, different approximate expressions F ₁ and F ₂ are calculated according to the incident angles γ ₁ and γ ₂ . The parameters k, l _i , c, and m of the approximate expressions F ₁ and F ₂ are preferably the same value, but may be different values when optimized by the above-described experiment. In any case, the incident angle gamma ₁ in the approximation formula F _1, F _2, since the gamma ₂ becomes different value, the curve drawn by both are different shapes.

FIG. 15 is a graph showing the approximate expressions F ₁ and F ₂ . In the figure, the horizontal axis indicates the inclination angle θ _{a, b} and the vertical axis indicates the luminance value B _{a, b} . Here, for a certain pixel P _{a, b} , when the luminance value B _{a, b} = 128 in the captured image 33b ₁ captured at the incident angle γ ₁ , two solutions are obtained by solving the approximate expression F _1. θ _1a and θ _1b are obtained. For the same pixel P _{a, b} , when the luminance value B _{a, b} = 64 in the captured image 33b ₂ captured at the incident angle γ ₂ , two solutions θ are obtained by solving the approximate expression F _{2. 2a} and θ _2b are obtained.

That is, a total of four inclination angles θ _1a , θ _1b , θ _2a , and θ _2b are obtained. In step S130, the pixel P _a, the inclination angle theta _{a, b} of _b is calculated based on these. For example, an average value of two inclination angles θ _1b and θ _{2a that} are closest to the inclination angles θ _1a , θ _1b , θ _2a , and θ _2b may be calculated as the inclination angle θ _{a, b} . Thus, the accuracy of the inclination angle θ _{a, b} is improved by specifying the inclination angle θ _{a, b} comprehensively from the plurality of captured images 33b ₁ , 33b ₂ and the approximate expressions F ₁ , F _2. Can do. Subsequent processing can be similarly performed.

  In the above, the example in which the inclination angle θ is estimated using the two ring lights 24a and 24b is exemplified, but more than two ring lights may be used. By providing a large number of ring lights each having a different incident angle γ and acquiring the correspondence between the inclination angle θ and the luminance value B for each of them, it is possible to estimate the appropriate inclination angle θ comprehensively from the many correspondences. It becomes possible. That is, more accurate shape estimation can be performed by increasing the number of ring lights installed.

  In the embodiment described above, the example in which the inclination angle is specified by substituting the luminance value into the approximate expression and solving the approximate expression is exemplified, but the inclination angle may be specified by other methods. For example, the correspondence relationship between the luminance value and the tilt angle may be investigated in advance by experiments or the like, and the correspondence relationship may be stored in a table. Then, by referring to this table, the tilt angle can be specified from the luminance value. According to such a configuration, it is not necessary to perform the calculation for solving the approximate expression for each pixel, so that the processing efficiency can be improved.

Furthermore, in order to reduce the data amount of the table defining the correspondence between the luminance value and the inclination angle, only the correspondence between the representative luminance value and the inclination angle may be stored in the table. In this case, the correspondence between the other luminance values and the tilt angle is not defined, but the correspondence between the other luminance values and the tilt angle can be obtained by using linear interpolation, spline interpolation, or the like. . For example, it is assumed that a table as shown in FIG. 16 is stored. The table E1 describes representative luminance value B values ₀ , 16, 32,... That divide 256 gradations into 16 equal parts, and the tilt angle θ ₀ , corresponding to the representative luminance value B is described. θ ₁₆ , θ ₃₂ ... are also defined.

Since the inclination angle θ ₁₆ corresponding to the luminance value B = 16 is defined in the table E1, the inclination angle θ ₁₆ can be obtained by referring to the table E1. On the contrary,
For example, since the tilt angle θ ₂₀ corresponding to the luminance value B = 20 is not defined in the table E1, the tilt angle θ ₂₀ cannot be obtained directly. However, the inclination angle θ ₂₀ can be estimated by performing linear interpolation as shown in FIG. In the figure, the inclination angle θ ₂₀ is calculated by dividing the representative inclination angles θ ₁₆ and θ ₃₂ adjacent to the inclination angle θ ₂₀ according to the deviation of the luminance value B. Thus, by calculating the tilt angle θ using interpolation, the data in the table E1 can be reduced without complicating the arithmetic processing.

(5) Modification using fuzzy inference:
Furthermore, the correspondence between the luminance value B and the inclination angle θ may be estimated by fuzzy inference. Hereinafter, the procedure will be described. FIG. 18 shows a flow of processing for calculating the inclination angle θ by fuzzy inference. Note that the processing shown in the figure is executed in place of step S130 in FIG. Also, the hardware has the same configuration as that shown in FIG. 13, and the imaging of the solder 52 is performed at the incident angles γ ₁ and γ _{2 of} the two types of inspection light corresponding to the ring lights 24a and 24b. To do. On the other hand, the software configuration shown in FIG. 19 is applied.

In step S120 of FIG. 4, two captured images 33a1 and 33a2 corresponding to the incident angles γ ₁ and γ ₂ are acquired, and pixel data to be determined is extracted from these. In step S130a, the pixel P is selected. That is, steps S130b to S130e are processing for one pixel P. By repeatedly executing steps S130b to S130e for each pixel P, the inclination angle θ is specified for all the pixels P, and the angle image 33b is generated. It is possible. Note that the inclination angle θ may be calculated for each pixel P, or the inclination angle θ may be calculated for each pixel block such as a pixel column or a pixel row.

In step S130b, the upper luminance value B _γ1 and the lower luminance value B _γ2 for the pixel P selected in step S130a are acquired from the captured images 33a1 and 33a2. Incidentally, the upper luminance value B _.gamma.1 is a luminance value obtained from the imaging image 33a1 taken at an incident angle gamma _1, the lower luminance value B _.gamma.2 is acquired from the imaging image 33a2 taken at an incident angle gamma ₂ Mean the luminance value. In step S130c, the first membership function X1 stored in advance in the HDD 34 is acquired, and the suitability of the upper luminance value B _γ1 and the lower luminance value B _γ2 with respect to the first membership function X1 is evaluated.

FIG. 20 is a graph showing the first membership function X1. In the figure, the horizontal axis indicates the upper luminance value B _γ1 and the lower luminance value B _γ2 , and the vertical axis indicates compatibility. The adaptability varies between 0 and 1, and the greater the value, the higher the adaptability. The first membership function X1 is composed of three functions, and shows a trajectory of suitability for the low group G1, the medium group G2, and the high group G3, respectively. This function may be composed of a normal distribution function or a trigonometric function, or may be composed of a linear function or a higher-order function. For example, when the vertical luminance values B _γ1 and B _γ2 are 64 or less, the suitability of the low group G1 is 1, and the suitability of the medium group G2 and the high group G3 is 0. When the upper and lower luminance values B _γ1 and B _γ2 are 128, the suitability of the middle group G2 is 1, and the suitability of the low group G1 and the high group G3 is 0.

The subsequent processing will be described assuming that the upper luminance value B _γ1 imaged at the incident angle γ ₁ is 200 and the lower luminance value B _γ2 imaged at the incident angle γ ₂ is 100. Since the upper luminance value B _γ1 is 200, the suitability of the medium group G2 and the low group G1 is 0, and the suitability of the high group G3 is 1. On the other hand, since the lower luminance value B _γ2 is 100, the suitability of the high group G3 is 0, the suitability of the medium group G2 is 0.6, and the suitability of the low group G1 is 0.2. FIG. 21 is a table showing the compatibility of the upper and lower luminance values B _γ1 and B _γ2 in the above example.

In step S130d, determination values T1 to T6 are calculated based on the suitability acquired in step S130c. The definitions of the determination values T1 to T6 are as shown in FIG. When the above example is applied, the suitability of the high group G3 with the upper luminance value _Bγ1 is 1, and the suitability of the low group G1 with the lower luminance value _Bγ2 is 0.2. .2 and T1 = 0.2. Furthermore, the suitability of the high group G3 with the upper luminance value B _γ1 is 1, and the suitability of the middle group G2 with the lower luminance value B _γ2 is 0.6. 0.6. Also, since the compatibility of the high group G3 below luminance value B _.gamma.2 it is 0, and all determination value T3~T6 0.

  In step S130e, the second membership function X2 stored in advance in the HDD 34 is acquired, and the tilt angle θ is calculated from the second membership function X2. FIG. 23 is a graph showing the second membership function X2. In the figure, the horizontal axis indicates the inclination angle θ, and the vertical axis indicates the determination values T1 to T6. The second membership function X2 is configured by a substantially mountain-shaped function provided for each of the groups K1 to K6 corresponding to the inclination angle θ.

  Each of the groups K1 to K6 has a peak at an inclination angle θ (θ = 0 °, 15 °, 30 °, 45 °, 60 °, 75 °), and has a shape that widens the hem to the left and right. Then, the suitability determination of the group K1 is performed based on the determination value T1, the conformity determination of the group K2 is performed based on the determination value T2, the conformity determination of the group K3 is performed based on the determination value T3, and the conformity determination of the group K4 is performed. The determination is made by the determination value T4, the determination of the suitability of the group K5 is made by the determination value T5, and the determination of the suitability of the group K6 is made by the determination value T6.

  In the above example, since T1 = 0.2, T2 = 0.6, and T3 = T4 = T5 = T6 = 0, the matching region V in which the suitability is satisfied by the determination values T1 to T6 in the groups K1 to K6. Becomes a diagonal line. Then, a value obtained by reading the horizontal axis of the center of gravity Z of the matching region V is calculated as the inclination angle θ. Note that, in the matching region V, the overlapping of different groups K1 to K6 is not performed by overlapping. That is, the center of gravity Z is calculated assuming that there is no overlap. In the example of the figure, the inclination angle θ is calculated as 10 °.

  When the tilt angle θ is calculated, it is determined in step S130f whether or not it is the final pixel P. When the inclination angle θ is not calculated for the final pixel P, a new pixel P is selected in step S130a, and steps S130b to S130e are executed in the same manner. In this way, the inclination angle θ can be calculated for all the pixels P. When the inclination angle θ is calculated for the final pixel P in step S130f and it is confirmed that the inclination angle θ is calculated for all the pixels P, the angle image 33b can be generated in step S130g. When the angle image 33b is generated, step S140 and subsequent steps shown in FIG. 4 are executed as described above. That is, as shown in FIG. 7, the solder shape is reproduced, and pass / fail judgment is performed based on the solder shape.

Here, in the second membership function X2, when the inclination angle θ is 0 °, that is, when the center of gravity of the matching region V is 0 °, T1 = 1, T2 = T3 = T4 = T5 = T6 = 0 Must. When the inclination angle θ is 15 °, T2 = 1, T1 = T3 = T4 = T5 = T6 = 0. Thus, the determination values T1 to T6 when the inclination angle θ is 0 °, 15 °, 30 °, 45 °, 60 °, and 75 ° are clear, and the upper and lower luminance values B that determine the determination values T1 to T6. _γ1 and B _γ2 are also clear. For example, T2 = 1, T1 = T3 = T4 = T5 = T6 = 0 when the inclination angle θ is 15 ° is when the upper luminance value B _γ1 is 192 or more and the lower luminance value B _γ2 is 128. Limited. Similarly, the reason why T3 = 1, T1 = T2 = T4 = T5 = T6 = 0 when the inclination angle θ is 30 ° is that the upper luminance value B _γ1 is 192 or more and the lower luminance value B _γ2 is 192 or more. Limited to cases.

Thus, the correspondence between the inclination angle θ and the upper and lower luminance values B _γ1 and B _γ2 is known for typical inclination angles θ of 0 °, 15 °, 30 °, 45 °, 60 °, and 75 °. In this case, by using the membership functions X1 and X2 for the upper and lower luminance values B _γ1 and B _γ2 and the inclination angle θ, the corresponding upper and lower luminance values B _γ1 and B _γ2 can be estimated for other inclination angles θ. it can. That is, with respect to typical inclination angles θ (0 °, 15 °, 30 °, 45 °, 60 °, 75 °), the correspondence relationship with the upper and lower luminance values B _γ1 and B _γ2 is investigated in advance, and the same correspondence is obtained. By defining the membership functions X1 and X2 based on the relationship, the correspondence relationship of the other inclination angles θ is specified by interpolation.

  Since the curve shapes of the membership functions X1 and X2 are created in an estimated manner, the calculated inclination angles θ (other than 0 °, 15 °, 30 °, 45 °, 60 °, and 75 °) are used. Some estimation error may occur. Therefore, the accuracy of each inclination angle θ of the solder shape reproduced as shown in FIG. 7 is inferior. However, although individual accuracy is inferior, the tendency of the overall solder shape can be grasped. Therefore, as in the first embodiment, it is preferable to calculate an approximate curve that fits the polygonal line shown in FIG.

  For example, a γ function that approximates a polygonal line may be calculated as shown in FIG. According to the γ function, the overall degree of unevenness of the solder shape can be evaluated by the magnitude of the γ value. In calculating the approximate γ function, the γ value may be varied to identify the γ value that gives the highest correlation coefficient between the polygonal line and the approximate curve. If the γ value is large, it can be said that the amount of solder is large, and if the γ value is small, it can be said that the amount of solder is small. Furthermore, when the correlation coefficient between the polygonal line and the approximate curve is low, it can be determined that the solder shape is not likely to be a smooth solder shape but likely to be an irregular defect. Further, the solder shape may be divided into several sections, and a γ function that approximates each section may be calculated.

(5) Summary:
In the present invention, by using an approximate expression F represented by formula (1), the brightness value B _a, by calculating the tilt angle theta _{a, b} from _b, and the inclination angle theta _{a, b} of the inspection target accurately Can be estimated. Tilt angle theta _{a, b} are to be calculated pixel P _a, each _b, it is possible to estimate the pixel P _a, and the arrangement of the _b, and the shape of the inspection object from an inclination angle θ _{a, b.} Then, by determining whether the estimated shape is a shape similar to a non-defective product / defective product, the quality of the inspection object can be determined.

1 is an overall view of a quality determination apparatus according to the present invention. It is an internal block diagram of a computer. It is a software block diagram for performing quality determination. It is a flowchart of a quality determination process. 3 is a plan view showing a field of view S. FIG. 3 is a plan view showing an evaluation region T. FIG. It is explanatory drawing which shows a mode that a solder shape is specified. It is a figure which shows the shape data corresponding to a solder shape. It is a figure explaining incident angle (gamma). It is a figure explaining a reflective state. It is a graph which shows the correspondence of an inclination angle and a luminance value. 3 is a graph showing an approximate expression F. It is a general view of the quality determination apparatus concerning a modification. It is an internal block diagram of the computer concerning a modification. It is a graph showing the approximate expression F _1, F _2. It is the table which prescribed | regulated the correspondence of typical luminance value and inclination angle. It is a figure which specifies the correspondence of a luminance value and an inclination angle by linear interpolation. It is a flowchart which shows the flow of the process which produces | generates an angle image using fuzzy reasoning. It is a software block diagram for performing quality determination. It is a graph which shows a 1st membership function. It is a table listing compatibility. It is a table | surface which shows the definition of a judgment value. It is a graph which shows a 2nd membership function. It is a figure explaining the state which made the gamma function approximated to the solder shape.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 ... Shape quality determination apparatus 20 ... Imaging unit 21 ... Controller 21a ... Image memory (VRAM)
22 ... Camera 22a ... Optical system 22b ... CCD imaging plate 23 ... XY stage 24 ... Ring light 30 ... Computer 31 ... CPU
32 ... RAM
33 ... Video memory (VRAM)
33a ... Captured image 33b ... Angle image 34 ... Hard disk (HDD)
34b, M ... pass / fail judgment program 34c ... substrate data 34d ... shape data 36 ... display 38a ... keyboard 38b ... mouse 50 ... mounting board 51 ... chip component 52 ... solder E1 ... table M1 ... imaging execution unit M2 ... imaging image acquisition unit M3 ... tilt angle acquisition unit M4 ... shape estimation unit M5 ... pass / fail judgment unit X1 ... first membership function X2 ... second membership function P ... pixel S ... field of view γ ... incident angle θ ... (average) tilt angle

Claims (8)

Irradiating means for irradiating the inspection object with inspection light at a predetermined incident angle;
Imaging means for acquiring a captured image represented by a luminance value of reflected light for each pixel by capturing a reflected image of the inspection light with respect to the inspection object;
Inclination angle acquisition means for acquiring the same inclination angle for each pixel from the correspondence relationship between the luminance value and the inclination angle of the inspection object reflected by the reflected light;
Shape estimation means for estimating the shape of the inspection object based on the inclination angle of each pixel acquired by the inclination angle acquisition means and the arrangement information of the pixels;
A shape pass / fail judgment device comprising: pass / fail judgment means for judging pass / fail based on the shape estimated by the shape estimation means.   2. The shape pass / fail determination according to claim 1, wherein the correspondence is defined by an approximate expression in which at least specular reflection and diffuse reflection when the inspection light is reflected by the inspection object are taken into account. apparatus.   3. The shape pass / fail determination apparatus according to claim 2, wherein at least the incident angle, the light amount of the inspection light, and the physical property value of the inspection object are given as constants in the approximate expression. The irradiation unit irradiates the inspection object with inspection light at a plurality of incident angles,
4. The tilt angle acquiring unit according to claim 1, wherein the tilt angle acquiring unit acquires the tilt angle for each of the pixels based on the plurality of correspondence relationships respectively defined for the plurality of incident angles. The shape quality determination device according to any one of the above.   The tilt angle acquisition means estimates a correspondence relationship between the other brightness values and the tilt angle based on a correspondence relationship between a representative representative brightness value and the tilt angle. The shape quality determination device according to any one of claims 1 to 4.   The inclination angle acquisition means estimates a correspondence relationship between the other luminance values and the inclination angle based on fuzzy inference using a membership function for the luminance value and a membership function for the inclination angle. The shape pass / fail judgment apparatus according to claim 5.   The quality determination means calculates a γ function that approximates the shape estimated by the shape estimation means, and performs quality determination based on a γ value of the γ function. The shape quality determination device according to any one of claims 6 to 6. An irradiation step of irradiating the inspection object with inspection light at a predetermined incident angle;
An imaging step of acquiring a captured image represented by a luminance value of reflected light for each pixel by capturing a reflected image of the inspection light with respect to the inspection object;
An inclination angle acquisition step of acquiring the same inclination angle for each of the pixels from the correspondence relationship between the luminance value and the inclination angle of the inspection object on which the reflected light is reflected;
A shape estimation step of estimating the shape of the inspection object based on the inclination angle of each pixel acquired in the inclination angle acquisition step and the arrangement information of the pixel;
A quality determination method comprising: a quality determination step of performing quality determination based on the shape estimated in the shape estimation step.

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