JP2014014857A - Image processing method, and image processing system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an image processing method, and image processing system capable of accurately recognizing a shape of a bead and reducing a calculation load of image processing.SOLUTION: An image processing method for recognizing a shape of a bead on the basis of a plurality of pieces of image data obtained by consecutively photographing and acquiring a welded area during welding includes: a step for binarizing each acquired image data so that a spatter area candidate being a candidate for a bright area corresponding to a spatter can clearly appear; a step for performing XOR operation processing of image data with respect to image data acquired before and after the image so as to extract a spatter area including a spatter area candidate changing between a plurality of pieces of the binarized image data; a step for determining whether the spatter area candidate is a movement spatter area; and a step for removing a spatter range including the movement spatter area in the case that the spatter area candidate is the movement spatter area. An image processing system uses the method.

Description

  The present invention relates to an image processing method for recognizing the shape of a bead formed in a welding region based on a plurality of image data obtained by continuously photographing and capturing a welding region being welded, and an image using the method. It relates to a processing system.

  Conventionally, image processing for recognizing the shape of a bead in a welding area is performed based on a plurality of images obtained by continuously capturing and capturing a welding area during welding with a camera, an optical sensor, or the like. However, spattering inevitably occurs when welding metals or the like. It is difficult to predict the spatter generation amount, generation timing, scattering direction, and the like, and when such spatter overlaps the bead, it is difficult to recognize the bead shape with high accuracy in image processing. There is.

  Regarding image processing of spatter, for example, in Patent Document 1, in an image obtained by continuously photographing and capturing a welding area during arc welding, detection lines are set on both sides in the image width direction with respect to the arc discharge portion. By detecting the spatter passing through the number of spatters, the number and size of the sputters are calculated.

JP 2009-28775 A

  However, in the image processing of Patent Document 1, the position of spatter cannot be grasped, and image processing cannot be performed by removing spatter from the captured image. Therefore, in such image processing, the bead shape cannot be recognized with high accuracy.

  Further, when it is attempted to accurately recognize the position and scattering direction of the sputter, it is necessary to perform a process of calculating the position and scattering direction of the spatter and storing data relating to the calculated position and scattering direction of the sputter. Therefore, there is a problem that the calculation load increases due to such processing.

  The present invention has been made in view of such a situation, and an object thereof is to provide an image processing method and an image processing system capable of accurately recognizing the shape of a bead and reducing the calculation load of image processing. It is in.

  In order to solve the problem, an image processing method according to an aspect of the present invention provides a shape of a bead formed in a welding region based on a plurality of image data obtained by continuously photographing and capturing a welding region during welding. An image processing method for recognizing each of the plurality of captured image data so that a sputter region candidate that is a bright region candidate corresponding to moving sputter or stationary sputter is highlighted, and An image captured before or next to the binarized image data so as to extract a sputter range including a sputter region candidate that changes between the binarized image data. A step of performing an XOR operation on the data, and determining whether or not the sputter region candidate is a moving sputter region corresponding to a slender moving sputter. If a step, the sputtered area candidate is determined to the a mobile sputter area, and removing the sputtered range including the moving sputtering zone.

  In the image processing method according to an aspect of the present invention, the step of removing the sputtering area including the moving sputtering area calculates a plurality of representative center points in the moving sputtering area, and based on the calculated representative center points. A center line passing through the center of the width of the moving sputter region is calculated by approximate fitting of the line segment, the sputter range including the moving sputter region where the center line is calculated is stored, and the stored sputter range is stored as the image data. Removing from.

  In the image processing method according to the aspect of the present invention, the calculation of the representative center point is performed by forming an elliptical cutting ellipse area on the image, the major axis direction of the cutting ellipse area being the moving sputter area. The direction is changed so as to be orthogonal to the longitudinal direction, the centroid of the cutting ellipse region and the centroid of the moving sputter region are matched, and the binarized data representing the cutting ellipse region is moved to The binarization data representing the sputter region is converted so as to be opposite, and the converted binarization data of the cut elliptical region and the binarization of the moving sputter region are separated so as to separate the moving sputter region. AND operation processing is performed on the data, the centroids of the moving sputter regions separated by the AND operation processing are calculated, and the centroids of the moving sputter regions before the separation Each centroid moving sputtering region that is includes defining as representative central point.

  In the image processing method according to one aspect of the present invention, when it is determined that the sputter region candidate is not the moving sputter region, it is determined whether or not the sputter region candidate is a static sputter region corresponding to a static sputter. And a step of storing a sputter range including the static sputter region and removing the stored sputter range when it is determined that the sputter region candidate is the static sputter region.

  In the image processing method according to an aspect of the present invention, in determining whether the sputter region candidate is the stationary sputter region, a shortest distance between the sputter region candidate and a bead region corresponding to the bead is determined. When the length is equal to or longer than a predetermined length, it is determined that the sputter region candidate is the stationary sputter region.

  In the image processing method according to an aspect of the present invention, when the sputter region candidate has an isotropic shape in the determination as to whether or not the sputter region candidate is the stationary sputter region, It is determined that the region is the static sputtering region.

  An image processing system according to one embodiment of the present invention uses the above-described image processing method.

  According to the present invention, the following effects can be obtained. An image processing method according to an aspect of the present invention is an image processing method for recognizing the shape of a bead formed in a welding region based on a plurality of image data obtained by continuously capturing and capturing a welding region during welding. Each of the plurality of captured image data is binarized so that a sputter region candidate that is a bright region candidate corresponding to moving sputter or stationary sputter emerges, and the binarized plural The binarized image data is subjected to an XOR operation on the image data captured before or next to the image data so as to extract a sputter range including a sputter region candidate that changes between the image data. Determining whether or not the sputter region candidate is a moving sputter region corresponding to a slender moving sputter; and If the frequency candidate is determined to the a mobile sputter area, and removing the sputtered range including the moving sputtering zone. Further, in the image processing method according to one aspect of the present invention, the step of removing the sputtering range including the moving sputter region calculates a plurality of representative center points in the moving sputter region, and the calculated representative center points The center line passing through the width center of the moving sputter region is calculated by line segment approximation fitting based on the above, the sputter range including the moving sputter region where the center line is calculated is stored, and the stored sputter range is Including removal from the image data. Therefore, the moving sputter region on the image is removed, and the bead shape can be accurately recognized without being affected by the moving spatter. In particular, when the moving sputter overlaps with the bead, the shape of the bead can be accurately recognized by using images before and after the timing when the moving sputter overlaps with the bead. Further, since the moving sputter region is removed from the image data and only the image data required for bead shape recognition is subjected to image processing, the calculation load of image processing can be reduced.

  In the image processing method according to the aspect of the present invention, the calculation of the representative center point is performed by forming an elliptical cutting ellipse area on the image, the major axis direction of the cutting ellipse area being the moving sputter area. The direction is changed so as to be orthogonal to the longitudinal direction, the centroid of the cutting ellipse region and the centroid of the moving sputter region are matched, and the binarized data representing the cutting ellipse region is moved to The binarization data representing the sputter region is converted so as to be opposite, and the converted binarization data of the cut elliptical region and the binarization of the moving sputter region are separated so as to separate the moving sputter region. AND operation processing is performed on the data, the centroids of the moving sputter regions separated by the AND operation processing are calculated, and the centroids of the moving sputter regions before the separation Each centroid moving sputtering region that is includes defining as representative central point. Therefore, the representative center point of the moving sputter region used for line segment approximation fitting can be easily calculated, and the calculation load of image processing can be reduced.

  In the image processing method according to one aspect of the present invention, when it is determined that the sputter region candidate is not the moving sputter region, it is determined whether or not the sputter region candidate is a static sputter region corresponding to a static sputter. And a step of storing a sputter range including the static sputter region and removing the stored sputter range when it is determined that the sputter region candidate is the static sputter region. Therefore, the static sputter region on the image is removed, and the bead shape can be accurately recognized without being affected by the static sputter. In addition, since the static sputter region is removed from the image data and only the image data required for bead shape recognition is subjected to image processing, the calculation load of image processing can be reduced.

In the image processing method according to an aspect of the present invention, in determining whether the sputter region candidate is the stationary sputter region, a shortest distance between the sputter region candidate and a bead region corresponding to the bead is determined. When the length is equal to or longer than a predetermined length, it is determined that the sputter region candidate is the stationary sputter region. In the image processing method according to one aspect of the present invention, when the sputter region candidate has an isotropic shape in the determination as to whether or not the sputter region candidate is the stationary sputter region, It is determined that the candidate is the stationary sputtering region.
Therefore, the stationary sputter region can be accurately determined, and the stationary sputter region can be reliably removed. Therefore, the bead shape can be accurately recognized.

  An image processing system according to one embodiment of the present invention uses the above-described image processing method. Therefore, the bead shape can be accurately recognized as described above, and the calculation load of image processing can be reduced.

It is a schematic diagram which shows an example of the bead formed in a welding area | region. 1 is a block diagram illustrating an image processing system according to a first embodiment of the present invention. It is a schematic diagram which shows the laser irradiation part and monitor part of the image capture device in 1st Embodiment of this invention. It is a figure which shows the relationship between the radiation intensity of a black body radiation, and a wavelength. It is a figure which shows the relationship between the relative sensitivity of the image pick-up element produced from a silicon-type semiconductor, and the wavelength input into an image pick-up element. It is a figure which shows an example of the relationship between the time passage just after welding in the 1st Embodiment of this invention, and the brightness | luminance of residual heat emission. It is a block diagram which shows the image processing part of the image processing apparatus in 1st Embodiment of this invention. In 1st Embodiment of this invention, it is a schematic diagram which shows an example of the image which displayed the bead area | region corresponding to the actual bead. FIG. 9A is a schematic diagram illustrating an example of an image displaying moving sputtering. FIG. 9B is a schematic diagram illustrating an example of an image captured next to FIG. FIG. 9C is a schematic diagram illustrating an example of an image captured next to FIG. 9B. FIG. 9D is a schematic diagram illustrating an example of an image captured next to FIG. 9C. FIG. 10A is a schematic diagram illustrating an example of an image displaying stationary sputtering. FIG. 10B is a schematic diagram illustrating an example of an image captured next to FIG. FIG. 10C is a schematic diagram illustrating an example of an image captured next to FIG. FIG. 10D is a schematic diagram illustrating an example of an image captured next to FIG. FIG. 11A is a schematic diagram showing an example of an image in which an initial cut elliptical area is displayed together with a moving sputter area in the first embodiment of the present invention. FIG. 11B is a schematic diagram illustrating an example of an image in a state where the direction of the cutting elliptical region in FIG. FIG. 11C is a schematic diagram showing an example of an image in a state in which the centroid of the cutting elliptical region in FIG. 11B and the centroid of the moving sputter region coincide with each other. FIG. 11D is a schematic diagram showing an example of an image in a state where the moving sputter region is separated by the cut elliptical region of FIG. FIG.11 (e) is a schematic diagram which shows an example of the image in the state which calculated the centroid of the separated movement sputter | spatter area | region of FIG.11 (d). FIG. 11 (f) forms a center line based on the representative center point consisting of the centroid of the moving sputter region before separation in FIG. 11 (c) and the centroid of the moved sputter region after separation in FIG. 11 (e). It is a schematic diagram which shows an example of the image in the state which was made. In 1st Embodiment of this invention, it is a schematic diagram which shows an example of the image which displayed the static sputtering which calculated the representative center point. It is a flowchart explaining the outline | summary of the sputter removal method used for the image processing method which concerns on 1st Embodiment of this invention. It is a flowchart explaining the line segment approximate fitting of FIG. 14 is a flowchart for explaining determination of stationary sputtering in FIG. 13.

[First Embodiment]
An image processing system and an image processing method according to the first embodiment of the present invention will be described.

  Initially, with reference to FIG. 1, the bead m formed in the welding area J of the welding member M which is the object which performs image processing is demonstrated. The bead m formed in a substantially arc shape includes a joining start end portion (hereinafter referred to as “start end portion”) m1 formed at a laser welding start point and a joining end portion (hereinafter referred to as “laser welding end point”). , M2 and a joining intermediate portion (hereinafter referred to as “intermediate portion”) m3 formed between the start end portion m1 and the end portion m2. In the present embodiment, as an example, the bead m is formed in a substantially arc shape, but may have other shapes such as a linear shape, an L shape, a wave shape, and the like.

  Referring to FIG. 2, the image processing system 1 includes an image capturing device 2. The image capturing device 2 can irradiate the welding region J of the welding member M with a laser beam L <b> 1 for welding. The welding region J where the residual heat emission occurs is photographed, and an image of the photographed welding region J is captured. The image processing system 1 also has an image processing device 3 connected to the image capturing device 2. The image processing device 3 includes an image processing unit 4, and the image processing unit 4 recognizes the shape of the bead m based on the image of the welding region J captured by the image capturing device 2. The image processing apparatus 3 includes a bead shape determination unit 5, and the bead shape determination unit 5 determines a defect occurring in the bead m based on the shape of the bead m recognized by the image processing unit 4. It has become.

  Here, the details of the image capturing device 2 will be described with reference to FIGS. 2 and 3. Referring to FIG. 2, the image capturing device 2 includes a laser irradiation unit 6, and the laser irradiation unit 6 is configured to be able to irradiate the welding region J of the welding member M with the laser beam L <b> 1 for welding. Has been. The image capturing device 2 includes a monitor unit 7, and the monitor unit 7 is configured to continuously capture images of the welding region J irradiated with the laser. The image capturing device 2 includes a storage unit 8, and the storage unit 8 is configured to continuously store images taken by the monitor unit 7. The image capturing device 2 includes an image capturing unit 9, and the image capturing unit 9 is configured to capture an image stored in the storage unit 8.

  Referring to FIG. 3, the laser irradiation unit 6 includes a laser oscillator 6a, and the laser oscillator 6a is configured to be able to emit laser light L1. The laser irradiation unit 6 includes a substantially flat half mirror 6b, and the half mirror 6b is disposed on the optical path of the laser light L1 emitted from the laser oscillator 6a. The front surface 6b1 and the back surface 6b2 of the half mirror 6b are inclined at a predetermined angle θ1 with respect to the optical path of the laser light L1 emitted from the laser oscillator 6a. As an example, the predetermined angle θ1 is preferably 45 degrees. The laser irradiation unit 6 has a welding condensing lens 6c. The welding condensing lens 6c is disposed on the optical path of the laser light L1 that has passed through the half mirror 6b, and this laser light L1 is transmitted to the welding member M. It is comprised so that it may condense on. In such a laser irradiation unit 6, the laser beam L1 emitted from the laser oscillator 6a passes through the half mirror 6b and is collected by the welding condenser lens 6c, and then irradiated to the welding member M. It will be. Further, part of the laser light L1 irradiated to the welding member M is reflected, and this reflected light (hereinafter referred to as “monitoring light”) L2 passes through the welding condensing lens 6c and the half mirror 6b. After the angle is changed by, it is sent to the monitor unit 7.

  The monitor unit 7 includes a substantially flat mirror 7a. The mirror 7a is disposed on the optical path of the monitoring light L2 whose angle is changed by the half mirror 6c of the laser irradiation unit 6, and the reflection surface 7a1 of the mirror 7a. Is inclined at a predetermined angle θ2 with respect to the optical path of the monitoring light L2. The monitor unit 7 has a magnification adjustment lens 7b, and the magnification adjustment lens 7b is configured to adjust the photographing magnification. The magnification adjusting lens 7b is disposed on the optical path of the monitoring light L2 reflected by the mirror 7a. The monitor unit 7 includes a long-pass filter (hereinafter referred to as “Si long-pass filter”) 7c corresponding to an imaging element (hereinafter referred to as “Si-based imaging element”) 7f manufactured from a silicon-based semiconductor, which will be described later. The Si long pass filter 7c is configured to transmit light in a wavelength range of 800 nm or more. The Si long pass filter 7c is disposed on the optical path of the monitoring light L2 that has passed through the magnification adjusting lens 7b. The monitor unit 7 has an ND filter 7d, and the ND filter 7d is configured to reduce the amount of light passing therethrough. The ND filter 7d is disposed on the optical path of the monitoring light L2 that has passed through the Si long pass filter 7c. The monitor unit 7 includes an imaging condenser lens 7e. The imaging condenser lens 7e is disposed on the optical path of the monitoring light L2 that has passed through the ND filter 7d, and this monitoring light L2 is supplied to Si described later. The system imaging device 7f is configured to collect light on the imaging surface. The monitor unit 7 includes a Si image sensor 7f, and the Si image sensor 7f is configured to convert the monitoring light L2 into an analog electric signal. The Si-based image sensor 7f has sensitivity to light in a wavelength range of 200 nm to 1100 nm. The monitor unit 7 has an amplifier 7g, and the amplifier 7g is configured to amplify an analog electric signal sent from the Si-based image sensor 7f. The monitor unit 7 includes an A / D converter 7h, and the A / D converter 7h is configured to convert the analog electric signal amplified by the amplifier 7g into a digital electric signal. The digital electric signal converted by the A / D converter 7h is sent to the storage unit 8. The frame rate of the monitor unit 7 is 50 Hz or more and 1000 Hz or less.

  The conditions of the imaging surface of the Si-based imaging element 7f will be described. When the imaging surface of the Si-based image sensor 7f is significantly larger than the area where the entire bead m is arranged, the bead m displayed on the image is represented by a small number of pixels, so that the shape of the bead m can be accurately recognized. Disappear. Therefore, assuming that the imaging surface of the Si-based imaging element 7f is formed in a substantially square shape, the length of one side of the imaging surface is d, the focal length of the welding condenser lens 6c is f1, and the imaging surface When the focal length of the condenser lens 7e is f2, the magnification of the magnification adjusting lens 7b is s, and the maximum length of the region where the entire bead m is arranged is l, the length of one side of the imaging surface of the Si imaging element 7f. Is preferable to satisfy the condition of the following formula (1).

  The wavelength range of light passing through the Si long pass filter 7c will be described. Plasma light generated during laser welding contains many components of transition emission generated by orbital electrons of atoms, and the wavelength range of this transition emission is typically in the range of 200 nm to 780 nm corresponding to the visible range. It has become. On the other hand, the relationship between the radiation intensity of black body radiation and the wavelength is as shown in the graph of FIG. 4 when the absolute temperature is calculated as 1200 K, 1000 K, and 800 K using the black body radiation equation. . In the graph of FIG. 4, the calculation result when the absolute temperature is 1200K is indicated by a solid line A1, the calculation result when the absolute temperature is 1000K is indicated by a broken line A2, and the calculation result when the absolute temperature is 800K. This is indicated by a one-dot chain line A3. Referring to the graph of FIG. 4, the radiant intensity of blackbody radiation increases as the wavelength increases. Further, the radiation intensity of black body radiation increases as the temperature increases. Therefore, it can be confirmed that the radiation intensity of the black body radiation included in the residual heat emission having a high temperature is increased.

  Further, the relationship between the relative sensitivity of the Si image sensor 7f and the wavelength of light input to the Si image sensor 7f is typically as shown in FIG. As shown in FIG. 5, the sensitivity of the Si-based image sensor 7f decreases in the wavelength range of 600 nm or more, and the Si-based image sensor 7f hardly senses low intensity light in the wavelength range of 800 nm to 1100 nm. , And tends to sense high intensity light.

  Therefore, in consideration of the upper limit 780 nm of the wavelength range of transition emission included in the plasma light and the variation in wavelength, the wavelength range of the light transmitted through the Si long pass filter 7c is set to 800 nm or more. Therefore, light is transmitted to the Si image sensor 7f in a wavelength range of 800 nm or more, and the Si image sensor 7f senses input light in a wavelength range of 800 nm to 1100 nm. In such a wavelength range, the Si-based imaging element 7f is difficult to detect plasma light including a transition light emission component having a low radiation intensity, but includes a large amount of a light emission component due to black body radiation having a high radiation intensity. Residual heat emission is easily detected. Note that the Si long-pass filter 7c is preferably configured to block light having a wavelength shorter than 800 nm. However, the Si imaging element 7f only needs to be able to sense light in the wavelength range of 800 nm to 1100 nm. For example, the Si long-pass filter 7c is configured to block light having a wavelength smaller than 800 nm, 900 nm, or 1000 nm. It may be.

  The range of the frame rate of the monitor unit 7 will be described. Since the generated plasma occupies a large area near the start of welding, the bead m that has already been welded cannot often be observed. Therefore, it is effective to store an image in the storage unit 8 after a certain time has elapsed since the start of welding. Further, in order to set the entire bead m as a target of image processing, it is only necessary to use a part of a plurality of images acquired in succession. Therefore, a part of the plurality of images may be acquired. Also, the images used for image processing need not be completely continuous. In the terminal portion m2 of the bead m, when a plurality of images are not captured at a high speed, the metal cools down. Therefore, it is necessary to capture images at a high sampling rate. On the other hand, when an image is captured at a high sampling rate during observation from the start of welding to the end of welding, a plurality of images with almost no change are acquired. Since it is useless to calculate similar characteristics in such a plurality of images, it is preferable to determine the frame rate of the monitor unit 7 in consideration of shortening the calculation processing time, saving the capacity of the storage unit 8, and the like. . Therefore, as the upper limit of the frame rate increases, the number of images to be captured increases, so that the accuracy of recognizing the shape of the bead m increases, while the number of images to be captured per second increases. When the frame rate is greater than 1000 frames (that is, when the frame rate is greater than 1000 Hz), the upper limit value of the frame rate is set to 1000 Hz in consideration of an increase in calculation load of image processing.

  On the other hand, when the lower limit value of the frame rate is low, the welding region J of the bead m to be photographed moves from the timing of photographing one image to the timing of photographing the next image, and the monitor unit There is a risk of deviating from the shooting range captured by 7. In this case, the bead m cannot be accurately photographed. Therefore, the lower limit value of the frame rate needs to satisfy the following conditions.

  When the frame rate is f, the moving speed of the laser beam L1 used for welding is Vm, and the shortest distance from the center of the shooting range to the boundary between the shooting range and the shooting range is Rm, the frame rate Preferably satisfies the condition of the following expression (2).

  Under typical conditions, Vm is 0.133 m / sec (8 m / min) and Rm is 0.002 m (2 mm). Therefore, it is necessary to make f larger than about 67 Hz from the equation (2). Furthermore, the lower limit value of the frame rate is set to 50 Hz in consideration of variations in the moving speed of the laser light L1.

  Referring to FIG. 6, the image capturing unit 9 is configured to capture an image of residual heat emission that occurs within a predetermined time immediately after the end of welding. Specifically, the image capturing unit 9 starts capturing an image when the average brightness G of the image is equal to or higher than a predetermined capture start brightness threshold g1, and the average brightness G of the image is a predetermined capture end brightness threshold g2. In the following cases, it is configured to recognize that the residual heat emission has ended and end the image capture.

  Here, an example of a preferable form of the image capturing device 2 will be described. The residual heat emission is attenuated after being generated for several tens of milliseconds (milliseconds) immediately after the end of welding. In this case, a high-speed camera with a frame rate of about 500 Hz (cycle 2 ms) is preferably used for the monitor unit 7 and about 10 images (= 20 ms ÷ 2 ms) are captured. Moreover, it is preferable that a high dynamic range camera is used for the monitor unit 7, and since the signal detection dynamic range is wide and the measurable luminance range is wide, it is possible to take images during and immediately after welding. . In the image capturing unit 9, it is preferable that the start luminance threshold value g <b> 1 for starting image capturing is an intermediate value of the average luminance G during and immediately after welding. The end luminance threshold value g2 for completing the image capture is preferably smaller than the start luminance threshold value g1 and larger than the average luminance G of the image that has become so dark that residual heat emission cannot be confirmed.

  Next, details of the image processing unit 4 of the image processing apparatus 3 will be described with reference to FIGS. 7 and 8. Referring to FIG. 7, the image processing unit 4 includes a bead recognition unit 10, which recognizes a bead area candidate based on the image captured by the image capturing device 2. Yes. The bead area candidate is a bright area in which the residual heat emission luminance H is higher than a predetermined contour luminance threshold value h, and the contour luminance threshold value h is set so that the contour line of the bead m can be identified. In addition, the bead area | region E is comprised from the some bead area | region point e, as shown in FIG. The bead region E has a start end portion E1 corresponding to the start end portion m1 of the bead m, an intermediate portion E2 corresponding to the end portion m2 of the bead m, and an end portion E3 corresponding to the intermediate portion m3 of the bead m. Yes. As an example, the bead area point e is represented by one or more pixels on the image, and the plurality of bead area points e may be arranged adjacent to each other or arranged at intervals of a pixel unit. .

  The image processing unit 4 includes a bead discriminating unit 11. The bead discriminating unit 11 selects a bead area E corresponding to an actual bead from the plurality of bead area candidates when the plurality of bead area candidates are recognized. It comes to choose. Further, the bead discriminating unit 11 calculates the aspect ratio (aspect ratio) of each bead area candidate, and selects a bead area E corresponding to the actual bead m from the plurality of bead area candidates based on the aspect ratio. It is preferable that For example, when the aspect ratio is larger than a value corresponding to a horizontally long shape of a general bead m, it may be set to recognize that such a bead area candidate corresponds to an actual bead m. When the bead area candidates corresponding to the actual bead m and the spatter scattered during welding are recognized, the bead area candidates corresponding to the spatter are formed in an isotropic shape, whereas the bead m Is formed in a horizontally long shape. Therefore, the bead area E corresponding to the actual bead m is accurately determined. Further, in consideration of the case where the bead area candidates corresponding to the spatter are not formed in an isotropic shape, the bead discriminating means 11 moves in an image in which a plurality of bead area candidates are captured before and after the time. It is preferable to determine whether or not the bead area candidate that is stopped is the bead area E corresponding to the actual bead m.

  Here, with reference to FIGS. 9A to 9D and FIGS. 10A to 10D, images displaying moving sputtering and stationary sputtering will be described. Referring to FIGS. 9A to 9D, an elongated moving sputter region N1 corresponding to moving spatter and a bead region E corresponding to bead m are displayed on the image. As shown in FIGS. 9A to 9D, the moving sputter region N1 moves from the peripheral region of the image toward the central region of the image. In FIG. 9D, the moving sputter region N1 overlaps the bead region E. Referring to FIGS. 10A to 10D, a substantially circular stationary sputter region N2 corresponding to stationary sputter and a bead region E corresponding to bead m are displayed on the image. As shown in FIG. 10A, the stationary sputter region N2 has an elongated shape in the initial state. However, as shown in FIGS. 10B and 10C, the static sputtering region N2 changes so as to be shorter with respect to one end thereof. Thereafter, the static sputtering region N2 changes to a substantially circular shape as shown in FIG.

  Further, the image processing unit 4 is configured as follows in order to remove the moving sputter region N1 and the stationary sputter region N2 after discriminating the bead region E from the bead region candidates. Referring to FIG. 7, the image processing unit 4 includes a binarization unit 12, and the binarization unit 12 binarizes each of a plurality of captured image data with a predetermined binarization threshold. It is supposed to be. It should be noted that the binarization threshold is preferably set so that the sputter region candidate is raised on the image, and in particular, this binarization threshold is a value that can clearly raise the sputter region in advance. It is good to confirm and to determine based on this confirmation result. The sputter region candidate may be a bright region in which the residual heat emission luminance H is larger than the contour luminance threshold h as described above. The image processing unit 4 includes an XOR operation unit 13, and the XOR operation unit 13 can extract a sputter range including a sputter region candidate that changes between a plurality of binarized image data. The binarized image data is subjected to an XOR operation on the image data captured before or next to the image data. The image processing unit 4 includes a noise processing unit 14, and the noise processing unit 14 is configured to remove noise included in a plurality of image data subjected to the XOR operation process. The image processing unit 4 has a moving sputter determination unit 15, and the moving sputter determination unit 15 determines whether or not the sputter region candidate is a moving sputter region N 1 corresponding to a slender shaped mobile sputter. ing. The image processing unit 4 has a representative center point calculation element 16, and when the representative center point calculation element 16 determines that the sputter region candidate is the moving sputter region N <b> 1 as shown in FIG. In addition, the representative center point r1 of the moving sputter region N1 is calculated.

  Referring to FIG. 7 again, the image processing unit 4 has a center line forming unit 17, and the center line forming unit 17 is a line based on a plurality of representative center points r1, as shown in FIG. A center line R1 passing through the width center of the moving sputter region N1 is calculated by minute approximation fitting. As an example, a linear function may be used for line segment approximation fitting. This linear function may be defined based on the following equation when a plurality of representative center points r1 are located on the XY coordinates. When the maximum value of the X coordinate at the plurality of representative center points r1 is Xmax and the minimum value of the X coordinate at the plurality of representative center points r1 is Xmin, the change amount of the X coordinate is DX = Xmax−Xmin. When the maximum value of the Y coordinate at the plurality of representative center points r1 is Ymax and the minimum value of the Y coordinate at the plurality of representative center points r1 is Ymin, the amount of change in the Y coordinate is DY = Ymax−Ymin. When DX is greater than or equal to DY, the linear function is defined by Y = aX + b (a and b are coefficients), whereas when DX is less than DY, the linear function is X = aY + b (a and b are coefficients). Defined.

  Referring to FIG. 7, the image processing unit 4 has a moving sputter storage unit 18, and the moving sputter storage unit 18 stores a sputter range including a moving sputter region where the center line R <b> 1 is calculated. . As an example, the stored center line R1 may be stored as a linear function defined by aX + bY + c = 0 (a, b, and c are coefficients). The image processing unit 4 has a moving spatter removing unit 19. The moving spatter removing unit 19 removes the stored sputter range from the image data. The image processing unit 4 includes a stationary sputter determination element 20. When the moving sputter determination unit 15 determines that the sputter area candidate is not the moving sputter area N 1, the sputter area candidate is stationary. It is determined whether or not it is a static sputtering region N2 corresponding to sputtering. The image processing unit 4 includes a representative center point calculating unit 21. The representative center point calculating unit 21 calculates the centroid of the stationary sputtering region N2 as the representative center point r2, as shown in FIG. ing. Referring to FIG. 7 again, the image processing unit 4 has a stationary sputter storage unit 22, and the stationary sputter storage unit 22 determines that the sputter region candidate is the static sputter region N 2. The sputter range including is memorized. The image processing unit 4 has a stationary sputter removing unit 23, and the stationary spatter removing unit 23 removes the stored sputtering range.

  Details of the representative center point calculation element 16 will be described with reference to FIGS. 7 and 11A to 11F. Referring to FIG. 7, the representative center point calculation element 16 has an ellipse forming unit 24. The ellipse forming unit 24 cuts an elliptical bright area on the image as shown in FIG. An ellipse area Z is formed. Referring to FIG. 7, the representative center point calculating element 16 has a direction changing means 25, and the direction changing means 25, as shown in FIG. The direction is changed so as to be orthogonal to the longitudinal direction of the moving sputter region. Referring to FIG. 7, the representative center point calculating element 16 has an ellipse moving means 26, and the ellipse moving means 26 moves with the centroid Cz of the cutting ellipse area Z as shown in FIG. The centroid Cn1 of the sputter region N1 is made to coincide. Referring to FIG. 7, the representative center point calculating element 16 has binarized data reversing means 27. The binarized reversing means 27 converts the binarized data representing the cutting ellipse area Z into the moving sputter region. The binary data representing N1 is converted in reverse. Referring to FIG. 7, the representative center point calculating element 16 has an AND operation means 28, and the AND operation means 28 is cut so as to separate the moving sputter region N1 as shown in FIG. 11 (d). An AND operation process is performed between the binarized data of the elliptical area Z for use and the binarized data of the moving sputtering area N1. Referring to FIG. 7, the representative center point calculating element 16 has a representative center point defining means 29, and the representative center point defining means 29 is, as shown in FIG. The centroid Cn1 and the centroid Cn1 ′ of each of the separated moving sputter regions N1 ′ are calculated as the representative center point r1. As shown in FIG. 11F, the center line R1 is formed based on the representative center point r1 calculated in this way.

  Details of the stationary sputter determination element 19 will be described with reference to FIGS. 7 and 12. Referring to FIG. 7, the stationary sputter determination element 19 includes a distance determination unit 29, and the distance determination unit 29 is located between the periphery of the bead region E and the periphery of the sputter region candidate as shown in FIG. 12. When the shortest distance d is equal to or longer than a predetermined length, it is determined that the sputter region candidate is the stationary sputter region N2. As an example, such a lower limit value of the predetermined length is a predetermined width of the bead m or a calculated width of the bead region E as a condition for clarifying whether or not the predetermined length is a part of the bead m. It is good to be. As an example, the upper limit value of the predetermined length may be the maximum length from the bead area E to the periphery of the captured image. Referring to FIG. 7, the stationary sputter determination element 20 includes a shape determination unit 31, and the shape determination unit 31 determines that the sputter region candidate is a static sputter region N <b> 2 when the sputter region candidate has an isotropic shape. It is determined to be. As an example of a criterion for determining whether or not a sputter region candidate has an isotropic shape, the aspect ratio of the sputter region candidate may be set to ½ or more and 2 or less.

  Here, a method for recognizing the shape of the bead m formed in the welding region J using the image processing system 1 of the present embodiment will be described. First, an image capturing method in the image capturing device 2 will be described. In the laser irradiation unit 6 of the image capturing device 2, a laser oscillator 6a emits a laser beam L1. The laser beam L1 emitted from the laser oscillator 6a passes through the half mirror 6b and is collected by the welding condensing mirror 6c, and then irradiated to the welding region J of the welding member M. Thereafter, residual heat emission is emitted from the portion where the bead m is formed by the laser light L1 irradiated to the welding region J of the welding member M, and becomes the monitoring light L2. The monitoring light L2 passes through the welding condenser lens 6c and is sent to the monitor unit 7 after the angle is changed by the half mirror 6b.

  In the monitor unit 7 of the image capturing device 2, the monitoring light L2 sent from the laser irradiation unit 6 is sent to the magnification adjusting lens 7b after the angle is changed by the mirror 7a. When the monitoring light L2 passes through the magnification adjusting lens 6b, the magnification is adjusted. The monitoring light L2 whose magnification is adjusted by the magnification adjusting lens 7b is sent to the Si long pass filter 7c. In the Si long pass filter 7c, a wavelength component smaller than 800 nm of the monitoring light L2 is blocked, and a wavelength component larger than 800 nm of the monitoring light L2 passes through the Si long pass filter 7c. The monitoring light L2 that has passed through the Si long pass filter 7c is sent to the ND filter 7d. In the ND filter 7d, the amount of the monitoring light L2 decreases so that the shape of the bead m can be clearly recognized by the image processing unit 4 of the image processing apparatus 3. The monitoring light L2 that has passed through the ND filter 7d is sent to the imaging condenser lens 7e. The monitoring light L2 is collected in the imaging condenser lens 7e. The monitoring light L2 collected by the photographing condenser lens 7e is irradiated to the Si-based image sensor 7f. In the Si-based imaging device 7f, the component in the wavelength range of 800 nm to 1100 nm in the monitoring light L2 is sensed, the sensed monitoring light L2 is converted into an analog electric signal, and this analog electric signal is sent to the amplifier 7g. In the amplifier 7g, the analog electric signal is amplified, and the amplified analog electric signal is sent to the A / D converter 7h. In the A / D converter 7h, the analog electric signal is converted into a digital electric signal, and this digital electric signal is sent to the storage unit 8. In the storage unit 8, the digital electric signal is stored as one image. In this way, the Si-based image sensor 7f is irradiated with the monitoring light L2, the Si-based image sensor 7f converts the monitoring light L2 into an analog electric signal, and the A / D converter 7h converts the analog electric signal into a digital electric signal. The operation of storing the digital electric signal as one image is continuously performed based on a frame rate larger than 50 Hz and smaller than 1000 Hz. Further, the image stored in the storage unit 8 is captured by the image capturing unit 9.

  Next, a method for recognizing the bead area E will be described. Based on the image captured by the image capturing unit 8 of the image capturing device 2, a bead area candidate having a residual heat emission brightness H greater than a predetermined contour brightness threshold h is recognized. Here, when a plurality of bead area candidates are recognized, the bead area E corresponding to the actual bead m is determined from the plurality of bead area candidates.

  Further, a sputter removal method will be described with reference to the flowchart of FIG. Each of the plurality of captured image data is binarized with a predetermined binarization threshold (S1). Image data obtained by capturing binarized image data before or next to the image data so as to extract a sputter range including a sputter region candidate changing between a plurality of binarized image data. Is subjected to XOR operation processing (S2). The noise of the image data subjected to the XOR operation processing is removed (S3). It is determined whether or not the sputter region candidate is a moving sputter region N1 corresponding to the elongated sputter (S4). If it is determined that the sputter region candidate is the moving sputter region N1 (YES), the representative center point r1 of the moving sputter region N1 is calculated (S5). A center line R1 passing through the width center of the moving sputtering region N1 is formed by linear function fitting based on the calculated representative center point r1 (S6). The sputter range including the moving sputter region N1 for which the center line R1 is calculated is stored (S7), the stored sputter range is removed (S8), and the sputter removal is terminated.

  On the other hand, if it is determined that the sputter region candidate is not the moving sputter region N1 (NO), it is determined whether or not the sputter region candidate is a static sputter region N2 corresponding to static sputter (S9). If it is determined that the sputter region candidate is the static sputter region N2 (YES), the centroid of the static sputter region N2 is calculated as the representative center point r2 (S10). The sputter range in which the representative center point r2 is calculated is stored (S11), the stored sputter range is removed (S12), and the sputter removal is terminated. On the other hand, if it is determined that the sputter region candidate is not the stationary sputter region N2 (NO), the sputter removal is finished as it is.

  The calculation of the representative center point r1 of the moving sputtering area N1 will be described in detail with reference to the flowchart of FIG. An elliptical area for cutting Z, which is an elliptical bright area, is formed on the image (S21). The cutting ellipse area Z is changed in direction so that the major axis direction thereof is orthogonal to the longitudinal direction of the moving sputtering area N1 (S22). The centroid Cz of the cutting ellipse area Z and the centroid Cn1 of the moving sputtering area N1 are matched (S23). The binarized data of the cutting ellipse area Z is reversed (S24). An AND operation process is performed between the binarized data of the cutting ellipse area Z and the binarized data of the moving sputter area N1 so as to separate the moving sputter area N1 (S25). Each centroid Cn1 'of the moving sputter region N1' separated by the AND operation processing is calculated (S26). The centroid Cn1 of the moving sputter region N1 before separation and the centroid Cn1 'of each of the separated moving sputter regions N1' are defined as representative central points r1 (S27).

  Details of the determination of the static sputtering region N2 will be described with reference to the flowchart of FIG. The shortest distance d between the periphery of the sputter region candidate and the periphery of the bead region E is calculated (S31). It is determined whether or not the calculated shortest distance d is greater than or equal to a predetermined length (S32). If the shortest distance d is equal to or longer than the predetermined length (YES), it is determined that the sputtering area candidate is the stationary sputtering area N2 (S33), and the determination of the stationary sputtering area N2 is ended.

  On the other hand, if the shortest distance d is smaller than the predetermined length (NO), it is determined whether or not the sputter region candidate has an isotropic shape (S34). If the sputter region candidate has an isotropic shape (YES), it is determined that the sputter region candidate is the static sputter region N2 (S33), and the determination of the static sputter region N2 is terminated. If the sputter region candidate is not isotropic (NO), it is determined that the sputter region candidate is not the static sputter region N2 (S35), and the determination of the static sputter region N2 is terminated.

  As described above, according to the present embodiment, the moving sputter region N1 on the image is removed, and the shape of the bead m can be accurately recognized without being affected by the moving sputter. In particular, when the moving sputter overlaps with the bead m, the shape of the bead m can be accurately recognized by using images before and after the timing when the moving sputter overlaps the bead m. Further, since the moving sputter region N1 is removed from the image data and only the image data required for the shape recognition of the bead m is subjected to image processing, the calculation load of image processing can be reduced.

  According to the present embodiment, as described above, the representative center point r1 of the moving sputter region N1 used for the line segment approximate fitting is simply calculated, and the calculation load of image processing can be reduced.

  According to the present embodiment, the static sputter region N2 on the image is removed, and the shape of the bead m can be accurately recognized without being affected by the static sputter. Further, since the static sputter region N2 is removed from the image data and only the image data required for the shape recognition of the bead m is image-processed, the calculation load of image processing can be reduced.

  According to the present embodiment, in determining whether or not the sputter region candidate is the stationary sputter region N2, the shortest distance d between the sputter region candidate and the bead region E corresponding to the bead m is a predetermined length or more. In some cases, it is determined that the sputter region candidate is the stationary sputter region. Further, in determining whether the sputter region candidate is the stationary sputter region N2, if the sputter region has an isotropic shape, it is determined that the sputter region candidate is the static sputter region N2. Therefore, the stationary sputter region N2 can be accurately determined and the stationary sputter region N2 can be reliably removed. Therefore, the shape of the bead m can be accurately recognized.

[Second Embodiment]
An image processing system according to the second embodiment of the present invention will be described below. The second embodiment is basically the same as the first embodiment. Elements similar to those in the first embodiment will be described using the same symbols and names as those in the first embodiment. Here, a configuration different from the first embodiment will be described.

  In this embodiment, instead of the Si long-pass filter 7c in the first embodiment, an InGaAs long-pass corresponding to an image sensor (hereinafter referred to as “InGaAs-based image sensor”) manufactured from an indium gallium arsenide-based semiconductor described later. A filter is provided. The long pass filter for InGaAs is configured to transmit light in a wavelength range of 1200 nm or more. In the present embodiment, an InGaAs image sensor is provided instead of the Si image sensor 7f of the first embodiment. The InGaAs-based image sensor has sensitivity to light in a wavelength range of 800 nm to 2600 nm. The InGaAs-based image sensor is configured to convert the monitoring light L2 sent to the imager 6f into an analog electric signal. Further, the conditions of the imaging surface of the InGaAs imaging device are the same as the imaging surface conditions of the Si imaging device 7f in the first embodiment.

  The wavelength range of light transmitted through the long pass filter for InGaAs will be described. As described above, plasma light generated during laser welding contains many components of transition emission generated by orbital electrons of atoms, and the wavelength range of this transition emission typically corresponds to the visible range. It is in the range of 200 nm to 780 nm. On the other hand, the radiation intensity of blackbody radiation increases as the wavelength increases. Further, the radiation intensity of black body radiation increases as the temperature increases. Therefore, it can be confirmed that the radiation intensity of the black body radiation included in the residual heat emission having a high temperature is increased. In addition, since light emitted from a laser or the like includes a wavelength component around 1060 nm, it is preferable that the light input to the InGaAs-based image pickup device avoid a wavelength range around 1060 nm.

  Therefore, in consideration of the upper limit 780 nm of the wavelength range of transition emission included in plasma light, avoiding light having a wavelength near 1060 nm corresponding to the emission wavelength of laser, etc., and variations in emission wavelength of laser, etc. The wavelength range of light passing through the InGaAs long pass filter is set to 1200 nm or more. For this reason, light is sent to the InGaAs imaging device in a wavelength range of 1200 nm or more, and the InGaAs imaging device senses input light in the wavelength range of 1200 nm to 2600 nm. The InGaAs long-pass filter is preferably configured to block light having a wavelength shorter than 1200 nm. However, since the InGaAs-based imaging device only needs to be able to sense light in the wavelength range of 800 nm to 2600 nm, for example, a long pass filter for InGaAs emits light having a wavelength smaller than 1300 nm, 1400 nm, 1500 nm, 1600 nm, 1700 nm, 1800 nm, or 1900 nm. You may be comprised so that it may interrupt | block.

  Moreover, the method of recognizing the shape of the bead m formed in the welding region J using the image processing system 1 of the present embodiment is the same as that of the first embodiment except for the configuration described above of the present embodiment. Yes.

  As described above, according to the present embodiment, the same effects as those of the first embodiment can be obtained.

[Third Embodiment]
An image processing system according to the third embodiment of the present invention will be described below. The third embodiment is basically the same as the first embodiment. Elements similar to those in the first embodiment will be described using the same symbols and names as those in the first embodiment. Here, a configuration different from the first embodiment will be described.

  In the present embodiment, a Si band-pass filter is provided instead of the Si long-pass filter 7c in the first embodiment. The band pass filter for Si is configured to transmit light in a wavelength range of 800 nm or more and 1050 nm or less.

  The wavelength range of light passing through the Si bandpass filter will be described. The lower limit value of the wavelength range of the light transmitted through the Si bandpass filter is based on the same reason that the lower limit value of the wavelength range of the light transmitted through the Si longpass filter 7c in the first embodiment is 800 nm. It is set to 800 nm. In addition, in consideration of avoiding light having a wavelength near 1060 nm, which corresponds to the emission wavelength of a laser, etc., and variations in the emission wavelength of the laser, etc., the upper limit value of the wavelength range of the light passing through the Si bandpass filter is It is set to 1050 nm.

  A method for recognizing the shape of the bead m formed in the welding region J using the image processing system 1 of the present embodiment is the same as that of the first embodiment except for the configuration described above of the present embodiment.

  As described above, according to the present embodiment, the same effects as those of the first embodiment can be obtained.

[Fourth Embodiment]
An image processing system according to the fourth embodiment of the present invention will be described below. The fourth embodiment is basically the same as the second embodiment. The same elements as those of the second embodiment will be described using the same symbols and names as those of the second embodiment. Here, a configuration different from the second embodiment will be described.

  In this embodiment, an InGaAs band-pass filter is provided instead of the InGaAs long-pass filter in the second embodiment. The bandpass filter for InGaAs is configured to transmit light in a wavelength range of 1200 nm or more and 2000 nm or less.

  The wavelength range of light that passes through the bandpass filter for InGaAs will be described. The lower limit value of the wavelength range of light passing through the InGaAs bandpass filter is 1200 nm based on the same reason that the lower limit value of the wavelength range of light passing through the InGaAs longpass filter in the second embodiment is set to 1200 nm. It is stipulated in. In addition, the upper limit of sensitivity to light in the long wavelength high sensitivity type InGaAs imaging device is 2600 nm, and the upper limit of sensitivity to light in the short wavelength high sensitivity type InGaAs imaging device is 1700 nm. Further, the short wavelength high sensitivity type InGaAs imaging device has a constant sensitivity (response performance) even in the range of 1700 nm to 2000 nm because its band gap gradually decreases. Therefore, the upper limit of the wavelength range of the light transmitted through the InGaAs band-pass filter is set to 2000 nm so as to correspond to all InGaAs-based image pickup devices such as the long wavelength high sensitivity type and the short wavelength high sensitivity type.

  As described above, according to the present embodiment, the same effects as those of the second embodiment can be obtained.

  Although the embodiments of the present invention have been described so far, the present invention is not limited to the above-described embodiments, and various modifications and changes can be made based on the technical idea of the present invention.

  For example, as a first modification of the present invention, the image capturing unit 3 may be configured to capture and capture welding other than laser welding. For example, welding other than laser welding may be arc welding, electroslag welding, electron beam welding, or the like.

  As a second modification of the present invention, the image capturing unit 3 may be configured to capture and capture light emitted by a laser other than residual heat emission during welding. Further, when the image capturing unit 3 captures and captures welding other than laser welding, the image capturing unit 3 may be configured to capture and capture light emission other than residual heat emission during welding.

DESCRIPTION OF SYMBOLS 1 Image processing system 3 Image processing apparatus 4 Image processing part 12 Binarization means 13 XOR operation means 15 Moving sputter determination means 16 Representative center point calculation element 17 Center line formation means 18 Moving spatter storage means 19 Moving spatter removal means 20 Stationary spatter Determination element 21 Representative center point calculation means 22 Static sputter storage means 23 Static spatter removal means 24 Ellipse formation means 25 Direction change means 26 Ellipse movement means 27 Binary data reversal means 28 AND operation means 29 Representative point definition means 30 Distance determination means 31 Shape determination means M Welding member J Welding area m Bead m1 Joining end part (starting part)
m2 Junction termination part (termination part)
m3 Joining middle part (middle part)
L1 Laser beam L2 Monitoring beam θ1, θ2 Angle G Average luminance g1 Start luminance threshold g2 End luminance threshold t Time E Bead region E1 End portion E2 End portion E3 Intermediate portion e Bead region point N1 Moving sputter region N2 Stationary sputter region Z For cutting Elliptical regions Cn1, Cn1 ′, Cz Centroids r1, r2 Representative center point R1 Center line d Shortest distance A1 Solid line A2 Broken line A3 Dash-dot lines S1 to S12, S21 to S27, S31 to S35 Steps

Claims (7)

An image processing method for recognizing the shape of a bead formed in the welding region based on a plurality of image data obtained by continuously capturing and capturing a welding region during welding,
Binarizing each of the captured plurality of image data so that a sputter region candidate that is a bright region candidate corresponding to moving sputter or stationary sputter is raised;
Image data obtained by capturing the binarized image data before or next to the image data so as to extract a sputter range including a sputter region candidate that changes between the binarized image data. Performing an XOR operation on
Determining whether or not the sputter region candidate is a moving sputter region corresponding to an elongated shaped mobile sputter;
And a step of removing a sputtering area including the moving sputtering area when it is determined that the sputtering area candidate is the moving sputtering area. Removing the sputter area including the moving sputter region,
Calculating a plurality of representative center points in the moving sputter region;
By a line segment approximate fitting based on the calculated representative center point, a center line passing through the width center of the moving sputter region is calculated,
The image processing method according to claim 1, further comprising: storing a sputter range including a moving sputter region for which the center line is calculated; and removing the stored sputter range from the image data. The calculation of the representative center point is as follows:
Forming an elliptical cut elliptical area on the image;
The elliptical area for cutting is redirected so that its major axis direction is orthogonal to the longitudinal direction of the moving sputter area,
The centroid of the elliptical area for cutting and the centroid of the moving sputter area are matched,
The binarized data representing the elliptical area for cutting is converted in reverse to the binarized data representing the moving sputter area,
An AND operation process is performed between the binarized data of the converted elliptical area for cutting and the binarized data of the moving sputter area so as to separate the moving sputter area,
Calculate each centroid of the moving sputter area separated by the AND operation processing, and use the centroid of the moving sputter area before separation and each centroid of the separated moving sputter area as a representative central point. The image processing method according to claim 2, comprising defining. If it is determined that the sputter region candidate is not the moving sputter region, determining whether the sputter region candidate is a stationary sputter region corresponding to a static sputter; and
4. The method according to claim 1, further comprising: storing a sputter range including the static sputter region and removing the stored sputter range when it is determined that the sputter region candidate is the static sputter region. The image processing method as described in any one of Claims. In determining whether the sputter region candidate is the stationary sputter region,
The image according to claim 4, wherein when the shortest distance between the sputter region candidate and a bead region corresponding to the bead is equal to or longer than a predetermined length, the sputter region candidate is determined to be the stationary sputter region. Processing method. In determining whether the sputter region candidate is the stationary sputter region,
The image processing method according to claim 4, wherein when the sputter region candidate has an isotropic shape, the sputter region candidate is determined to be the stationary sputter region.   An image processing system using the image processing method according to claim 1.

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