WO2017050088A1 - Procédé et dispositif de localisation de composant électronique - Google Patents

Procédé et dispositif de localisation de composant électronique Download PDF

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Publication number
WO2017050088A1
WO2017050088A1 PCT/CN2016/096745 CN2016096745W WO2017050088A1 WO 2017050088 A1 WO2017050088 A1 WO 2017050088A1 CN 2016096745 W CN2016096745 W CN 2016096745W WO 2017050088 A1 WO2017050088 A1 WO 2017050088A1
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WIPO (PCT)
Prior art keywords
plug
electronic component
pixel
model
area
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PCT/CN2016/096745
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English (en)
Chinese (zh)
Inventor
雷延强
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广州视源电子科技股份有限公司
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Publication of WO2017050088A1 publication Critical patent/WO2017050088A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/70—Determining position or orientation of objects or cameras
    • G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
    • G06T7/74—Determining position or orientation of objects or cameras using feature-based methods involving reference images or patches
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0004—Industrial image inspection
    • G06T7/001—Industrial image inspection using an image reference approach
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10004—Still image; Photographic image

Definitions

  • the present invention relates to the field of automatic detection, and in particular, to an electronic component positioning method and apparatus.
  • Automatic optical inspection refers to the use of optical imaging to obtain the surface state of the finished product, and image processing to detect the presence of foreign matter or surface defects on the surface of the finished product.
  • automatic optical inspection is widely used for quality inspection of circuit boards.
  • the relevant detecting device automatically scans the circuit board to acquire an image, extracts a partial image of each electronic component, and uses image processing technology to determine whether the electronic components on the circuit board have defects such as mis-insertion, missing insertion or reverse insertion. Finally, the electronic components with suspected defects are displayed or marked for easy viewing and maintenance.
  • an object of the present invention is to provide an electronic component positioning method and apparatus that can quickly and accurately locate the positions of all electronic components on an image of a circuit board.
  • Embodiments of the present invention provide a method for positioning an electronic component, including the following steps:
  • Background modeling is performed on at least two plug-in front panel images obtained, and a model of each pixel of the background model is obtained, wherein the plug-in front panel image is an image of a circuit board without an electronic component inserted, each pixel point
  • the model consists of k Gaussian distribution functions, and k is an integer greater than one;
  • An adjacent candidate element pixel is connected to the plug-in rear panel image to form at least one connected region to position the electronic component.
  • the weight, mean and covariance of the model of each pixel that has been established are updated using corresponding pixel points on the front panel image of the other plug-in to obtain the updated model p(x) of each pixel.
  • the k probability values of each of the pixel points of the acquired back-plate image of the acquired plug-in are corresponding to the k-gauss distribution functions of the corresponding pixel points on the background model, specifically:
  • the connected area is a rectangle.
  • connecting adjacent candidate element pixels on the back panel image of the plug-in to form at least one connected area to locate an area where the electronic component is located includes:
  • the connected region is marked as an interference region.
  • a probability value calculation unit configured to respectively calculate k probability values of k Gaussian distribution functions of corresponding pixel points of each pixel point of the acquired plug-in back panel image, wherein the plug-in
  • the board image is an image of a circuit board into which the electronic component is inserted;
  • a comparing unit configured to compare the k probability values with a preset threshold one by one, and mark corresponding pixel points as candidates on the plug-in back panel image when any one of the probability values is smaller than the threshold Component pixel
  • a positioning unit configured to connect adjacent candidate element pixels on the back panel image of the insert to form at least one connected area to locate an area where the electronic component is located.
  • the modeling unit includes:
  • a model building unit for establishing a model p(x) for each pixel in any of the plug-in front panel images, wherein x is the gray value of the pixel, k is the number of Gaussian models, and ⁇ j , ⁇ j , C j respectively represent the weight, mean and covariance of the jth Gaussian model;
  • the updating unit is configured to update the weight, the mean and the covariance of the model of each pixel that has been established by using corresponding pixel points on the image of the front panel of the other plug-in, and obtain an updated model of each pixel.
  • the probability value calculation unit is specifically configured to separately calculate a probability of each pixel point y on the back panel image of the plug-in under k Gaussian distribution functions of corresponding pixel points of the background model. Value p j (y), where And 1 ⁇ j ⁇ k.
  • the connected area is a rectangle.
  • the positioning unit comprises:
  • An area calculation unit configured to calculate an area of the at least one connected area
  • a determining unit configured to determine whether an area of each connected area is greater than a preset area threshold
  • a marking unit configured to mark the connected area as an effective area including an electronic component to locate the electronic component when an area of the connected area is greater than the area threshold; otherwise, marking the connected area as an interference area .
  • the electronic component positioning method and device provided by the embodiment of the present invention establishes a background model by using a Gaussian mixture model, and then matches each pixel of the background model according to the back panel image of the plug-in, and obtains candidates according to the matching situation.
  • Component pixels, and by connecting adjacent candidate element pixels, position the electronic component in the back panel image of the plug-in, thereby realizing rapid and accurate positioning of the electronic component from the image of the back panel of the plug-in for subsequent Board inspection provides a reliable standard layout.
  • FIG. 1 is a flow chart of a method for positioning an electronic component according to an embodiment of the present invention.
  • FIG. 3 is a schematic diagram of a rear panel of a plug-in according to an embodiment of the present invention.
  • FIG. 4 is a schematic diagram of positioning an electronic component in an image of a back panel of the plug-in according to an embodiment of the present invention.
  • FIG. 5 is a flowchart of an electronic component positioning apparatus according to an embodiment of the present invention.
  • FIG. 6 is a schematic structural view of the modeling unit shown in FIG. 5.
  • FIG. 7 is another schematic structural view of the positioning unit shown in FIG. 5.
  • Embodiments of the present invention improve an electronic component positioning method and apparatus for positioning the position of all electronic components on a circuit board by means of automatic positioning. The details are described below separately.
  • FIG. 1 is a flowchart of a method for positioning an electronic component according to an embodiment of the present invention.
  • the electronic component positioning method can be performed by the electronic component positioning device and includes at least steps S101 to S104. among them,
  • S101 Perform background modeling on the collected at least two plug-in front panel images to obtain a model of each pixel of the background model, where the plug-in front panel image is an image of a circuit board that is not inserted into the electronic component, and each pixel
  • the model of the point consists of k Gaussian distribution functions, and k is an integer greater than one.
  • the front panel image of the plug-in is an image of a circuit board that is not inserted into an electronic component.
  • the electronic component positioning device may model the plug-in front panel image by using a Gaussian mixture model to obtain a background model of the plug-in front panel.
  • a Gaussian mixture model in order to describe the background and its possible changes, a plurality of background images are required for the background modeling. Therefore, the plug-in front panel image of the present invention is at least two.
  • the electronic component positioning device takes a plug-in front panel image, and creates a model p(x) for each pixel of the plug-in front panel image, wherein x is the pixel value of the pixel, k is the number of Gaussian models, and ⁇ j , ⁇ j , C j represent the weight, mean and covariance of the jth Gaussian model, respectively.
  • x is the pixel value of the pixel
  • k is the number of Gaussian models
  • ⁇ j , ⁇ j , C j represent the weight, mean and covariance of the jth Gaussian model, respectively.
  • the pixel value of one pixel of the plug-in front panel image is represented as a combination of k Gaussian distribution functions, and the weight, the mean and the covariance of the Gaussian model can be set according to the empirical value.
  • the weight, mean and covariance of the model of each pixel that has been established are updated by using corresponding pixel points on the image of the other plug-in front panel, and the updated model p(x) of each pixel is obtained.
  • the electronic component positioning device when a new pixel is added (ie, a new plug-in front panel image is added), the electronic component positioning device respectively separates the pixel value of the new pixel from the pixel of the corresponding background model.
  • the probability of the new pixel value falling into the corresponding Gaussian distribution is calculated simultaneously with the mean ⁇ j of the k Gaussian distributions of the points, and the matched Gaussian distribution is selected according to the judgment rule.
  • the parameters such as the weight, mean and covariance of these Gaussian distributions need to be updated according to the pixel values of the new pixel points.
  • the electronic component positioning device obtains a model of each pixel point of the background model by the above operation, wherein the model of each pixel point is composed of k Gaussian distribution functions, and k is greater than 1 An integer, and preferably, k ranges from 3 to 5.
  • the electronic component positioning device first acquires an image of the back panel of the plug-in, wherein the image of the back panel of the plug-in is an image of a circuit board into which the electronic component is inserted. Then, the electronic component locating device respectively calculates k probability values under k Gaussian distribution functions of corresponding pixel points of the pixel of the plug-in rear panel image on the background model.
  • the size of the background template and the back panel image of the plug-in are both M ⁇ N pixels.
  • the electronic component positioning device can be represented by k Gaussian distribution functions.
  • the electronic component positioning device first reads the pixel value y of the first pixel point (such as the coordinate (1, 1)) of the back panel image of the plug-in, and then the electronic component positioning device reads k Gaussian distribution functions of pixels on the corresponding background model (such as coordinates (1, 1)) Then, the electronic component positioning device substitutes the pixel values y of the back panel image of the plug-in into the k Gaussian distribution functions to obtain k probability values, wherein the j-th probability value can be expressed as
  • the electronic component positioning device traverses all the pixel points on the back panel image and the background template of the plug-in, the k probability values corresponding to each pixel point can be obtained.
  • the electronic component positioning device compares the k probability values with a preset threshold one by one, wherein when any of the probability values is less than the threshold, the corresponding pixel points are Marked as candidate element pixels, and when all k probability values are greater than the threshold, the pixel points are marked as background pixels.
  • the electronic component positioning device connects adjacent candidate component pixels after marking all the pixels on the back panel image of the plug-in.
  • at least one connected area will be formed after the communication, and the connected area is the position where the electronic component is located.
  • the shape of the connected region is a rectangle (as shown by three white squares in FIG. 4).
  • the connected area may also be a circle, a triangle, or other shapes, which is not specifically limited in the present invention.
  • pixel points that are originally background pixels are sometimes erroneously calculated as candidate element pixels due to problems such as accuracy of the algorithm or parameter errors. At this time, it may cause The position where the electronic component does not exist originally forms a connected region.
  • the electronic component positioning device can be set as follows:
  • the areas of communication having a small area are excluded, that is, the interference areas caused by calculation accuracy or error are excluded, and the connected areas are all areas including electronic components.
  • the electronic component positioning method obtained by the embodiment of the present invention obtains a background model by using a Gaussian mixture model, and then matches each pixel of the background model according to the back panel image of the plug-in to obtain a candidate component pixel. And by connecting adjacent candidate element pixels, the position of the electronic component is located in the back panel image of the plug-in, thereby realizing the position of the electronic component quickly and accurately from the image of the back panel of the plug-in, and providing for subsequent board inspection. Reliable standard layout.
  • FIG. 5 is a structural diagram of an electronic component positioning apparatus according to an embodiment of the present invention.
  • the electronic component positioning device 100 can be used to execute the electronic component positioning method described above, and at least includes a modeling unit 10, a probability value calculation unit 20, a comparison unit 30, and a positioning unit 40, wherein:
  • the modeling unit 10 is configured to perform background modeling on the collected at least two plug-in front panel images to obtain a model of each pixel point of the background model, wherein the plug-in front panel image is a circuit without an electronic component inserted
  • the image of the plate, the model of each pixel consists of k Gaussian distribution functions, and k is an integer greater than one.
  • the front panel image of the plug-in is an image of a circuit board that is not inserted into an electronic component.
  • the modeling unit 10 may first acquire at least two plug-in front panel images as background images.
  • the modeling unit 10 may model the plug-in front panel image by using a Gaussian mixture model to obtain a background model of the plug-in front panel.
  • the Gaussian mixture model requires multiple background images in order to characterize the background and its possible changes during background modeling.
  • the plug-in front panel image of the present invention is at least two.
  • the modeling unit 10 includes a model establishing unit 11 and an updating unit 12, where:
  • the model establishing unit 11 is configured to establish a model p(x) for each pixel in any of the plug-in front panel images, where x is the gray value of the pixel, a is the number of Gaussian models, and ⁇ j , ⁇ j , C j represent the weight, mean and covariance of the jth Gaussian model, respectively.
  • the model establishing unit 11 takes a plug-in front panel image and creates a model p(x) for each pixel of the plug-in front panel image, where x is the pixel value of the pixel, k is the number of Gaussian models, and ⁇ j , ⁇ j , C j represent the weight, mean and covariance of the jth Gaussian model, respectively.
  • x is the pixel value of the pixel
  • k is the number of Gaussian models
  • ⁇ j , ⁇ j , C j represent the weight, mean and covariance of the jth Gaussian model, respectively.
  • the pixel value of one pixel of the plug-in front panel image is represented as a combination of k Gaussian distribution functions, and the weight, the mean and the covariance of the Gaussian model can be set according to the empirical value.
  • the updating unit 12 is configured to update the weight, the mean and the covariance of the model of each pixel that has been established by using corresponding pixel points on the image of the front panel of the other plug-in to obtain a model of each pixel after the update. p(x).
  • the updating unit 12 separates the pixel values of the new pixel from the k-gauss distribution described above. Compared with the mean ⁇ j , the probability that the new pixel value falls into the corresponding Gaussian distribution is calculated at the same time, and the matched Gaussian distribution is selected according to the judgment rule. When there is a matching Gaussian distribution, the parameters such as the weight, mean and covariance of these Gaussian distributions need to be updated according to the pixel values of the new pixel points. For a specific calculation process, reference may be made to the parameter update principle of the general Gaussian mixture model, and the present invention will not be described herein.
  • the modeling unit 10 obtains a model of each pixel point of the background model by the above operation, wherein the model of each pixel point is composed of k Gaussian distribution functions, and k is greater than 1 An integer, and preferably, k ranges from 3 to 5.
  • the probability value calculation unit 20 is configured to respectively calculate k probability values of k Gaussian distribution functions of corresponding pixel points of each pixel point of the acquired plug-in back panel image, where
  • the back panel image of the plug-in is an image of a board into which the electronic component is inserted.
  • the probability value calculation unit 20 first acquires an image of the back panel of the plug-in, wherein the image of the back panel of the plug-in is an image of a circuit board into which the electronic component is inserted. Then, the probability value calculation unit 20 respectively calculates k probability values under k Gaussian distribution functions of corresponding pixel points of the pixel of the plug-in back panel image on the background model.
  • the size of the background template and the back panel image of the plug-in are both M ⁇ N pixels.
  • the probability value calculation unit 20 can be represented by k Gaussian distribution functions.
  • the probability value calculation unit 20 first reads the pixel value y of the first pixel point (such as the coordinate (1, 1)) of the plug-in back panel image, and then the probability value calculation unit 20 Read k Gaussian distribution functions of pixels on the corresponding background model (such as coordinates (1, 1)) Then, the probability value calculation unit 20 substitutes the pixel value y distribution of the plug-in back panel image into the k Gaussian distribution functions to obtain k probability values, wherein the j-th probability value can be expressed as
  • the probability value calculation unit 20 traverses all the pixel points on the back panel image and the background template of the plug-in, the k probability values corresponding to each pixel point can be obtained.
  • the comparing unit 30 is configured to compare the k probability values with a preset threshold one by one, and when the probability value is less than the threshold, the corresponding pixel points are displayed on the plug-in back panel image. Marked as candidate element pixels.
  • the comparing unit 30 compares the k probability values one by one with a preset threshold, wherein when any one of the probability values is less than the threshold, the comparing unit 30 Corresponding pixel points are labeled as candidate element pixels, and when all k probability values are greater than the threshold, then comparison unit 30 marks the pixel points as background pixels.
  • the positioning unit 40 may include:
  • the area calculating unit 41 is configured to calculate an area of the at least one connected area.
  • the determining unit 42 is configured to determine whether an area of each connected area is greater than a preset area threshold.
  • the marking unit 43 is configured to mark the connected area as an effective area including an electronic component when an area of the connected area is larger than the area threshold; otherwise, mark the connected area as an interference area not including an electronic component .
  • the positioning unit 40 excludes those connected areas having a small area, that is, excludes interference areas caused by calculation accuracy or error, and ensures that the connected areas are all areas including electronic components.
  • the electronic component positioning apparatus 100 obtains a background model by using a Gaussian mixture model, and then matches each pixel of the background model according to the back panel image of the plug-in to obtain a candidate component. Pixels, and by connecting adjacent candidate element pixels, position the electronic component in the back panel image of the plug-in, thereby realizing the position of the electronic component quickly and accurately from the image of the back panel of the plug-in, for subsequent board detection Provide a reliable standard layout.
  • the storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

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  • Engineering & Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Quality & Reliability (AREA)
  • Image Processing (AREA)

Abstract

L'invention concerne un procédé de localisation d'un composant électronique, dont les étapes consistent : à procéder à une modélisation en arrière-plan sur au moins deux images acquises d'une carte avant de branchement, et à acquérir un modèle de chaque point de pixel d'un modèle d'arrière-plan ; à calculer séparément k valeurs de probabilité de k fonctions de distribution gaussienne d'un point de pixel du modèle d'arrière-plan, correspondant à chaque point de pixel d'une image acquise d'une carte arrière de branchement ; à comparer les k valeurs de probabilité à une valeur de seuil prédéfinie une par une, et lorsque l'une quelconque des valeurs de probabilité est inférieure à la valeur de seuil, à marquer les points de pixels correspondants comme pixels de composants candidats sur l'image de la carte arrière de branchement ; et à communiquer les pixels de composants candidats adjacents sur l'image de la carte arrière de branchement pour former au moins une zone communiquée pour la localisation d'un composant électronique. L'invention concerne également un dispositif de localisation d'un composant électronique. La présente invention réalise une localisation rapide d'un composant électronique et accélère la vitesse de fabrication d'un format normalisé dans un processus de détection de carte de circuit imprimé.
PCT/CN2016/096745 2015-09-24 2016-08-25 Procédé et dispositif de localisation de composant électronique WO2017050088A1 (fr)

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