CN112802014A - Detection method, device and equipment for LED (light emitting diode) missing welding defects and storage medium - Google Patents

Detection method, device and equipment for LED (light emitting diode) missing welding defects and storage medium Download PDF

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CN112802014A
CN112802014A CN202110325576.5A CN202110325576A CN112802014A CN 112802014 A CN112802014 A CN 112802014A CN 202110325576 A CN202110325576 A CN 202110325576A CN 112802014 A CN112802014 A CN 112802014A
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welding
image
led
gray value
missing
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CN112802014B (en
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吴晨刚
陈健
李正大
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Gaoshi Technology Suzhou Co ltd
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Huizhou Govion Technology Co ltd
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    • 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
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/11—Region-based segmentation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/136—Segmentation; Edge detection involving thresholding
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/187—Segmentation; Edge detection involving region growing; involving region merging; involving connected component labelling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/60—Analysis of geometric attributes
    • G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G01N2021/8887—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques
    • 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
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30108—Industrial image inspection
    • G06T2207/30148—Semiconductor; IC; Wafer
    • 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
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30108—Industrial image inspection
    • G06T2207/30152—Solder

Abstract

The application relates to a method, a device, equipment and a storage medium for detecting missing welding defects of an LED. The method comprises the following steps: collecting a product image of the LED and processing the product image to identify a welding wire and a welding spot area; carrying out binarization processing on the images of the bonding wires and the welding spots to obtain a binary image of the bonding wires and the welding spots; and calculating the area of the welding line and the welding point area based on the binary diagram of the welding line and the welding point, comparing the area with a preset area threshold value, and detecting the welding missing defect of the LED according to the comparison result. The scheme provided by the application can simply, accurately and objectively realize the missing welding defect detection of the LED.

Description

Detection method, device and equipment for LED (light emitting diode) missing welding defects and storage medium
Technical Field
The application relates to the technical field of semiconductors, in particular to a method, a device, equipment and a storage medium for detecting missing welding defects of an LED.
Background
With the development of LED technology, LED lighting is becoming more and more widespread in modern technology, and LED technology is gradually taking an important position in various fields. In the production process of the LED, the yield and the quality are very important in the production and packaging processes, so the detection of the defects of the bonding wires and the quality control in the production and packaging processes are very important. The bonding wires are used for connecting the anode and the cathode of the LED semiconductor chip, and the missing welding can directly cause the disqualification of an LED product, so that the finding of a rapid and accurate detection method for the missing welding defect of the LED has important significance for improving the quality of the LED product and reducing the production cost.
The traditional method for detecting the welding wire mostly adopts manual detection, an inspector needs to detect the welding wire of a large number of products by naked eyes under a microscope for a long time, visual fatigue of the inspector is easily caused, false detection is caused, the consistency of product quality is difficult to guarantee, especially for LED products subjected to semitransparent glue dispensing, the definition of the welding wire and welding spots is reduced by the semitransparent glue dispensing, and the difficulty of manual detection is increased.
Disclosure of Invention
In order to overcome the problems in the related art, the application provides the detection method for the LED missing welding defect, and the LED missing welding detection can be objectively and accurately realized.
The application provides a method for detecting the missing welding defect of the LED, which comprises the following steps:
collecting a product image of the LED;
identifying and positioning the product image to obtain a welding line image and a welding spot image;
respectively carrying out binarization image processing on the welding line image and the welding spot image to obtain a welding line binary image and a welding spot binary image;
respectively calculating the maximum connected domain area M of the welding wire and the maximum connected domain area N of the welding spot based on the welding wire binary image and the welding spot binary image;
and judging to obtain the detection result of the missing welding defect of the LED according to the comparison result of the M and the welding wire area threshold value L and the comparison result of the N and the welding spot area threshold value W.
In one embodiment, the performing binary image processing on the bonding wire image and the pad image to obtain a bonding wire binary image and a pad binary image respectively includes:
sharpening the welding line image to obtain a sharpened image;
carrying out top cap image processing on the welding spot image to obtain a top cap image;
and respectively carrying out binarization image processing on the sharpened image and the top hat image to obtain the welding line binary image and the welding spot binary image.
In one embodiment, the performing binary image processing on the bonding wire image and the pad image to obtain a bonding wire binary image and a pad binary image respectively includes:
updating the gray value of each pixel point according to the comparison result of the gray value of each pixel point of the welding line image and the first threshold value to obtain a welding line binary image;
and updating the gray value of each pixel point according to the comparison result of the gray value of each pixel point of the welding spot image and the second threshold value to obtain the welding spot binary image.
In an embodiment, the updating the gray value of each pixel point according to the comparison result between the gray value of each pixel point of the weld line image and the first threshold to obtain the gray value updating process of one pixel point in the weld line binary image includes:
reading the gray value of the pixel point;
judging whether the gray value is greater than or equal to a first threshold value T1, if so, adjusting the gray value of the pixel point to 255; if not, adjusting the gray value of the pixel point to be 0;
the first threshold T1 ranges from 100 to 130.
In an embodiment, the updating the gray value of each pixel point according to the comparison result between the gray value of each pixel point of the solder joint image and the second threshold to obtain the gray value updating process of one pixel point in the solder joint binary image includes:
reading the gray value of the pixel point;
judging whether the gray value is greater than or equal to a second threshold value T2, if so, adjusting the gray value of the pixel point to 255; if not, adjusting the gray value of the pixel point to be 0;
the value range of the second threshold T2 is 1 to 5.
In one embodiment, the determining to obtain the detection result of the missing welding defect of the LED according to the comparison result of the M and the bonding wire area threshold L and the comparison result of the N and the welding spot area threshold W includes:
judging whether M is smaller than L and N is larger than W, if so, judging that the LED has a welding missing defect;
if not, judging that the LED is not welded in a missing mode.
This application second aspect provides a detection apparatus of LED's hourglass welding defect, includes:
the acquisition module is used for acquiring a product image of the LED and transmitting the product image to the image processing module;
the image processing module is used for identifying and segmenting the welding line and welding spot regions of the product image, carrying out binarization image processing and transmitting the obtained binary image to the calculation module;
the calculation module is used for calculating the maximum connected domain area of the welding wire and the welding spot according to the binary image of the welding wire and the welding spot and transmitting the maximum connected domain area of the welding wire and the welding spot to the defect detection module;
and the defect detection module analyzes according to the maximum communication area of the welding wire and the welding spot and outputs the detection result of the welding missing defect of the LED.
The third aspect of the present application provides an apparatus for detecting a missing solder defect of an LED, comprising:
a processor; and
a memory having executable code stored thereon, which when executed by the processor, causes the processor to perform the method as described above.
A fourth aspect of the present application provides a non-transitory machine-readable storage medium having stored thereon executable code, which when executed by a processor of an electronic device, causes the processor to perform a method as described above.
The technical scheme provided by the application can comprise the following beneficial effects:
according to the scheme, the welding line and welding spot images are subjected to binarization processing to obtain a binary image of the welding line and the welding spot, the area of the welding line and the area of the welding spot are calculated based on the binary image, and the area is compared with a preset area threshold value, so that the missing welding defect detection of the LED is realized. Through the binarization image processing, the detection area can be separated from the background, so that the interference of background pixels to the detection process is prevented, and the detection accuracy is improved. Especially for LED products with semitransparent glue dispensing, the influence of the semitransparent glue dispensing on the definition of welding wires and welding spots can be eliminated, misjudgment caused by interference is avoided, and the detection accuracy is improved. The detection of the missing welding defect can be realized by calculating the area of the welding area and comparing the area with an area threshold value, the process has a quantifiable judgment standard, the influence of the subjectivity of manual detection on the detection accuracy is eliminated, and the consistency of the product quality is ensured.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
Drawings
The foregoing and other objects, features and advantages of the application will be apparent from the following more particular descriptions of exemplary embodiments of the application, as illustrated in the accompanying drawings wherein like reference numbers generally represent like parts throughout the exemplary embodiments of the application.
FIG. 1 is a schematic flow chart illustrating a method for detecting a missing solder defect of an LED according to an embodiment of the present application;
FIG. 2 is a schematic flow chart illustrating a method for positioning a bonding wire and a bonding pad area according to an embodiment of the present disclosure;
FIG. 3 is a flowchart illustrating a method for obtaining a binary image of bonding wires and pads according to an embodiment of the present disclosure;
FIG. 4 is a schematic structural diagram of an apparatus for detecting a missing solder defect of an LED according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of an apparatus for detecting a missing solder defect of an LED according to an embodiment of the present application.
Detailed Description
Preferred embodiments of the present application will be described in more detail below with reference to the accompanying drawings. While the preferred embodiments of the present application are shown in the drawings, it should be understood that the present application may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this application and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It should be understood that although the terms "first," "second," "third," etc. may be used herein to describe various information, these information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the present application. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present application, "a plurality" means two or more unless specifically limited otherwise.
The LED product welding missing defect detection is carried out by utilizing naked eyes through a microscope, so that the condition of false detection is easily caused due to visual fatigue of an inspector and the subjectivity of judgment, the detection accuracy is influenced, and the product quality consistency is difficult to guarantee.
Example 1
In view of the above problems, embodiments of the present application provide a method for detecting an LED missing-soldering defect, which can accurately and objectively detect the LED missing-soldering defect.
The technical solutions of the embodiments of the present application are described in detail below with reference to the accompanying drawings.
Fig. 1 is a schematic flow chart of a method for detecting a missing-soldering defect of an LED according to an embodiment of the present application.
Referring to fig. 1, the method for detecting the missing solder defect of the LED includes:
101. collecting a product image of the LED;
in the embodiment of the present application, the product image of the LED may be a single product image or a whole product image. And if the collected image is a whole product image, identifying and segmenting the product image to obtain a single product image, and then executing the step 102.
It should be noted that, in the embodiment of the present application, there is no strict limitation on whether the LED is packaged and dispensed, and the technical scheme in the embodiment of the present application is applicable to both the translucent dispensing LED product and the dispensing-free LED product.
It is understood that the above description of the LED and the product image is only an example of the embodiments of the present application, and should not be taken as a limitation of the present invention.
In the embodiment of the application, an industrial CCD camera is adopted to collect the images of the LED products.
It should be noted that, in the embodiment of the present application, there is no strict limitation on the camera for performing image acquisition, that is, the above description on the industrial CCD camera is only one example of the embodiment of the present application, and does not constitute a limitation on the present invention.
102. Positioning a welding wire and a welding spot area;
specifically, the method comprises the following steps: and identifying and positioning based on the product image to obtain a welding line image and a welding spot image.
In the embodiment of the application, the product image is subjected to image recognition, and after the product image is positioned in a welding line area, the product image is segmented to obtain the welding line image; and similarly, after the product image is positioned in the welding spot area, the product image is segmented to obtain the welding spot image.
It should be noted that the above description of the identification and positioning process is only an example given in the embodiments of the present application, and should not be taken as a limitation on the present invention.
103. Acquiring a binary image of the welding wire and the welding spot;
specifically, the method comprises the following steps: and respectively carrying out binarization image processing on the welding line image and the welding spot image to obtain a welding line binary image and a welding spot binary image.
In this embodiment of the present application, the process of performing binarization image processing on the bonding wire image is as follows: and updating the gray value of each pixel point according to the comparison result of the gray value of each pixel point of the welding line image and the first threshold value to obtain the welding line binary image.
Taking a pixel point in the weld line image as an example, the specific process of updating the gray value of a pixel point in updating the gray value of each pixel point according to the comparison result between the gray value of each pixel point of the weld line image and the first threshold value includes:
reading the gray value of the pixel point;
judging whether the gray value is greater than or equal to a first threshold value T1, if so, adjusting the gray value of the pixel point to 255; if not, adjusting the gray value of the pixel point to be 0.
In the embodiment of the present application, the process of updating the gray value needs to be performed on each pixel point in the weld line image, and the weld line binary image can be obtained after all the pixel points in the weld line image complete the process of updating the gray value.
It should be understood that the above description of the process of obtaining the two-value map of the weld line is only an example in the embodiment of the present application, and should not be taken as a limitation to the present invention.
In the embodiment of the present application, the process of performing binarization image processing on the welding spot image is as follows: and updating the gray value of each pixel point according to the comparison result of the gray value of each pixel point of the welding spot image and the second threshold value to obtain the welding spot binary image.
Taking a pixel point in the solder joint image as an example, the specific process of updating the gray value of a pixel point in updating the gray value of each pixel point according to the comparison result of the gray value of each pixel point of the solder joint image and the second threshold value comprises the following steps:
reading the gray value of the pixel point;
judging whether the gray value is greater than or equal to a second threshold value T2, if so, adjusting the gray value of the pixel point to 255; if not, adjusting the gray value of the pixel point to be 0.
In the embodiment of the present application, the process of updating the gray value needs to be performed on each pixel point in the welding spot image, and the welding spot binary image can be obtained after all the pixel points in the welding spot image complete the process of updating the gray value.
In the embodiment of the present application, the value range of the first threshold T1 is 100 to 130; the value range of the second threshold T2 is 1 to 5.
It should be noted that, in the embodiment of the present application, the values of the T1 and the T2 are not strictly limited, and in an actual application process, the values may be adjusted according to actual situations and requirements, for example, in the embodiment of the present application, the value of the T1 is 119, and the value of the T2 is 3.
It is to be understood that the above description of the T1 and the T2 are only examples and should not be taken as limiting the present invention.
104. Calculating the maximum connected domain area of the welding wire and the welding spot;
specifically, the method comprises the following steps: respectively calculating the maximum connected domain area M of the welding wire and the maximum connected domain area N of the welding spot based on the welding wire binary image and the welding spot binary image;
in the embodiment of the present application, the maximum connected domains adopt an 8-adjacent adjacency relationship.
In the embodiment of the present application, the adopted connected component algorithm is not strictly limited, and in practical applications, the adopted connected component algorithm may be adjusted according to situations, for example, the Two-Pass method or the Seed-Filling Seed Filling method may be adopted to calculate the maximum connected component.
It should be understood that the above description of the maximum connected domain is only an example in the embodiment of the present application, and should not be taken as a limitation of the present invention.
In the embodiment of the present application, since the product image is identified and positioned in step 102, and the bonding wire region and the welding spot region are separated, in the obtained bonding wire image, the largest connected region is the bonding wire region, and the calculation of the largest connected region area of the bonding wire image can eliminate the pixel points with interference during binarization processing, so as to obtain the accurate bonding wire region area; similarly, the area of the welding spot region can be accurately obtained by calculating the maximum connected domain area of the welding spot image.
It should be understood that the above description of the maximum connected domain area is only an example of the embodiments of the present application, and should not be taken as a limitation on the present invention.
105. And judging a threshold value according to the maximum communication area of the welding wire and the welding spot to obtain a detection result.
Specifically, the method comprises the following steps: and judging to obtain the detection result of the missing welding defect of the LED according to the comparison result of the M and the welding wire area threshold value L and the comparison result of the N and the welding spot area threshold value W.
In this embodiment of the present application, the threshold determination process specifically includes: judging whether M is smaller than L and N is larger than W, if so, judging that the LED has a welding missing defect; if not, judging that the LED is not welded in a missing mode.
In the embodiment of the application, if M is smaller than L and N is larger than W, it indicates that the area of the bonding wire region detected by the image is smaller than the preset bonding wire area, and the pale white region formed by the non-welded part of the welding point is larger than the preset welding point area threshold, which indicates that the welding region of the welding line fails to meet the requirement and the pale white region formed by the non-welded part of the welding point is too large, so that it can be determined that the corresponding LED product has the quality defect of missing welding.
In the embodiment of the present application, the value of the bonding wire area threshold L ranges from 4 to 16, and the value of the pad area threshold W ranges from 10 to 50.
It should be noted that the above description of the bonding wire area threshold and the pad area threshold is only an example, and in an actual application process, values of the bonding wire area threshold and the pad area threshold may be adjusted according to a production condition, for example, in this embodiment, a value of the bonding wire area threshold L is 9, and a value of the pad area threshold W is 30.
It is to be understood that the above description of the wire area threshold and the pad area threshold should not be construed as limiting the invention.
According to the scheme, the welding line and welding spot images are subjected to binarization processing to obtain a binary image of the welding line and the welding spot, the area of the welding line and the area of the welding spot are calculated based on the binary image, and the area is compared with a preset area threshold value, so that the missing welding defect detection of the LED is realized. Through the binarization image processing, the detection area can be separated from the background, so that the interference of background pixels to the detection process is prevented, and the detection accuracy is improved. Especially for LED products with semitransparent glue dispensing, the influence of the semitransparent glue dispensing on the definition of welding wires and welding spots can be eliminated, misjudgment caused by interference is avoided, and the detection accuracy is improved. The detection of the missing welding defect can be realized by calculating the area of the welding area and comparing the area with an area threshold value, the process has a quantifiable judgment standard, the influence of the subjectivity of manual detection on the detection accuracy is eliminated, and the consistency of the product quality is ensured.
Example 2
The present embodiment is designed for step 102 in embodiment 1 described above.
Fig. 2 is a flowchart illustrating a method for positioning a bonding wire and a pad area according to an embodiment of the present disclosure.
Referring to fig. 2 in detail, the method for positioning the bonding wire and the bonding pad area includes:
201. calling a welding wire template and a welding spot template from a standard template library;
in the embodiment of the application, the standard template library may include LED product templates of various models, where the LED product templates are positioning data obtained by processing in advance according to LED product samples.
It should be noted that the above description of the standard template library is only an example in the embodiment of the present application, and should not be taken as a limitation of the present invention.
202. And performing template matching on the product image based on the welding wire template and the welding spot template respectively to obtain the welding wire image and the welding spot image.
In the embodiment of the present application, an algorithm used for the template matching is not strictly limited, and different algorithms can be used according to actual production conditions to complete the template matching process, so as to obtain the bonding wire image and the solder joint image. For example, in an actual production process, a correlation method or an error method may be used for template matching.
It should be understood that the above description of template matching is only an example of the embodiments of the present application, and should not be taken as a limitation on the present invention.
According to the embodiment of the application, the product image is processed by utilizing template matching, and the welding line image and the welding spot image are respectively separated, so that the separation detection of the welding line and the welding spot area is realized, the detection precision is improved, and the calculation amount for processing a single image is reduced.
Example 3
The present embodiment is designed for step 103 in the above embodiment 1.
Fig. 3 is a flowchart illustrating a method for obtaining a binary diagram of bonding wires and bonding pads according to an embodiment of the present application.
With particular reference to fig. 3, the method for obtaining a binary image of bonding wires and pads comprises:
301. sharpening the welding line image to obtain a sharpened image;
in the embodiment of the present application, the purpose of sharpening the bonding wire image is to highlight the features of the bonding wire, so that the bonding wire is separated from the background when the binarization image processing is performed subsequently.
It should be noted that, in the embodiment of the present application, the adopted sharpening method is not strictly limited, and in an actual application process, any image sharpening algorithm may be adopted to sharpen the weld line image, for example, a high-pass filtering method or a spatial differentiation method.
It should be understood that the above description of the sharpening process is only an example in the embodiment of the present application, and should not be taken as a limitation of the present invention.
302. Carrying out top cap image processing on the welding spot image to obtain a top cap image;
in the embodiment of the present application, the process of performing top hat image processing on the welding spot image is as follows: performing an opening operation on the welding spot image to obtain an opening operation image; and subtracting the welding spot image and the opening operation image to obtain the top cap image.
In the embodiment of the application, the top hat image processing can make the light white area in the welding spot image stand out, so that the contrast of the welding spot and the background is improved.
It should be noted that, in the practical application process, other image processing methods may be adopted to process the weld image according to the practical requirements, for example, the maximum inter-class variance method.
It should be understood that the above description of the process of processing the image of the welding spot is only an example of the embodiment of the present application, and should not be construed as limiting the present invention.
It should be noted that, in the embodiment of the present application, there is no strict timing limitation on step 301 and step 302, that is, step 302 may be executed before step 301 or in parallel with step 301.
It should be understood that the execution sequence of the steps 301 and 302 is only an example in the embodiment of the present application, and should not be taken as a limitation to the present invention.
303. And obtaining a binary image of the welding line and the welding point according to the sharpened image and the top cap image.
Specifically, the method comprises the following steps: and respectively carrying out binarization image processing on the sharpened image and the top hat image to obtain the welding line binary image and the welding spot binary image.
The above-mentioned binary image processing procedure has been described in step 103 of embodiment 1, and is not described herein again.
In the embodiment of the application, the welding line image is subjected to sharpening image processing, so that the contrast between a welding line area and a background in the welding line image can be improved, the accuracy of subsequent binarization image processing is improved, the obtained welding line binary image can accurately represent a real welding line, and the reliability of welding line missing welding detection according to the welding line binary image is ensured; similarly, the top cap image processing is carried out on the welding spot image, so that the contrast between a welding spot area and the background in the welding spot image can be improved, the reliability of the representation of the welding spot binary image is improved, and the accuracy of welding spot missing welding detection is improved.
Example 4
Corresponding to the embodiment of the application function realization method, the application also provides a device for detecting the missing welding defect of the LED and a corresponding embodiment.
Fig. 4 is a schematic structural diagram of an apparatus for detecting an LED missing-soldering defect according to an embodiment of the present application.
With particular reference to fig. 4, the device for detecting the missing solder defect of the LED comprises:
the acquisition module 401 is used for acquiring a product image of the LED and transmitting the product image to the image processing module;
the image processing module 402 is used for identifying and segmenting the welding line and welding spot regions of the product image, performing binarization image processing and transmitting the obtained binary image to the calculation module;
the calculation module 403 calculates the maximum connected domain area of the bonding wire and the welding point according to the binary image of the bonding wire and the welding point, and transmits the maximum connected domain area of the bonding wire and the welding point to the defect detection module;
and the defect detection module 404 analyzes the maximum connected domain area of the bonding wire and the welding point and outputs the detection result of the missing welding defect of the LED.
Example 5
Corresponding to the embodiment of the application function realization method, the application also provides detection equipment for the missing welding defect of the LED and a corresponding embodiment.
Fig. 5 is a schematic structural diagram of an apparatus for detecting a missing solder defect of an LED according to an embodiment of the present application.
Referring to fig. 5, the apparatus 500 for detecting the missing solder defect of the LED includes:
a processor 501; and
a memory 502 having executable code stored thereon which, when executed by the processor, causes the processor to perform the method as described above.
Example 6
Corresponding to the foregoing application function implementation method embodiments, the present application further provides a non-transitory machine-readable storage medium and corresponding embodiments.
The non-transitory machine-readable storage medium has stored thereon executable code that, when executed by a processor of an electronic device, causes the processor to perform the method as described above.
With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
The Processor 501 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 502 may include various types of storage units, such as system memory, Read Only Memory (ROM), and permanent storage. Wherein the ROM may store static data or instructions for the processor 501 or other modules of the computer. The persistent storage device may be a read-write storage device. The persistent storage may be a non-volatile storage device that does not lose stored instructions and data even after the computer is powered off. In some embodiments, the persistent storage device employs a mass storage device (e.g., magnetic or optical disk, flash memory) as the persistent storage device. In other embodiments, the permanent storage may be a removable storage device (e.g., floppy disk, optical drive). The system memory may be a read-write memory device or a volatile read-write memory device, such as a dynamic random access memory. The system memory may store instructions and data that some or all of the processors require at runtime. In addition, the memory 502 may include any combination of computer-readable storage media, including various types of semiconductor memory chips (DRAM, SRAM, SDRAM, flash memory, programmable read-only memory), magnetic and/or optical disks, as well. In some embodiments, memory 502 may include a removable storage device that is readable and/or writable, such as a Compact Disc (CD), a digital versatile disc read only (e.g., DVD-ROM, dual layer DVD-ROM), a Blu-ray disc read only, an ultra-dense disc, a flash memory card (e.g., SD card, min SD card, Micro-SD card, etc.), a magnetic floppy disk, or the like. Computer-readable storage media do not contain carrier waves or transitory electronic signals transmitted by wireless or wired means.
The memory 502 has stored thereon executable code, which when processed by the processor 501, may cause the processor 501 to perform some or all of the methods described above.
The aspects of the present application have been described in detail hereinabove with reference to the accompanying drawings. In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments. Those skilled in the art should also appreciate that the acts and modules referred to in the specification are not necessarily required in the present application. In addition, it can be understood that the steps in the method of the embodiment of the present application may be sequentially adjusted, combined, and deleted according to actual needs, and the modules in the device of the embodiment of the present application may be combined, divided, and deleted according to actual needs.
Furthermore, the method according to the present application may also be implemented as a computer program or computer program product comprising computer program code instructions for performing some or all of the steps of the above-described method of the present application.
Alternatively, the present application may also be embodied as a non-transitory machine-readable storage medium (or computer-readable storage medium, or machine-readable storage medium) having stored thereon executable code (or a computer program, or computer instruction code) which, when executed by a processor of an electronic device (or electronic device, server, etc.), causes the processor to perform part or all of the various steps of the above-described method according to the present application.
Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the applications disclosed herein may be implemented as electronic hardware, computer software, or combinations of both.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems and methods according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Having described embodiments of the present application, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.

Claims (10)

1. A detection method for LED missing welding defects is characterized by comprising the following steps:
collecting a product image of the LED;
identifying and positioning the product image to obtain a welding line image and a welding spot image;
respectively carrying out binarization image processing on the welding line image and the welding spot image to obtain a welding line binary image and a welding spot binary image;
respectively calculating the maximum connected domain area M of the welding wire and the maximum connected domain area N of the welding spot based on the welding wire binary image and the welding spot binary image;
and judging to obtain the detection result of the missing welding defect of the LED according to the comparison result of the M and the welding wire area threshold value L and the comparison result of the N and the welding spot area threshold value W.
2. The method for detecting the missing welding defect of the LED according to claim 1, wherein the step of respectively performing binarization image processing on the bonding wire image and the welding spot image to obtain a bonding wire binary image and a welding spot binary image comprises the following steps:
sharpening the welding line image to obtain a sharpened image;
carrying out top cap image processing on the welding spot image to obtain a top cap image;
and respectively carrying out binarization image processing on the sharpened image and the top hat image to obtain the welding line binary image and the welding spot binary image.
3. The method for detecting the missing welding defect of the LED according to claim 1, wherein the step of respectively performing binarization image processing on the bonding wire image and the welding spot image to obtain a bonding wire binary image and a welding spot binary image comprises the following steps:
updating the gray value of each pixel point according to the comparison result of the gray value of each pixel point of the welding line image and the first threshold value to obtain a welding line binary image;
and updating the gray value of each pixel point according to the comparison result of the gray value of each pixel point of the welding spot image and the second threshold value to obtain the welding spot binary image.
4. The method for detecting the missing solder defect of the LED of claim 3, wherein the step of updating the gray value of each pixel according to the comparison result between the gray value of each pixel in the bonding wire image and the first threshold to obtain the gray value of one pixel in the bonding wire binary image comprises:
reading the gray value of the pixel point;
judging whether the gray value is greater than or equal to a first threshold value T1, if so, adjusting the gray value of the pixel point to 255; if not, adjusting the gray value of the pixel point to be 0;
the first threshold T1 ranges from 100 to 130.
5. The method for detecting the LED missing solder defect of claim 3, wherein the step of updating the gray value of each pixel point according to the comparison result of the gray value of each pixel point of the solder joint image and the second threshold value to obtain the gray value of one pixel point in the solder joint binary image comprises the following steps:
reading the gray value of the pixel point;
judging whether the gray value is greater than or equal to a second threshold value T2, if so, adjusting the gray value of the pixel point to 255; if not, adjusting the gray value of the pixel point to be 0;
the value range of the second threshold T2 is 1 to 5.
6. The method for detecting the LED missing welding defect according to claim 1, wherein the step of judging to obtain the LED missing welding defect detection result according to the comparison result of the M and the welding wire area threshold value L and the comparison result of the N and the welding spot area threshold value W comprises the following steps:
judging whether M is smaller than L and N is larger than W, if so, judging that the LED has a welding missing defect;
if not, judging that the LED is not welded in a missing mode.
7. The method for detecting the missing welding defect of the LED according to claim 1, wherein the identifying and positioning the product image to obtain the welding line image and the welding spot image comprises:
calling a welding wire template and a welding spot template from a standard template library;
and performing template matching on the product image based on the welding wire template and the welding spot template respectively to obtain the welding wire image and the welding spot image.
8. The utility model provides a detection apparatus for LED's hourglass welds defect which characterized in that includes:
the acquisition module is used for acquiring a product image of the LED and transmitting the product image to the image processing module;
the image processing module is used for identifying and segmenting the welding line and welding spot regions of the product image, carrying out binarization image processing and transmitting the obtained binary image to the calculation module;
the calculation module is used for calculating the maximum connected domain area of the welding wire and the welding spot according to the binary image of the welding wire and the welding spot and transmitting the maximum connected domain area of the welding wire and the welding spot to the defect detection module;
and the defect detection module analyzes according to the maximum communication area of the welding wire and the welding spot and outputs the detection result of the welding missing defect of the LED.
9. The utility model provides a detection equipment of LED's hourglass welding defect which characterized in that includes:
a processor; and
a memory having executable code stored thereon, which when executed by the processor, causes the processor to perform the method of any one of claims 1-7.
10. A non-transitory machine-readable storage medium having stored thereon executable code, which when executed by a processor of an electronic device, causes the processor to perform the method of any one of claims 1-7.
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Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104020222A (en) * 2014-06-18 2014-09-03 长春光华微电子设备工程中心有限公司 Welding quality detecting system of full-automatic ultrasonic aluminium wire press welder
CN104867145A (en) * 2015-05-15 2015-08-26 广东工业大学 IC element solder joint defect detection method based on VIBE model
CN104867144A (en) * 2015-05-15 2015-08-26 广东工业大学 IC element solder joint defect detection method based on Gaussian mixture model
CN107610085A (en) * 2016-07-11 2018-01-19 富强 A kind of welding point defect detecting system based on computer vision
CN107610111A (en) * 2017-09-12 2018-01-19 武汉大学 A kind of weld point image detection method based on deep learning
CN109001224A (en) * 2017-06-07 2018-12-14 宁德时代新能源科技股份有限公司 Welding seam detection method and detection device
CN109859181A (en) * 2019-01-29 2019-06-07 桂林电子科技大学 A kind of PCB welding point defect detection method
CN110930376A (en) * 2019-11-13 2020-03-27 上海交通大学 Method and system for detecting welding spot burrs based on machine vision

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104020222A (en) * 2014-06-18 2014-09-03 长春光华微电子设备工程中心有限公司 Welding quality detecting system of full-automatic ultrasonic aluminium wire press welder
CN104867145A (en) * 2015-05-15 2015-08-26 广东工业大学 IC element solder joint defect detection method based on VIBE model
CN104867144A (en) * 2015-05-15 2015-08-26 广东工业大学 IC element solder joint defect detection method based on Gaussian mixture model
CN107610085A (en) * 2016-07-11 2018-01-19 富强 A kind of welding point defect detecting system based on computer vision
CN109001224A (en) * 2017-06-07 2018-12-14 宁德时代新能源科技股份有限公司 Welding seam detection method and detection device
CN107610111A (en) * 2017-09-12 2018-01-19 武汉大学 A kind of weld point image detection method based on deep learning
CN109859181A (en) * 2019-01-29 2019-06-07 桂林电子科技大学 A kind of PCB welding point defect detection method
CN110930376A (en) * 2019-11-13 2020-03-27 上海交通大学 Method and system for detecting welding spot burrs based on machine vision

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
孙飞: "基于计算机视觉的PCB板焊点缺陷检测及分类", 《中国优秀硕士学位论文全文数据库信息科技辑》 *

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