CN111784648A - Soft material fitting precision detection method, device, equipment and storage medium - Google Patents
Soft material fitting precision detection method, device, equipment and storage medium Download PDFInfo
- Publication number
- CN111784648A CN111784648A CN202010567207.2A CN202010567207A CN111784648A CN 111784648 A CN111784648 A CN 111784648A CN 202010567207 A CN202010567207 A CN 202010567207A CN 111784648 A CN111784648 A CN 111784648A
- Authority
- CN
- China
- Prior art keywords
- soft material
- substrate reference
- extraction result
- fpc
- image
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 239000007779 soft material Substances 0.000 title claims abstract description 226
- 238000001514 detection method Methods 0.000 title claims abstract description 112
- 238000003860 storage Methods 0.000 title claims abstract description 16
- 239000000758 substrate Substances 0.000 claims abstract description 153
- 238000000605 extraction Methods 0.000 claims abstract description 128
- 238000000034 method Methods 0.000 claims abstract description 34
- 238000004590 computer program Methods 0.000 claims description 23
- PXFBZOLANLWPMH-UHFFFAOYSA-N 16-Epiaffinine Natural products C1C(C2=CC=CC=C2N2)=C2C(=O)CC2C(=CC)CN(C)C1C2CO PXFBZOLANLWPMH-UHFFFAOYSA-N 0.000 claims description 7
- 230000009466 transformation Effects 0.000 claims description 7
- 238000004364 calculation method Methods 0.000 claims description 6
- 238000010030 laminating Methods 0.000 claims description 6
- 238000007781 pre-processing Methods 0.000 claims description 6
- 238000010586 diagram Methods 0.000 description 7
- 230000006870 function Effects 0.000 description 7
- 230000008569 process Effects 0.000 description 5
- 230000006872 improvement Effects 0.000 description 4
- 238000004519 manufacturing process Methods 0.000 description 4
- 239000000463 material Substances 0.000 description 3
- 238000004891 communication Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000009499 grossing Methods 0.000 description 2
- 230000009471 action Effects 0.000 description 1
- 239000003086 colorant Substances 0.000 description 1
- 238000012790 confirmation Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000006073 displacement reaction Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 230000008676 import Effects 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000003647 oxidation Effects 0.000 description 1
- 238000007254 oxidation reaction Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
Images
Classifications
-
- 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
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/002—Measuring arrangements characterised by the use of optical techniques for measuring two or more coordinates
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/13—Edge detection
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
-
- 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
-
- 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
- G06T2207/30141—Printed circuit board [PCB]
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Theoretical Computer Science (AREA)
- Business, Economics & Management (AREA)
- Emergency Management (AREA)
- Quality & Reliability (AREA)
- Image Processing (AREA)
- Length Measuring Devices By Optical Means (AREA)
Abstract
The invention discloses a method, a device, equipment and a storage medium for detecting the fitting precision of a soft material, wherein the method comprises the following steps: collecting an image of the FPC to be detected; carrying out soft material edge extraction and substrate reference diagonal line extraction on the image of the FPC to be detected to obtain a soft material edge extraction result and a substrate reference diagonal line extraction result; determining position deviation values between four sides of the soft material and the corresponding substrate reference diagonal lines according to the soft material edge extraction result and the substrate reference diagonal line extraction result; and when the position deviation value between any one edge of the soft material and the substrate reference counterpoint line of the soft material meets the preset alarm condition, outputting alarm information. The invention can effectively solve the problems of low detection efficiency and low detection accuracy rate caused by adopting manual detection in the prior art.
Description
Technical Field
The invention relates to the technical field of FPC (flexible printed circuit) production, in particular to a method, a device, equipment and a storage medium for detecting the fitting precision of a soft material.
Background
The Flexible material, also called a coverlay, plays an insulating role and can also protect the lines on the FPC (Flexible Printed Circuit board) from oxidation and damage.
In the production process of the FPC, the fitting precision of the soft material has very important influence on the product quality of the FPC. At present, the detection of the fitting precision of the soft material is generally carried out manually by adopting a two-dimensional image measuring instrument. However, in the process of implementing the invention, the inventor finds that the existing soft material fitting precision detection method has the problems of low detection efficiency, low detection accuracy and the like due to the influence of human factors and external interference, and can not meet the production requirement.
Disclosure of Invention
The embodiment of the invention provides a method, a device, equipment and a storage medium for detecting the fitting precision of a soft material, which can effectively solve the problems of low detection efficiency and low detection accuracy caused by manual detection in the prior art.
An embodiment of the present invention provides a method for detecting a fitting accuracy of a soft material, including:
collecting an image of the FPC to be detected;
carrying out soft material edge extraction and substrate reference diagonal line extraction on the image of the FPC to be detected to obtain a soft material edge extraction result and a substrate reference diagonal line extraction result;
determining position deviation values between four sides of the soft material and the corresponding substrate reference diagonal lines according to the soft material edge extraction result and the substrate reference diagonal line extraction result;
and when the position deviation value between any one edge of the soft material and the substrate reference counterpoint line of the soft material meets the preset alarm condition, outputting alarm information.
As an improvement of the above scheme, the soft material edge extraction and the substrate reference pair bit line extraction are performed on the image of the FPC to be detected to obtain a soft material edge extraction result and a substrate reference pair bit line extraction result, and the method specifically includes:
creating a template for positioning, and extracting the central position of the template for positioning;
respectively creating a detection area corresponding to each edge of the soft material aiming at four edges of the soft material covered on the FPC to be detected, and extracting the central position of the detection area of each edge of the soft material;
aiming at substrate reference diagonal lines of four sides of the soft material on a substrate, respectively creating a detection area corresponding to each substrate reference diagonal line, and extracting the central position of the detection area of each substrate reference diagonal line;
template matching is carried out on the image of the FPC to be detected, and the central position of a matching area matched with the template for positioning is obtained;
performing affine transformation on the central position of the detection area of each side of the soft material and the central position of the detection area of each substrate reference pair bit line according to the central position of the template for positioning and the central position of the matching area to obtain the current central position of the detection area of each side of the soft material and the current central position of the detection area of each substrate reference pair bit line;
according to the current central position of the detection area of each edge of the soft material, performing edge extraction on the image of the FPC to be detected in the detection area of each edge of the soft material to obtain a soft material edge extraction result;
and according to the current central position of the detection area of each substrate reference counterpoint line, performing edge extraction on the image of the FPC to be detected in the detection area of each substrate reference counterpoint line to obtain a substrate reference counterpoint line extraction result.
As an improvement of the above scheme, the template matching of the image of the FPC to be detected to obtain the center position of the matching area matched with the template for positioning specifically includes:
preprocessing the image of the FPC to be detected to obtain a preprocessed image of the FPC to be detected;
and carrying out template matching on the preprocessed FPC to be detected image to obtain the central position of a matching area matched with the template for positioning.
As an improvement of the above solution, the determining, according to the soft material edge extraction result and the substrate reference pair line extraction result, a position deviation value between four edges of the soft material and the corresponding substrate reference pair line includes:
judging whether the soft material edge extraction result contains position coordinates of four edges of the soft material;
when the position coordinates of four sides of the soft material are judged to be contained in the soft material edge extraction result, judging whether the position coordinates of the substrate alignment reference line corresponding to the side are contained in the substrate reference alignment line extraction result or not for each side of the soft material, if so, calculating the position deviation value between the side and the corresponding substrate reference alignment line according to the position coordinates of the side and the position coordinates of the corresponding substrate alignment reference line, and if not, setting the position deviation value between the side and the corresponding substrate reference alignment line as a preset deviation value;
and when the position coordinates of the four sides of the soft material are not included in the soft material edge extraction result, setting the position deviation values between the four sides of the soft material and the substrate reference diagonal line as preset deviation values.
As an improvement of the above scheme, the preset alarm condition is greater than a first preset offset threshold or less than a second preset offset threshold; the first preset offset threshold is greater than the second preset offset threshold, and the preset offset value is smaller than the second preset offset threshold.
As a refinement of the above, the position offset value includes a shortest distance and a slope difference absolute value.
Another embodiment of the present invention provides a device for detecting the fitting accuracy of a soft material, including:
the image acquisition module is used for acquiring an image of the FPC to be detected;
the edge extraction module is used for carrying out soft material edge extraction and substrate reference bit line extraction on the image of the FPC to be detected to obtain a soft material edge extraction result and a substrate reference bit line extraction result;
the offset calculation module is used for determining position offset values between the four sides of the soft material and the corresponding substrate reference pair line according to the soft material edge extraction result and the substrate reference pair line extraction result;
and the precision detection module is used for outputting alarm information when the position deviation value between any one edge of the soft material and the substrate reference counterpoint line thereof meets the preset alarm condition.
Another embodiment of the present invention provides a device for detecting fitting accuracy of a soft material, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, where the processor implements the method for detecting fitting accuracy of a soft material according to any one of the above items when executing the computer program.
Another embodiment of the present invention provides a computer-readable storage medium, where the computer-readable storage medium includes a stored computer program, where when the computer program runs, a device where the computer-readable storage medium is located is controlled to execute the method for detecting the fitting accuracy of a soft material according to any one of the above items.
Compared with the prior art, the method, the device, the equipment and the storage medium for detecting the bonding precision of the soft material disclosed by the embodiment of the invention, by collecting the image of the FPC to be detected, and then carrying out soft material edge extraction and substrate reference bit line extraction on the image of the FPC to be detected, the soft material edge extraction result and the substrate reference bit line extraction result are obtained, then determining the position deviation values between the four sides of the soft material and the corresponding substrate reference pair bit lines according to the soft material edge extraction result and the substrate reference pair bit line extraction result, then when the position deviation value between any one edge of the soft material and the substrate reference diagonal line of the soft material meets the preset alarm condition, alarm information is output, the automatic detection of the fitting precision of the soft materials is realized, and the problems of low detection efficiency and low detection accuracy rate caused by manual detection in the prior art can be effectively solved.
Drawings
Fig. 1 is a schematic flow chart of a method for detecting the fitting accuracy of a soft material according to an embodiment of the present invention.
Fig. 2 is a schematic structural diagram of a laminator according to an embodiment of the present invention.
Fig. 3 is a schematic structural diagram of a head of a laminator according to an embodiment of the present invention.
Fig. 4 is a flowchart illustrating the operation of the laminator according to an embodiment of the present invention.
Fig. 5 is a schematic structural diagram of a device for detecting the fitting accuracy of a soft material according to an embodiment of the present invention.
Fig. 6 is a schematic structural diagram of a device for detecting the fitting accuracy of a soft material according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a schematic flow chart of a method for detecting the fitting accuracy of a soft material according to an embodiment of the present invention.
The method for detecting the fitting precision of the soft material provided by the embodiment of the invention comprises the following steps:
s11, collecting an image of the FPC to be detected;
s12, carrying out soft material edge extraction and substrate reference diagonal line extraction on the image of the FPC to be detected to obtain a soft material edge extraction result and a substrate reference diagonal line extraction result;
s13, determining position deviation values between four sides of the soft material and the corresponding substrate reference alignment lines according to the soft material edge extraction result and the substrate reference alignment line extraction result;
and S14, outputting alarm information when the position deviation value between any one edge of the soft material and the substrate reference counterpoint line thereof meets the preset alarm condition.
It should be noted that, in step S11, the definition of the image of the FPC to be inspected depends on the inspected object and the light source under the condition that the camera is not changed, and the light source needs to be finely adjusted when the imaging effect is not ideal because the inspected FPC substrate and the attached soft material have some differences at different positions. The light source is adjusted mainly from angle of lighting, the intensity of light and the colour of light, and the adjustment is carried out in three aspect, under the fixed condition of installation angle of image acquisition device, mainly adjusts in real time the colour and the intensity of light and obtains sharp image, and wherein, the light source can adopt compact RGB three-colour annular light, detects under general the condition and adopts the blue light, and exposure time selects 200 milliseconds (camera exposure time sets up to 2000 microseconds).
It should be noted that the shape of the soft material and the substrate is rectangular, the size of the soft material is generally smaller than that of the substrate, and the color of the substrate is greatly different between the colors of the soft material, so that the soft material region and the substrate region can be well distinguished according to the color. The substrate reference alignment line comprises an upper alignment line, a lower alignment line, a left alignment line and a right alignment line which are respectively arranged on the edge of the substrate, and the upper alignment line, the lower alignment line, the left alignment line and the right alignment line are respectively used for upper alignment, lower alignment, left alignment and right alignment of the soft material. If the FPC to be detected is normally attached with the soft material, namely the FPC is not attached in a missing way and the deviation of the attaching position is small, the position coordinates of the four sides of the soft material are included in the soft material edge extraction result, and the position coordinates of the substrate reference counterpoint line corresponding to the four sides of the soft material are included in the substrate reference counterpoint line extraction result; if the soft material is not attached to the FPC to be detected due to the missing attachment, extracting the four edges of the soft material through the edge extraction of the soft material, wherein the position coordinates of the four edges of the soft material are not included in the soft material edge extraction result; if the substrate reference pair bit line on the substrate is covered by the soft material due to the large deviation of the bonding position, only the substrate reference pair bit line which is not covered by the soft material can be extracted through the substrate reference pair bit line, but the substrate reference pair bit line which is covered by the soft material cannot be extracted, and at this time, the substrate reference pair bit line extraction result only includes the position coordinates of the substrate reference pair bit line which is not covered by the soft material.
It should be noted that the fitting accuracy of the soft material on the FPC is represented by the distance and the rotation angle between the diagonal line on the substrate and the edge of the soft material, and the position deviation value can well reflect the distance and the rotation angle between the two lines, so the embodiment of the present invention determines the fitting accuracy of the soft material by calculating the position deviation values of the four sides of the soft material and the corresponding substrate reference diagonal lines. Optionally, the position offset value includes a shortest distance and a slope difference absolute value.
The preset alarm condition and the alarm information can be set according to actual needs, and are not limited herein. For example, the preset alarm condition may be set to be that the position deviation value is greater than a certain threshold value, and the alarm information is set to be that "the position deviation exceeds the set range", and when it is determined that the position deviation value between any one side of the soft material and the substrate reference alignment line is greater than the certain threshold value, the alarm information is output, so as to prompt confirmation of the bonding condition.
In an optional embodiment, after determining the position deviation values between the four sides of the soft material and the corresponding substrate reference alignment lines, the bonding position compensation amount of the bonding machine may be correspondingly adjusted according to the position deviation values between the four sides of the soft material and the corresponding substrate reference alignment lines, so as to control the bonding position of the bonding machine and improve the bonding quality.
The method for detecting the attaching precision of the soft material comprises the steps of acquiring an image of an FPC to be detected, extracting the edge of the soft material and extracting the substrate reference alignment line of the image of the FPC to be detected to obtain the soft material edge extraction result and the substrate reference alignment line extraction result, then determining the position deviation values between the four sides of the soft material and the corresponding substrate reference pair bit lines according to the soft material edge extraction result and the substrate reference pair bit line extraction result, then when the position deviation value between any one edge of the soft material and the substrate reference diagonal line of the soft material meets the preset alarm condition, alarm information is output, the automatic detection of the fitting precision of the soft materials is realized, and the problems of low detection efficiency and low detection accuracy rate caused by manual detection in the prior art can be effectively solved.
As one optional embodiment, the step S12 specifically includes:
s121, creating a template for positioning, and extracting the central position of the template for positioning;
s122, respectively creating a detection area corresponding to each edge of the soft material aiming at four edges of the soft material covered on the FPC to be detected, and extracting the central position of the detection area of each edge of the soft material;
s123, aiming at substrate reference alignment lines on the substrate of the four sides of the soft material, respectively creating a detection area corresponding to each substrate reference alignment line, and extracting the central position of the detection area of each substrate reference alignment line;
s124, template matching is carried out on the image of the FPC to be detected, and the central position of a matching area matched with the template for positioning is obtained;
s125, performing affine transformation on the central position of the detection area of each side of the soft material and the central position of the detection area of each substrate reference pair bit line according to the central position of the template for positioning and the central position of the matching area to obtain the current central position of the detection area of each side of the soft material and the current central position of the detection area of each substrate reference pair bit line;
s126, according to the current central position of the detection area of each edge of the soft material, performing edge extraction on the image of the FPC to be detected in the detection area of each edge of the soft material to obtain a soft material edge extraction result;
and S127, according to the current central position of the detection area of each substrate reference counterpoint line, performing edge extraction on the image of the FPC to be detected in the detection area of each substrate reference counterpoint line to obtain a substrate reference counterpoint line extraction result.
In addition, step S121 may specifically be: generating a detection point coordinate; moving to the position of a first detection point, and collecting an image required by building a template; and carrying out contour extraction on the image required by establishing the template to obtain the template for positioning, and recording the central position of the template for positioning. The method comprises the steps of generating detection point coordinates by adopting two optional modes, wherein the detection point coordinates are respectively imported and taught for a CAD file, the CAD file import supports two formats (DXF and DWG), the GBR is converted into DXF by providing a GBR-DXF function, and if the GBR-format file needs to be imported, the GBR can be converted into DXF in system software, and then the converted DXF file is imported. After the coordinates of the detection points are obtained, the actual positions of the detection points may deviate from the coordinates in the file, so that multiple position searching is needed during detection. As can be appreciated, the templates used for positioning specifically include: contour line, center of contour line, angle of contour line. The purpose of establishing the positioning template is to determine the position of the soft material and the rotation angle thereof, and determine the position in the image for the later caliper and the soft material area.
In step S125, the affine transformation is performed because the center position and the direction of the set detection region are relative values with reference to the center position and the angle of the template for positioning. When the detection image acquired when the edge needs to be detected is different from the image acquired when the template is created, if the absolute coordinates of the detection area in the image are used, the phenomenon that the detection cannot be detected occurs, and through affine transformation, the relative coordinates of the central position of the detection area relative to the central position and the angle of the template for positioning are unchanged no matter how the image changes.
In an embodiment, in step S126, specifically, an edge of the image of the FPC to be detected is extracted by a caliper tool in the detection area of each edge of the soft material, so as to set a caliper on the extracted edge of the soft material, and in step S127, an edge of the image of the FPC to be detected is extracted by a caliper tool in the detection area of each substrate reference alignment line, so as to set a caliper on the extracted substrate reference alignment line, and the position coordinates of each line can be obtained by the caliper on each line. The number of the setting points of the caliper is in direct proportion to the length of the caliper, the setting point is generally set to be 2:1, the length of the caliper depends on the length of the edge to be detected, and the length of the caliper is set to be as large as possible because the length of the caliper is longer and the depth is higher.
In another embodiment, before the edge extraction is performed on the image of the FPC to be detected, preprocessing such as noise smoothing, restoration, gradient calculation, edge sharpening and the like may be performed on the image of the FPC to be detected, so that interference in the image is reduced, and the edge extraction accuracy is improved.
In this embodiment, the positions of the edge of the soft material on the image of the FPC to be detected and the substrate reference alignment line are determined by using a template matching positioning technology and an affine transformation technology, and then edge extraction is performed, so that the edge extraction accuracy can be effectively improved, and the detection accuracy of the bonding precision is improved.
Further, the S124 specifically includes:
s1241, preprocessing the image of the FPC to be detected to obtain a preprocessed image of the FPC to be detected;
s1242, template matching is carried out on the preprocessed FPC to be detected image, and the central position of a matching area matched with the template for positioning is obtained.
In this embodiment, the preprocessing mainly includes: noise smoothing, restoration, gradient computation, edge sharpening, etc. The image of the FPC to be detected is preprocessed, so that interference is reduced, the definition of the image can be improved, and the accuracy of template matching is improved.
As one optional embodiment, the step S13 specifically includes:
s131, judging whether the soft material edge extraction result contains position coordinates of four edges of the soft material;
s132, when the position coordinates of four sides of the soft material are judged to be contained in the soft material edge extraction result, judging whether the position coordinates of the substrate alignment reference line corresponding to the side are contained in the substrate reference alignment line extraction result or not for each side of the soft material, if so, calculating the position deviation value between the side and the corresponding substrate reference alignment line according to the position coordinates of the side and the position coordinates of the corresponding substrate alignment reference line, and if not, setting the position deviation value between the side and the corresponding substrate reference alignment line as a preset deviation value;
and S133, when the position coordinates of the four sides of the soft material are not included in the soft material edge extraction result, setting the position deviation values between the four sides of the soft material and the substrate reference diagonal line thereof as preset deviation values.
The preset offset value may be set according to an actual situation, which is not limited herein, and 1 is set to-1.
In this embodiment, the position deviation values between the four sides of the soft material and the substrate reference diagonal line thereof are determined according to whether the soft material edge extraction result and the substrate reference diagonal line extraction result contain complete edge position information, so that the accuracy of the position deviation values can be effectively improved, and the bonding precision detection accuracy is improved.
Further, the preset alarm condition is greater than a first preset offset threshold value or less than a second preset offset threshold value; the first preset offset threshold is greater than the second preset offset threshold, and the preset offset value is smaller than the second preset offset threshold.
In a specific implementation, the first preset offset threshold and the second preset offset threshold may be set according to an actual situation, and are not limited herein. Optionally, the first preset offset threshold is set to 0.03 mm, and the second preset offset threshold is set to 0.
It should be noted that, in an embodiment, the method for detecting the bonding precision of the soft material provided by the embodiment of the present invention may be executed by the laminator in the working process of the laminator as shown in fig. 2, so as to implement online detection of the bonding precision in the production process, thereby improving the efficiency. The laminating machine shown in fig. 2 comprises a left machine head 1, a right machine head 2 and an object carrying platform 3, wherein the object carrying platform 3 is used for placing the FPC to be detected. As shown in fig. 3, each of the handpieces includes a motor 101, a camera 102, a light source 103, an attaching Pad104 and a cylinder 105, and the camera 102 is used for acquiring an image of the FPC to be detected. The working process of the laminating machine is shown in fig. 4, in the whole working process of the laminating machine, firstly, a manipulator feeds materials (FPC substrate) and a shuttle plate feeds materials (soft materials); then the camera identifies the MARK points on the substrate; detecting a C-bit mark of the attaching position, and positioning and detecting the soft materials before attaching by a camera; executing the attaching action; the left machine head and the right machine head are alternately and circularly executed; after the bonding is performed, the flow of the bonding accuracy detection method provided in this embodiment is inserted. Wherein, in order to reduce aircraft nose displacement, improve detection efficiency, adopt the left side camera to detect left side laminating point, the right side camera detects right side laminating point.
Fig. 5 is a schematic structural diagram of a device for detecting the fitting accuracy of a soft material according to an embodiment of the present invention.
The device for detecting the fitting precision of the soft material provided by the embodiment of the invention comprises:
the image acquisition module 21 is used for acquiring an image of the FPC to be detected;
the edge extraction module 22 is used for performing soft material edge extraction and substrate reference diagonal line extraction on the image of the FPC to be detected to obtain a soft material edge extraction result and a substrate reference diagonal line extraction result;
an offset calculation module 23, configured to determine, according to the soft material edge extraction result and the substrate reference pair line extraction result, position offset values between four edges of the soft material and the corresponding substrate reference pair line;
and the precision detection module 24 is used for outputting alarm information when the position deviation value between any one edge of the soft material and the substrate reference alignment line thereof meets the preset alarm condition.
The device for detecting the bonding precision of the soft material, disclosed by the embodiment of the invention, acquires the image of the FPC to be detected, and then performs soft material edge extraction and substrate reference diagonal line extraction on the image of the FPC to be detected to obtain a soft material edge extraction result and a substrate reference diagonal line extraction result, then determining the position deviation values between the four sides of the soft material and the corresponding substrate reference pair bit lines according to the soft material edge extraction result and the substrate reference pair bit line extraction result, then when the position deviation value between any one edge of the soft material and the substrate reference diagonal line of the soft material meets the preset alarm condition, alarm information is output, the automatic detection of the fitting precision of the soft materials is realized, and the problems of low detection efficiency and low detection accuracy rate caused by manual detection in the prior art can be effectively solved.
As an optional embodiment, the edge extraction module 22 is specifically configured to:
creating a template for positioning, and extracting the central position of the template for positioning;
respectively creating a detection area corresponding to each edge of the soft material aiming at four edges of the soft material covered on the FPC to be detected, and extracting the central position of the detection area of each edge of the soft material;
aiming at substrate reference diagonal lines of four sides of the soft material on a substrate, respectively creating a detection area corresponding to each substrate reference diagonal line, and extracting the central position of the detection area of each substrate reference diagonal line;
template matching is carried out on the image of the FPC to be detected, and the central position of a matching area matched with the template for positioning is obtained;
performing affine transformation on the central position of the detection area of each side of the soft material and the central position of the detection area of each substrate reference pair bit line according to the central position of the template for positioning and the central position of the matching area to obtain the current central position of the detection area of each side of the soft material and the current central position of the detection area of each substrate reference pair bit line;
according to the current central position of the detection area of each edge of the soft material, performing edge extraction on the image of the FPC to be detected in the detection area of each edge of the soft material to obtain a soft material edge extraction result;
and according to the current central position of the detection area of each substrate reference counterpoint line, performing edge extraction on the image of the FPC to be detected in the detection area of each substrate reference counterpoint line to obtain a substrate reference counterpoint line extraction result.
Further, template matching is performed on the image of the FPC to be detected to obtain the central position of a matching area matched with the template for positioning, and the method specifically includes:
preprocessing the image of the FPC to be detected to obtain a preprocessed image of the FPC to be detected;
and carrying out template matching on the preprocessed FPC to be detected image to obtain the central position of a matching area matched with the template for positioning.
As an optional embodiment, the edge extracting module 23 is specifically configured to:
the determining, according to the soft material edge extraction result and the substrate reference diagonal line extraction result, position deviation values between four edges of the soft material and the corresponding substrate reference diagonal lines thereof specifically includes:
judging whether the soft material edge extraction result contains position coordinates of four edges of the soft material;
when the position coordinates of four sides of the soft material are judged to be contained in the soft material edge extraction result, judging whether the position coordinates of the substrate alignment reference line corresponding to the side are contained in the substrate reference alignment line extraction result or not for each side of the soft material, if so, calculating the position deviation value between the side and the corresponding substrate reference alignment line according to the position coordinates of the side and the position coordinates of the corresponding substrate alignment reference line, and if not, setting the position deviation value between the side and the corresponding substrate reference alignment line as a preset deviation value;
and when the position coordinates of the four sides of the soft material are not included in the soft material edge extraction result, setting the position deviation values between the four sides of the soft material and the substrate reference diagonal line as preset deviation values.
Further, the preset alarm condition is greater than a first preset offset threshold value or less than a second preset offset threshold value; the first preset offset threshold is greater than the second preset offset threshold, and the preset offset value is smaller than the second preset offset threshold.
As an alternative embodiment, the position offset value includes the shortest distance and the absolute value of the difference between the slopes.
It should be noted that the specific description of the device for detecting the fitting accuracy of the soft material provided in this embodiment is the same as the method for detecting the fitting accuracy of the soft material provided in the foregoing embodiment, and is not repeated herein.
Fig. 6 is a schematic structural diagram of a device for detecting the fitting accuracy of a soft material according to an embodiment of the present invention.
The device for detecting the fitting accuracy of the soft material provided by the embodiment of the invention comprises a processor 31, a memory 32 and a computer program which is stored in the memory 32 and configured to be executed by the processor 31, wherein the processor 31 implements the method for detecting the fitting accuracy of the soft material according to any one of the above embodiments when executing the computer program.
The processor 31 implements the steps in the above-mentioned method for detecting the fitting accuracy of the soft material when executing the computer program, for example, all the steps of the method for detecting the fitting accuracy of the soft material shown in fig. 1. Alternatively, the processor 31 may implement the functions of each module/unit in the above-mentioned soft material bonding accuracy detection apparatus embodiment when executing the computer program, for example, the functions of each module of the soft material bonding accuracy detection apparatus shown in fig. 5.
Illustratively, the computer program may be divided into one or more modules, which are stored in the memory 32 and executed by the processor 31 to accomplish the present invention. The one or more modules may be a series of instruction segments of a computer program capable of performing specific functions, and the instruction segments are used for describing the execution process of the computer program in the soft material fitting precision detection device. For example, the computer program may be divided into an image acquisition module, an edge extraction module, an offset calculation module, and a precision detection module, and each module has the following specific functions: the image acquisition module is used for acquiring an image of the FPC to be detected; the edge extraction module is used for carrying out soft material edge extraction and substrate reference bit line extraction on the image of the FPC to be detected to obtain a soft material edge extraction result and a substrate reference bit line extraction result; the offset calculation module is used for determining position offset values between the four sides of the soft material and the corresponding substrate reference pair line according to the soft material edge extraction result and the substrate reference pair line extraction result; and the precision detection module is used for outputting alarm information when the position deviation value between any one edge of the soft material and the substrate reference counterpoint line thereof meets the preset alarm condition.
The soft material fitting precision detection device can be a desktop computer, a notebook, a palm computer, a cloud server and other computing devices. The soft material fitting precision detection device may include, but is not limited to, a processor 31 and a memory 32. Those skilled in the art will appreciate that the schematic diagram is merely an example of the soft asset fit accuracy detection device, and does not constitute a limitation on the soft asset fit accuracy detection device, and may include more or less components than those shown, or combine some components, or different components, for example, the soft asset fit accuracy detection device may further include an input-output device, a network access device, a bus, etc.
The Processor 31 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. The general processor may be a microprocessor or the processor may be any conventional processor, and the processor 31 is a control center of the soft material bonding precision detection apparatus, and various interfaces and lines are used to connect various parts of the whole soft material bonding precision detection apparatus.
The memory 32 may be configured to store the computer program and/or the computer module, and the processor 31 implements various functions of the soft material fitting accuracy detection apparatus by running or executing the computer program and/or the computer module stored in the memory 32 and calling data stored in the memory 32. The memory 32 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data created according to use of the soft material attachment accuracy detection apparatus, and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
The module/unit integrated with the soft material fitting precision detection device can be stored in a computer readable storage medium if the module/unit is realized in the form of a software functional unit and is sold or used as an independent product. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, etc.
It should be noted that the above-described device embodiments are merely illustrative, where the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. In addition, in the drawings of the embodiment of the apparatus provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, and may be specifically implemented as one or more communication buses or signal lines. One of ordinary skill in the art can understand and implement it without inventive effort.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention.
Claims (9)
1. A method for detecting the fitting precision of a soft material is characterized by comprising the following steps:
collecting an image of the FPC to be detected;
carrying out soft material edge extraction and substrate reference diagonal line extraction on the image of the FPC to be detected to obtain a soft material edge extraction result and a substrate reference diagonal line extraction result;
determining position deviation values between four sides of the soft material and the corresponding substrate reference diagonal lines according to the soft material edge extraction result and the substrate reference diagonal line extraction result;
and when the position deviation value between any one edge of the soft material and the substrate reference counterpoint line of the soft material meets the preset alarm condition, outputting alarm information.
2. The method for detecting the fitting accuracy of the soft material according to claim 1, wherein the soft material edge extraction and the substrate reference pair bit line extraction are performed on the image of the FPC to be detected to obtain a soft material edge extraction result and a substrate reference pair bit line extraction result, and specifically comprises:
creating a template for positioning, and extracting the central position of the template for positioning;
respectively creating a detection area corresponding to each edge of the soft material aiming at four edges of the soft material covered on the FPC to be detected, and extracting the central position of the detection area of each edge of the soft material;
aiming at substrate reference diagonal lines of four sides of the soft material on a substrate, respectively creating a detection area corresponding to each substrate reference diagonal line, and extracting the central position of the detection area of each substrate reference diagonal line;
template matching is carried out on the image of the FPC to be detected, and the central position of a matching area matched with the template for positioning is obtained;
performing affine transformation on the central position of the detection area of each side of the soft material and the central position of the detection area of each substrate reference pair bit line according to the central position of the template for positioning and the central position of the matching area to obtain the current central position of the detection area of each side of the soft material and the current central position of the detection area of each substrate reference pair bit line;
according to the current central position of the detection area of each edge of the soft material, performing edge extraction on the image of the FPC to be detected in the detection area of each edge of the soft material to obtain a soft material edge extraction result;
and according to the current central position of the detection area of each substrate reference counterpoint line, performing edge extraction on the image of the FPC to be detected in the detection area of each substrate reference counterpoint line to obtain a substrate reference counterpoint line extraction result.
3. The method for detecting the fitting accuracy of the soft material according to claim 2, wherein the template matching is performed on the image of the FPC to be detected to obtain a center position of a matching area matched with the template for positioning, and specifically comprises:
preprocessing the image of the FPC to be detected to obtain a preprocessed image of the FPC to be detected;
and carrying out template matching on the preprocessed FPC to be detected image to obtain the central position of a matching area matched with the template for positioning.
4. The method according to claim 1, wherein the determining the position deviation values between the four sides of the soft material and the corresponding substrate reference pair line according to the soft material edge extraction result and the substrate reference pair line extraction result specifically includes:
judging whether the soft material edge extraction result contains position coordinates of four edges of the soft material;
when the position coordinates of four sides of the soft material are judged to be contained in the soft material edge extraction result, judging whether the position coordinates of the substrate alignment reference line corresponding to the side are contained in the substrate reference alignment line extraction result or not for each side of the soft material, if so, calculating the position deviation value between the side and the corresponding substrate reference alignment line according to the position coordinates of the side and the position coordinates of the corresponding substrate alignment reference line, and if not, setting the position deviation value between the side and the corresponding substrate reference alignment line as a preset deviation value;
and when the position coordinates of the four sides of the soft material are not included in the soft material edge extraction result, setting the position deviation values between the four sides of the soft material and the substrate reference diagonal line as preset deviation values.
5. The method for detecting the fitting accuracy of the soft material according to claim 4, wherein the preset alarm condition is greater than a first preset offset threshold value or less than a second preset offset threshold value; the first preset offset threshold is greater than the second preset offset threshold, and the preset offset value is smaller than the second preset offset threshold.
6. The method for detecting the fitting accuracy of the soft material according to claim 1, wherein the position offset value comprises an absolute value of a shortest distance and a difference between slopes.
7. The utility model provides a soft material laminating precision detection device which characterized in that includes:
the image acquisition module is used for acquiring an image of the FPC to be detected;
the edge extraction module is used for carrying out soft material edge extraction and substrate reference bit line extraction on the image of the FPC to be detected to obtain a soft material edge extraction result and a substrate reference bit line extraction result;
the offset calculation module is used for determining position offset values between the four sides of the soft material and the corresponding substrate reference pair line according to the soft material edge extraction result and the substrate reference pair line extraction result;
and the precision detection module is used for outputting alarm information when the position deviation value between any one edge of the soft material and the substrate reference counterpoint line thereof meets the preset alarm condition.
8. A soft material fitting accuracy detection device, characterized by comprising a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements the soft material fitting accuracy detection method according to any one of claims 1 to 6 when executing the computer program.
9. A computer-readable storage medium, comprising a stored computer program, wherein when the computer program runs, the computer-readable storage medium controls a device to execute the method according to any one of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010567207.2A CN111784648A (en) | 2020-06-19 | 2020-06-19 | Soft material fitting precision detection method, device, equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010567207.2A CN111784648A (en) | 2020-06-19 | 2020-06-19 | Soft material fitting precision detection method, device, equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111784648A true CN111784648A (en) | 2020-10-16 |
Family
ID=72757517
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010567207.2A Pending CN111784648A (en) | 2020-06-19 | 2020-06-19 | Soft material fitting precision detection method, device, equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111784648A (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112598645A (en) * | 2020-12-23 | 2021-04-02 | 深兰人工智能芯片研究院（江苏）有限公司 | Contour detection method, apparatus, device and storage medium |
| CN112611324A (en) * | 2020-12-02 | 2021-04-06 | 南京尚孚电子电路有限公司 | Insulation film pasting detection system for flexible circuit board and detection method thereof |
| CN112649446A (en) * | 2020-11-12 | 2021-04-13 | 巨轮(广州)智能装备有限公司 | FPC detection method, laminating method and device |
| CN113375558A (en) * | 2021-06-23 | 2021-09-10 | 深圳市泰科盛自动化***有限公司 | Detection system based on FFC flexible flat cable and Mylar laminating |
| CN114370993A (en) * | 2021-12-31 | 2022-04-19 | 深圳市深科达智能装备股份有限公司 | Detection method and calibration method of polaroid lamination detection equipment and related equipment |
| CN115272472A (en) * | 2022-09-27 | 2022-11-01 | 成都新西旺自动化科技有限公司 | Special-shaped high-precision alignment system |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006003561A (en) * | 2004-06-16 | 2006-01-05 | Sharp Corp | Aligned substrate |
| JP2012007898A (en) * | 2010-06-22 | 2012-01-12 | Kobelco Kaken:Kk | Positional shift detector for laminated substrate and semiconductor manufacturing device using the same, and positional shift detection method for laminated substrate |
| CN102736280A (en) * | 2012-05-22 | 2012-10-17 | 北京京东方光电科技有限公司 | Polarizing plate attached precision detection device and method |
| CN204301688U (en) * | 2014-12-16 | 2015-04-29 | 日东电工株式会社 | Bonding position testing fixture |
| CN105479786A (en) * | 2014-09-19 | 2016-04-13 | 软控股份有限公司 | Embryo molding part lamination detecting device and method |
| CN208334229U (en) * | 2018-05-04 | 2019-01-04 | 东莞塘厦裕华电路板有限公司 | Printed IC board detection system |
| CN110109945A (en) * | 2019-04-10 | 2019-08-09 | 深圳市华星光电技术有限公司 | Applied to the AOI detection method of substrate, device, storage medium and AOI detection device |
| CN209731941U (en) * | 2018-12-25 | 2019-12-03 | 东莞市宏鑫创达智能科技有限公司 | A kind of soft goods, materials and equipments of FPC detection structure in place |
-
2020
- 2020-06-19 CN CN202010567207.2A patent/CN111784648A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006003561A (en) * | 2004-06-16 | 2006-01-05 | Sharp Corp | Aligned substrate |
| JP2012007898A (en) * | 2010-06-22 | 2012-01-12 | Kobelco Kaken:Kk | Positional shift detector for laminated substrate and semiconductor manufacturing device using the same, and positional shift detection method for laminated substrate |
| CN102736280A (en) * | 2012-05-22 | 2012-10-17 | 北京京东方光电科技有限公司 | Polarizing plate attached precision detection device and method |
| CN105479786A (en) * | 2014-09-19 | 2016-04-13 | 软控股份有限公司 | Embryo molding part lamination detecting device and method |
| CN204301688U (en) * | 2014-12-16 | 2015-04-29 | 日东电工株式会社 | Bonding position testing fixture |
| CN208334229U (en) * | 2018-05-04 | 2019-01-04 | 东莞塘厦裕华电路板有限公司 | Printed IC board detection system |
| CN209731941U (en) * | 2018-12-25 | 2019-12-03 | 东莞市宏鑫创达智能科技有限公司 | A kind of soft goods, materials and equipments of FPC detection structure in place |
| CN110109945A (en) * | 2019-04-10 | 2019-08-09 | 深圳市华星光电技术有限公司 | Applied to the AOI detection method of substrate, device, storage medium and AOI detection device |
Non-Patent Citations (1)
| Title |
|---|
| 李永妮;陈来春;彭卫红;刘东;何为;: "关于双面铜基板多层覆盖膜的制作方法", 印制电路信息, no. 06, 10 June 2018 (2018-06-10) * |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112649446A (en) * | 2020-11-12 | 2021-04-13 | 巨轮(广州)智能装备有限公司 | FPC detection method, laminating method and device |
| CN112649446B (en) * | 2020-11-12 | 2024-02-13 | 巨轮(广州)智能装备有限公司 | FPC detection method, bonding method and device |
| CN112611324A (en) * | 2020-12-02 | 2021-04-06 | 南京尚孚电子电路有限公司 | Insulation film pasting detection system for flexible circuit board and detection method thereof |
| CN112598645A (en) * | 2020-12-23 | 2021-04-02 | 深兰人工智能芯片研究院（江苏）有限公司 | Contour detection method, apparatus, device and storage medium |
| CN112598645B (en) * | 2020-12-23 | 2022-07-01 | 深兰智能科技(上海)有限公司 | Contour detection method, apparatus, device and storage medium |
| CN113375558A (en) * | 2021-06-23 | 2021-09-10 | 深圳市泰科盛自动化***有限公司 | Detection system based on FFC flexible flat cable and Mylar laminating |
| CN113375558B (en) * | 2021-06-23 | 2022-12-23 | 深圳市泰科盛自动化***有限公司 | Detection system based on FFC flexible flat cable and Mylar laminating |
| CN114370993A (en) * | 2021-12-31 | 2022-04-19 | 深圳市深科达智能装备股份有限公司 | Detection method and calibration method of polaroid lamination detection equipment and related equipment |
| CN115272472A (en) * | 2022-09-27 | 2022-11-01 | 成都新西旺自动化科技有限公司 | Special-shaped high-precision alignment system |
| CN115272472B (en) * | 2022-09-27 | 2023-01-06 | 成都新西旺自动化科技有限公司 | Special-shaped high-precision alignment system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111784648A (en) | Soft material fitting precision detection method, device, equipment and storage medium | |
| EP3588429A1 (en) | Processing method, processing device, electronic device and computer readable storage medium | |
| CN110919653B (en) | Stair climbing control method and device for robot, storage medium and robot | |
| CN108381549B (en) | Binocular vision guide robot rapid grabbing method and device and storage medium | |
| CN111879777A (en) | Soft material fitting defect detection method, device, equipment and storage medium | |
| CN105528789B (en) | Robot visual orientation method and device, vision calibration method and device | |
| US10824900B2 (en) | Information processing device and recognition support method | |
| EP3910593A1 (en) | Image processing device, work robot, substrate inspection device, and specimen inspection device | |
| CN111721259A (en) | Underwater robot recovery positioning method based on binocular vision | |
| CN115171097B (en) | Processing control method and system based on three-dimensional point cloud and related equipment | |
| CN108510477B (en) | Method and device for positioning color block of test paper | |
| CN110926330A (en) | Image processing apparatus, image processing method, and program | |
| CN113313135A (en) | Marking control method and device and computer readable storage medium | |
| CN110640303B (en) | High-precision vision positioning system and positioning calibration method thereof | |
| CN110807807A (en) | Monocular vision target positioning pattern, method, device and equipment | |
| CN104760812A (en) | Monocular vision based real-time location system and method for products on conveying belt | |
| CN105701496B (en) | A kind of go disk recognition methods based on artificial intelligence technology | |
| CN108749338B (en) | Manicure prints calibration method, device, equipment and computer readable storage medium | |
| CN110188640B (en) | Face recognition method, face recognition device, server and computer readable medium | |
| US11712807B2 (en) | Image processing apparatus, robot and robot system | |
| CN111105365A (en) | Color correction method, medium, terminal and device for texture image | |
| CN111435429A (en) | Gesture recognition method and system based on binocular stereo data dynamic cognition | |
| CN114092428A (en) | Image data processing method, image data processing device, electronic equipment and storage medium | |
| CN116237995A (en) | Method and device for adjusting path track and readable storage medium | |
| CN113971662B (en) | Processing control method, device and equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |