CN109632814A - Part defect detection method - Google Patents
Part defect detection method Download PDFInfo
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- CN109632814A CN109632814A CN201910100932.6A CN201910100932A CN109632814A CN 109632814 A CN109632814 A CN 109632814A CN 201910100932 A CN201910100932 A CN 201910100932A CN 109632814 A CN109632814 A CN 109632814A
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- 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
- G01N21/8806—Specially adapted optical and illumination features
-
- 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
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
- G06T7/0008—Industrial image inspection checking presence/absence
-
- 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
- G01N21/8806—Specially adapted optical and illumination features
- G01N2021/8809—Adjustment for highlighting flaws
-
- 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
- G06T2207/20—Special algorithmic details
- G06T2207/20092—Interactive image processing based on input by user
- G06T2207/20104—Interactive definition of region of interest [ROI]
-
- 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
Abstract
The present invention relates to technical field of vision detection, refer in particular to a kind of part defect detection method, include the following steps, carry out Image Acquisition to part；The image of acquisition is subjected to spot detection algorithm process, identification obtains Central of the parts point coordinate；ROI algorithm frame is established based on Central of the parts point coordinate；ROI algorithm frame is moved to the position of detection needed for part；Spot detection algorithm is carried out in ROI algorithm frame, whether there is fleck in identification frame；There are three shoot station for setting, each shooting station acquires a part image, the corresponding position for only detecting part of every image, a position of analysis detection part is only needed to ensure that the stability of detection and analysis and the accuracy of detection judgement every time, the difficulty and use cost of algorithm operation are reduced simultaneously, conventional algorithm can be used in spot detection algorithm in this method, and convenient for the receiving understanding of those of ordinary skill and parameter setting, flexibility is good.
Description
Technical field
The present invention relates to technical field of vision detection, refer in particular to a kind of part defect detection method.
Background technique
The characteristics of Machine Vision Detection is the flexibility and the degree of automation for improving production.It is not suitable for manual work some
Dangerous work environment or artificial vision be difficult to the occasion met the requirements, machine in normal service vision substitutes artificial vision；Exist simultaneously
In high-volume industrial processes, manually visual inspection product quality low efficiency and precision is not high, with Machine Vision Detection side
Method can greatly improve the degree of automation of production efficiency and production.And machine vision is easily achieved information integration, is to realize
The basic technology of computer integrated manufacturing system.Vision-based detection is exactly to replace human eye with machine to measure and judge.Vision-based detection is
Refer to that, by machine vision product, image-pickup device is divided to CMOS and two kinds of CCD, will be ingested target and be converted into picture signal,
It sends dedicated image processing system to, according to the information such as pixel distribution and brightness, color, is transformed into digitized signal；Image
System carries out various operations to these signals to extract clarification of objective, and then the equipment at scene is controlled according to the result of differentiation
Movement.It is the valuable mechanism for producing, assembling or pack.It is in detection defect and prevents from faulty goods to be dispensed into disappearing
There is immeasurable value in terms of the function of the person of expense.
As above situation, vision-based detection has huge market value, most crucial in vision-based detection system not to be
Hardware device but algorithm steps, and algorithm steps can be because of testing result requirement, product shape, operating environment situation and design
The appearance of the factors such as the technical capability of personnel or group is multifarious, if core algorithm step design shortcoming, affects a whole set of view
The operational efficiency and running quality for feeling detection device, and in the feel detection algorithm step of ceramic part, most of skill in the market
Art scheme, which only just identifies Image Acquisition of part progress, judges whether there is defect, its entirety while identification error rate is high
The lasting use cost of equipment is high.
Summary of the invention
The technical problem to be solved in the present invention is to provide a kind of pair of parts to acquire multiple image, every image recognition detection zero
One position of part ensure that the part defect detection method of recognition accuracy while reducing algorithm operation difficulty.
In order to solve the above-mentioned technical problem, the present invention adopts the following technical scheme: a kind of part defect detection method, including
Following steps, step 1: Image Acquisition is carried out to part；
Step 2: the image of acquisition being subjected to spot detection algorithm process, and identifies and obtains Central of the parts point coordinate；
Step 3: ROI algorithm frame is established based on Central of the parts point coordinate；
Step 4: ROI algorithm frame is moved to the position of detection needed for part；
Spot detection algorithm is carried out in step 5:ROI algorithm frame, whether there is fleck in identification frame；
Step 6: the recognition result in ROI algorithm frame is converted into the output of readable data information.
Preferably, light source using low angle strip light exposes to part in the step 1, the light-emitting surface of the light source and horizontal
Angle between face is 8 to 21 degree, and the vertical spacing distance between light source and part is 0.8 to 4.6 millimeter.
Preferably, light source using low angle strip light exposes to part in the step 1, the light-emitting surface of the light source and horizontal
Angle between face is 12 degree, and the vertical spacing distance between light source and part is 1 millimeter.
Preferably, the Image Acquisition in the step 1 is that multiple parts acquire together.
Preferably, the Image Acquisition in the step 1 is to carry out Image Acquisition three times to part respectively.
Preferably, in the image acquired three times in the step 4, ROI algorithm frame only detects part in an image
A position, three images acquired three times respectively correspond ROI algorithm frame detection part head end portion, medial end portions and tail end
Portion.
Preferably, identifying in the step 5 whether there is fleck in ROI frame, the Components are judged if having fleck
Position existing defects judge that there is no defects at the part position if without fleck.
Preferably, the readable data information in the step 6 is exported to display device, and display device shows and acquires three times
Three images and image in defective site marking is come out.
The beneficial effects of the present invention are: a kind of part defect detection method is provided, this method is in the image of acquisition
It is acquired using strip source lamp and using low angle radiation modality assistant images, the defect effectively highlighted on part is special
Sign enhances recognition accuracy to obtain the image of high contrast, and in practical operation detection, there are three settings shoots station,
Each shooting station acquires a part image, and the corresponding position for only detecting part of every image is detected three times by part
Whole detection complete, only need every time a position of analysis detection part ensure that detection and analysis stability and detection judgement
Accuracy, while reducing the difficulty and use cost of algorithm operation, the spot detection algorithm in this method can be used conventional
Algorithm, convenient for the receiving understanding of those of ordinary skill and parameter setting, flexibility is good.
Detailed description of the invention
Fig. 1 is detection contrast schematic diagram of the technical solution of the present invention to multiple part head ends portion.
Fig. 2 is detection contrast schematic diagram of the technical solution of the present invention to multiple part medial end portions.
Specific embodiment
For the ease of the understanding of those skilled in the art, below with reference to embodiment, the present invention is further illustrated, real
The content that the mode of applying refers to not is limitation of the invention.
As shown in Figure 1 to Figure 2, a kind of part defect detection method, includes the following steps, step 1: dividing multiple parts 1
Do not acquired image three times, light source exposes to part 1 using low angle strip light, between the light-emitting surface and horizontal plane of the light source
Angle be 12 degree, vertical spacing between light source and part 1 distance is 1 millimeter；
Step 2: the image of acquisition being subjected to spot detection algorithm process, and identifies and obtains 1 center point coordinate of part；
Step 3: ROI algorithm frame is established based on 1 center point coordinate of part；
Step 4: the position of detection needed for ROI algorithm frame is moved to part 1, in the image acquired three times, ROI algorithm frame exists
A position of part 1 is only detected in one image, three images acquired three times respectively correspond ROI algorithm frame detection part 1
Head end portion, medial end portions and tail end；
Spot detection algorithm is carried out in step 5:ROI algorithm frame, be whether there is fleck in identification frame, is judged if having fleck
The 1 position existing defects of part judge that there is no defects at 1 position of part if without fleck；
Step 6: the recognition result in ROI algorithm frame is converted into the output of readable data information, the output of readable data information
To display device, display device shows in three images and image acquired three times and comes out defective site marking.
The part defect detection method of the present embodiment, this method using strip source lamp and make in the image of acquisition
It is acquired with low angle radiation modality assistant images, the defect characteristic on part 1 is effectively highlighted, to obtain high contrast
Image enhances recognition accuracy, and in practical operation detection, there are three station is shot, each shooting station acquisition is primary for setting
1 image of part, the corresponding position for only detecting part 1 of every image, detects complete the whole detection of part 1 three times, often
The secondary stability for needing a position of analysis detection part 1 to ensure that detection and analysis and the accuracy of detection judgement, drop simultaneously
The low difficulty and use cost of algorithm operation, the spot detection algorithm in this method can be used conventional algorithm, be convenient for common skill
The receiving understanding of art personnel and parameter setting, flexibility are good.
In addition, being used for description purposes only if any term " first ", " second ", it is not understood to indicate or imply relatively heavy
The property wanted or the quantity for implicitly indicating technical characteristic." first " is defined as a result, " second " feature can be expressed or implicit include
One or more this feature, in the present description, " several " are meant that two or more, unless otherwise clearly having
The restriction of body.
In the present invention, except as otherwise clear stipulaties and restriction, should make if any term " assembling ", " connected ", " connection " term
Broad sense goes to understand, for example, it may be being fixedly connected, may be a detachable connection, or be integrally connected；It is also possible to mechanical connect
It connects；It can be directly connected, be also possible to be connected by intermediary, can be and be connected inside two elements.For ability
For the those of ordinary skill of domain, the concrete meaning of above-mentioned term in the present invention can be understood as the case may be.
Several embodiments of the invention above described embodiment only expresses, the description thereof is more specific and detailed, but simultaneously
Limitations on the scope of the patent of the present invention therefore cannot be interpreted as.It should be pointed out that for those of ordinary skill in the art
For, without departing from the inventive concept of the premise, various modifications and improvements can be made, these belong to guarantor of the invention
Protect range.Therefore, the scope of protection of the patent of the invention shall be subject to the appended claims.
Claims (8)
1. part defect detection method, it is characterised in that: include the following steps,
Step 1: Image Acquisition is carried out to part (1)；
Step 2: the image of acquisition being subjected to spot detection algorithm process, and identifies and obtains part (1) center point coordinate；
Step 3: ROI algorithm frame is established based on part (1) center point coordinate；
Step 4: ROI algorithm frame is moved to the position detected needed for part (1)；
Spot detection algorithm is carried out in step 5:ROI algorithm frame, whether there is fleck in identification frame；
Step 6: the recognition result in ROI algorithm frame is converted into the output of readable data information.
2. part defect detection method according to claim 1, it is characterised in that: light source uses low angle in the step 1
Degree strip light exposes to part (1), and the angle between the light-emitting surface and horizontal plane of the light source is 8 to 21 degree, light source and part (1)
Between vertical spacing distance be 0.8 to 4.6 millimeter.
3. part defect detection method according to claim 1, it is characterised in that: light source uses low angle in the step 1
Degree strip light exposes to part (1), and the angle between the light-emitting surface and horizontal plane of the light source is 12 degree, light source and part (1) it
Between vertical spacing distance be 1 millimeter.
4. part defect detection method according to claim 1, it is characterised in that: the Image Acquisition in the step 1 is
Multiple parts (1) acquire together.
5. part defect detection method according to claim 1, it is characterised in that: the Image Acquisition in the step 1 is
Image Acquisition three times is carried out to part (1) respectively.
6. part defect detection method according to claim 5, it is characterised in that: to acquiring three times in the step 4
In image, ROI algorithm frame only detects a position of part (1) in an image, and three images acquired three times are right respectively
Answer head end portion, medial end portions and the tail end of ROI algorithm frame detection part (1).
7. part defect detection method according to claim 6, it is characterised in that: identifying in ROI frame in the step 5 is
No there are flecks, part (1) position existing defects are judged if having fleck, if judging the part (1) without fleck
Defect is not present in position.
8. part defect detection method according to claim 7, it is characterised in that: the readable data in the step 6
Information is exported to display device, and display device is shown in three images and image acquired three times by defective site marking
Out.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910100932.6A CN109632814A (en) | 2019-02-01 | 2019-02-01 | Part defect detection method |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910100932.6A CN109632814A (en) | 2019-02-01 | 2019-02-01 | Part defect detection method |
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| CN109632814A true CN109632814A (en) | 2019-04-16 |
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| CN201910100932.6A Pending CN109632814A (en) | 2019-02-01 | 2019-02-01 | Part defect detection method |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110082356A (en) * | 2019-04-20 | 2019-08-02 | 东莞中科蓝海智能视觉科技有限公司 | The visible detection method and device of wire surface defect |
| CN112581001A (en) * | 2020-12-24 | 2021-03-30 | 成都安易迅科技有限公司 | Device evaluation method and device, electronic device and readable storage medium |
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| CN102513819A (en) * | 2011-12-21 | 2012-06-27 | 中国计量学院 | Right angle type expansion bolt and screw automatic assembly device and defect detection method thereof |
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Application publication date: 20190416 |