CN106157300A - There is the formal print inspection of local optimum - Google Patents
There is the formal print inspection of local optimum Download PDFInfo
- Publication number
- CN106157300A CN106157300A CN201610465033.2A CN201610465033A CN106157300A CN 106157300 A CN106157300 A CN 106157300A CN 201610465033 A CN201610465033 A CN 201610465033A CN 106157300 A CN106157300 A CN 106157300A
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- image
- tolerance
- printing
- local
- threshold
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Classifications
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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
- G06T7/001—Industrial image inspection using an image reference approach
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B41—PRINTING; LINING MACHINES; TYPEWRITERS; STAMPS
- B41F—PRINTING MACHINES OR PRESSES
- B41F33/00—Indicating, counting, warning, control or safety devices
- B41F33/04—Tripping devices or stop-motions
- B41F33/10—Tripping devices or stop-motions for starting or stopping operation of damping or inking units
-
- 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
- G06T2207/30144—Printing quality
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- Engineering & Computer Science (AREA)
- Quality & Reliability (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Image Processing (AREA)
- Image Analysis (AREA)
- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
- Inking, Control Or Cleaning Of Printing Machines (AREA)
Abstract
The present invention relates to a kind of method for image inspection being carried out by computer adaptation, wherein in the range of image inspection configures, benchmark image is read in together with global threshold and tolerance, the wherein printing image of this image inspection detection printing process, and indicate the deviation to global threshold and tolerance on the display controlling computer, and obtain the local buildup of deviation for defect image.The method is characterized in that, user can change threshold value and/or tolerance for the regional area that printing image one determines in printing process, and stores this local threshold changed and/or tolerance, and uses in image inspection subsequently.
Description
Technical field
The present invention relates to a kind of for image review systems being carried out the method that local threshold is adaptive.
The present invention is in test automation technical field.
Background technology
The most use image checking method to be optimized, in order to perform in the range of presswork the printing completed
The defect being likely to occur is tested in product examine.Here, the image printed is swept up by means of digital camera, data are sent to calculate
Machine, and at this computer with compared with benchmark image produced by the data of preproduction phase.As an alternative, also may be used
To use the zero defect sample of printing image as benchmark image.Then, it is integrated in image inspection being referred to as reading in
(Einlernen).Then, depending on the parameter of comparison algorithm is arranged, identify the most digitized
(redigitalisiert) deviation between printing image and described benchmark image as defect (Fehler) and is indicated.
This parameter is arranged and there is multiple probability according to prior art so far.The most frequently used probability is by using
Person manually adjusts setup parameter.Here, the benchmark image that user analysis is set up by the data of presswork preproduction phase,
And according to the practical experience of analysis result and this user individual, image checking method is configured.Here, except threshold value with
Outward, determined following tolerance (Toleranzwert) by benchmark image the most by way of parenthesis: printing image to be checked record number
Value allows to deviate this tolerance with threshold value.The known expansion scheme of this method e.g., will adjust that setup parameter is abstract is
Different sensitive grades.The advantage of this method is, even if unfamiliar user also is able to perform the parameter of inspection method
Arrange, because user need not each parameter of direct intervention again.Otherwise, shortcoming is, with entirely free on his manually adjust setting compared with,
The motility of the method is not enough.Additionally, the overall shortcoming of all known manual methods relates to the dependency of mankind's user,
That is, the analysis of this user and then the adjustment setting of image checking method is probably vicious.User does not more have experience, adjusts
Selecting of whole setup parameter is the most complicated, then mistake probability is the highest.Additionally, be typically due to the reason of time and then cost, not exist
Parameter adaptation is carried out during each new presswork.Another shortcoming is, the tolerance configured is the overall situation (global) numerical value,
Measured value allows to deviate described tolerance with benchmark image.It is to say, for all threshold values in identical sensitive grade,
Big permissible aberration is the biggest.Consequent problem is, local (lokal) deviation of benchmark image, for user self
For (such as due to the ad hoc structure of these partial deviations) entirely without problem, but image review systems is still by this
A little partial deviations are labeled as defect, because these partial deviations violate the maximum tolerance limit.Printing image is in presswork
During (such as due to the abrasion of printer and other act on) often change.This makes to carry out the tolerance during presswork
Additional adaptation necessitates.
So far e.g., respective regions is by mask for solution known to this problem for prior art
(Maske) cover and ignored (auszusparen) by image review systems, this however at these positions in image inspection
On cause vacancy.Furthermore, it is possible to printing image division is become different inspection areas, and then enter by different tolerances
Performing check.But, there is shortcoming during this first time configuration being divided in image inspection: this division is only in the most known printing
When which region of image is problematic, ability is the most meaningful.Additionally, this division is manually performed by user mostly, and in practice
Seldom manually performed by user due to required consuming reason.
Therefore, by DE 102014004555 A1 it is known that improve for the uneven image-region with multiple seamed edge
Maximum tolerance, and, reduce maximum tolerance for the homogeneous image region with few seamed edge.But, ask for for all
Uneven or uniform region for, this changes is the most effective, say, that be also performed to global adaptation setting in addition.
Additionally, described global adaptation be set in image review systems first time configuration during perform equally.
Further possibility is, again reads in complete benchmark image.The region thus having been changed to becomes new treating
The standard of correction.
It is adaptive (it is to say, pin that prior art can not realize carrying out maximum tolerance during operation image inspection local
For fixed local image region).By this local adaptive should by fixed, selected by user
Image-region and object are marked with the maximum tolerance being different from printing image remainder, so that these image-regions
Checked adaptedly by image review systems with object.
Summary of the invention
Therefore, the task of the present invention is, proposes a kind of method for the tolerance of image review systems carries out adaptation, should
The tolerance of image review systems can be carried out additionally adaptive for selected local image region by method.
This task is according to the solution of the present invention, proposes one for carrying out image inspection by computer
Adaptive method, wherein, in the framework of image inspection configuration, performs the reading with global threshold and tolerance, image inspection
The printing image of system test printing process, and, the display controlling computer demonstrates and global threshold and tolerance
Deviation, wherein, the local buildup of deviation is summarized as defect image.It is characterized in that, user can be in printing process
Threshold value and/or tolerance is changed for the fixed regional area of printing image, and, store these local thresholds changed
Value and/or tolerance, and, use in image inspection subsequently.
Therefore, in the framework of this method, image review systems is as being configured by known in the art so far.But such as
Really this system identification goes out defect and is shown that then user can be selected and know around this on the display controlling computer
The image-region of the defect not gone out, and determine the size in this region, and the appearance changed then is determined for this region
Difference.The advantage of this method is, it is not necessary to read in the completely new benchmark image with adaptive tolerance, and, this user is also
By adaptive maximum acceptable tolerances, the change in printing image can be reacted.This change of this external memory and the most right
Work for image inspection subsequently.
This method favourable so that preferably improvement project by corresponding dependent claims and with reference to respective drawings institute
The description made draws.
Here, the preferred improvement project of the method according to the invention is, read in the fixed partial zones of printing image
Territory, as new partial reference.If the tolerance changed also is insufficient to, then can also again read in selected partial zones
Territory, as new partial reference.It is to say, as unlike known in the state of the art, again read in have and change print
The current page of map brushing picture, as new overall benchmark, but only reads in the regional area selected by user.This such as exists
In printing zone, single printing object is probably needs in the case of geometric aspects offsets.Such as, if at printing image
In a bar code move two pixels, then the inspection area that may print in benchmark image can not be printed also now
And vice versa.In this case, change the maximum tolerance limit the most helpful, and can only again read in the district offset
Territory.
Here, the preferred improvement project of the method according to the invention is, improve in fixed local image region
Threshold value and/or tolerance.
In most cases, need to improve maximum acceptable tolerances.First, when local changes while more than original
Tolerance, but be evaluated as can accept for user.
Here, the preferred improvement project of the method according to the invention is, by storage the local threshold changed and/or
Tolerance is for the operation of repeating print of same printed image.
If repeating identical presswork, then suggestion reuses the local tolerance changed.
Here, the preferred improvement project of the method according to the invention is, make storage the local threshold changed and/or
Tolerance is effective to defect image.
The most not only identify a defect in a region, but identify multiple deviation immediately adjacent to one another.
In this case, these defects are jointly indicated by image review systems as a defect image.It is to say, will display
On device, defective image section expands to the defect of all direct neighbors, thus indicates whole defective region.
Here, the preferred improvement project of the method according to the invention is, make the image pair of defect image and printing image
As being associated.
If identifying the defect image with multiple Adjacent defect, then make this defect image the most always with printing image
In determination image object be associated.Image review systems identifies this defective image object and it is shown completely
Go out.Then, user can change the tolerance for this image object or weight in the framework of the method according to the invention
Newly read in regional area.
Here, the preferred improvement project of the method according to the invention is, selected image object is classified, and
And, for having the subsequent job of the image object of same category, for the image object of this same category, apply this to select
The local threshold of the corresponding distribution of fixed image object and/or tolerance.If identifying defective image object and by using
Person marks with the tolerance changed, then image review systems stores this object, and, just returned as possible
Enter the determination classification of image object.Example e.g. bar code or matrix coder, landscape painting etc. for this kind.In
It is, for having the image object of same category in current presswork, to use identical tolerance to change.Even if in the future
In the presswork of the image object that application has same category, it is also possible to identical changing is applied for this image object
The threshold value become and/or tolerance.This can automatically carry out or can be configured by user.
Here, the preferred improvement project of the method according to the invention is, the image object of printing image is made up of seamed edge.
For this be identified as image object that is defective but that consider effectively as good situations for mainly should
It is following object by situation: this object has multiple seamed edge, such as bar code.
This method and the scheme that is functionally advantageously improved thereof will be with reference to respective drawings according at least one preferred embodiments
Describe in further detail.The most corresponding element indicates by the most identical reference.
Accompanying drawing explanation
Accompanying drawing shows:
The system structure of Fig. 1: image review systems；
Fig. 2: the example of defective image object；
The preferred flow process of Fig. 3: the method according to the invention.
Detailed description of the invention
Here, preferred embodiment is as described below.At least one is included at the image review systems 2 shown in Fig. 1 as example
The individual imageing sensor 5 (typically video camera 5) being integrated in printer 4.At least one video camera 5 photographs by printer 4
Produced printing image, and transmit data to computer 3 in order to analyze and process.Computer 3 can be self independent meter
Calculation machine (such as, the pattern process computer 14 of one or more specialties) or identical with the control computer 3 of printer 4.Root
Schematically illustrate in Fig. 3 according to the flow process of the method for the present invention.User 1 configures described image review systems 2, and its mode is to make
Benchmark image 13 is read in image review systems 2 by user 1.It is to say, for image inspection, calculate according to benchmark image 13
Global threshold 8, then, by by the view data of image detected by video camera 5, that print compared with this global threshold 8
Relatively.Meanwhile, user 1 gives the maximum tolerance 12 of threshold value 8 distribution license by image review systems 2.The maximum tolerance of this license
12 brightness values giving the actual printing image printed are allowed to what extent deviate from the threshold value of benchmark image 13
8.The tolerance 12 of whole printing image can be set to constant by user 1, and this also complies with the common practices in practice.So
And, different tolerances 12 is distributed in the region that printing image additionally can be given different.Thus, such as the most uneven with structure
(inhomogen) plane (such as including multiple seamed edge) is compared, and the image-region with uniformly (homogen) face can be by
Relatively sharplyInspection, and therefore obtain less tolerance.Then, these non-homogeneous must correspondingly be obtained
Tolerance limits that must be higher, because being here likely to deviate threshold value 8.The threshold value 8 thus set up by these and tolerance 12,
Then in the printing process run, perform image inspection.If image review systems 2 finds to exceed the deviation 9 of tolerance limits,
Then shown and controlled on the display 11 of computer 3 at printer 4.If but now user 1 can accept to be found
Defective image-region 9, then user 1 can select defective region or the selected defective image pair found
(such as by controlling the mouse of computer 4 and keyboard or passing through touch screen) and assign to this region 7 as 7 and to have increased
Maximum tolerance 10.For these defective regions or defective image object 7, the control computer 3 of printer 4 stores pin
The tolerance 10 being changed selected region, in order to operation image inspection.As an alternative or supplement, it is also possible to have been changed to
Region read in as new partial reference.Especially when simply increasing tolerance limits 12 and being insufficient to, above-mentioned situation is special
Favorably.Thus, figure 2 illustrates this situation: image object 6 is printing with the sharpest keen seamed edge (being here bar code)
During the most somewhat move with geometric ways in page.Compared with benchmark image 13, now due to bar code 7 moves
Dynamic, black region bleaches and vice versa.Image inspection finds considerable defect 9.But, because bar code 7 itself is
Correct, so this is acceptable defect.Therefore, relevant range is read in as new benchmark partly, thus makes image
Check and no longer defect area is included in these regions.For residue printing process and the image inspection that continues to run with whereby,
Then the tolerance 10 that changed for selected area applications or apply new partial reference.Additionally, user 1 can be
The configuration aspect of image inspection is adjusted setting so that even if performed local changes 10 in the situation of operation of repeating print
Under also keep effectively.
Reference numerals list
1 user
2 image review systems
3 control computer
4 printer
5 imageing sensors
6 original image objects
7 image objects with permissible aberration
8 global thresholds
The defect that 9 image inspections are found
The local maxima tolerance that 10 have changed
11 display
12 overall situation maximum tolerance values
13 benchmark images read in
14 pattern process computers
Claims (8)
1. for the method that by computer (3), image inspection is carried out adaptation, wherein, at the framework of image inspection configuration
In, read in the benchmark image (13) with global threshold (8) and tolerance (12), wherein, described image inspection is to printing process
Printing image is tested, and, the display (11) controlling computer (3) demonstrates and global threshold (8) and tolerance
(12) deviation (9), wherein, is summarized in defect image (7) by the local buildup of deviation (9),
It is characterized in that,
User (1) can during printing process for printing image fixed regional area and change threshold value (8) and/
Or tolerance (12), and, the local threshold having been changed to and/or tolerance (10) store and are applied to other image inspection.
Method the most according to claim 1, it is characterised in that read in the fixed regional area of printing image as newly
Partial reference.
3. according to the method one of aforementioned claim Suo Shu, it is characterised in that improve in fixed local image region
Threshold value (8) and/or tolerance (12).
4. according to the method one of aforementioned claim Suo Shu, it is characterised in that repeat to make for having same printed image
Industry, applies the local threshold changed and/or tolerance (10) stored.
5. according to the method one of aforementioned claim Suo Shu, it is characterised in that the local threshold changed that stored and/or
Tolerance (10) is effective to defect image.
Method the most according to claim 5, it is characterised in that described defect image and the image object (7) printing image
It is associated.
Method the most according to claim 6, it is characterised in that selected image object (7) is classified, and,
For having the subsequent job of the image object of same category, for the image object of this same category, this is applied to select
The local threshold of the corresponding distribution of image object and/or tolerance (10).
8. according to the method one of aforementioned claim Suo Shu, it is characterised in that the image object (7) of printing image has rib
Limit.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DE102015207135.9 | 2015-04-20 | ||
| DE102015207135 | 2015-04-20 |
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| Publication Number | Publication Date |
|---|---|
| CN106157300A true CN106157300A (en) | 2016-11-23 |
| CN106157300B CN106157300B (en) | 2021-07-27 |
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610465033.2A Active CN106157300B (en) | 2015-04-20 | 2016-04-20 | Method for adapting an image examination by means of a computer |
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| CN (1) | CN106157300B (en) |
| DE (1) | DE102016204506A1 (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110136094A (en) * | 2018-02-06 | 2019-08-16 | 海德堡印刷机械股份公司 | Adapting to image smoothing processing |
| CN111806087A (en) * | 2019-04-01 | 2020-10-23 | 海德堡印刷机械股份公司 | Brightness-adaptive sheet inspection |
Families Citing this family (3)
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| DE102019109791A1 (en) * | 2019-04-12 | 2020-10-15 | Stephan Krebs | Device for checking print images for a printing or finishing machine and method for validating inspection algorithms of a device for checking print images |
| US10976974B1 (en) | 2019-12-23 | 2021-04-13 | Ricoh Company, Ltd. | Defect size detection mechanism |
| US11373294B2 (en) | 2020-09-28 | 2022-06-28 | Ricoh Company, Ltd. | Print defect detection mechanism |
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| CN110136094A (en) * | 2018-02-06 | 2019-08-16 | 海德堡印刷机械股份公司 | Adapting to image smoothing processing |
| CN110136094B (en) * | 2018-02-06 | 2020-11-24 | 海德堡印刷机械股份公司 | Adaptive image smoothing |
| CN111806087A (en) * | 2019-04-01 | 2020-10-23 | 海德堡印刷机械股份公司 | Brightness-adaptive sheet inspection |
| CN111806087B (en) * | 2019-04-01 | 2022-05-13 | 海德堡印刷机械股份公司 | Brightness-adaptive sheet inspection |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106157300B (en) | 2021-07-27 |
| DE102016204506A1 (en) | 2016-10-20 |
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