CN104376573B - A kind of image smear detection method and system - Google Patents
A kind of image smear detection method and system Download PDFInfo
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- CN104376573B CN104376573B CN201410728013.0A CN201410728013A CN104376573B CN 104376573 B CN104376573 B CN 104376573B CN 201410728013 A CN201410728013 A CN 201410728013A CN 104376573 B CN104376573 B CN 104376573B
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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
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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Abstract
The present invention relates to technical field of image processing, there is provided a kind of image smear detection method and system, methods described include:The image brightness values of image intermediate region are detected;When the image brightness values of image intermediate region meet brightness value threshold range, search and determine image border line, form image smear detection zone;Image smear detection zone is traveled through by dust detection calibrated bolck, and carries out stain judgement;If the gray value of block of pixels is less than stain gray value threshold value, judgement block of pixels is non-stain block;If the gray value of block of pixels is more than or equal to stain gray value threshold value, judge that block of pixels is stain block;When the image brightness values of image intermediate region do not meet brightness value threshold range, whole image brightness value is adjusted, then continues executing with the step of forming image smear detection zone, realizes the detection to image smear, detection efficiency and detection quality are higher, reduce the fraction defective of product.
Description
Technical field
The invention belongs to technical field of image processing, more particularly to a kind of image smear detection method and system.
Background technology
Industrial camera is a key component in NI Vision Builder for Automated Inspection, and its most essential function exactly changes optical signal
Into orderly electric signal, it is also the important step in Machine Vision System Design to select suitable camera, and the selection of camera is not only
Collected image resolution ratio, picture quality etc. are directly determined, at the same it is also directly related with the operational mode of whole system.
Visualize electronic product miniaturization, high-resolution, for miniature and high-resolution state, electronic product screen
The detection of stain, not only need high resolution industrial camera, it is often more important that the image for needing to take camera carries out high quality
Algorithm Analysis, because high resolution industrial camera price is very high, then the Algorithm Analysis of the high quality of image procossing shows
Obtain particularly important.
At present, problems, such as the effect of dust detection be present to the analysis method of the image smear of industrial camera shooting
Rate is relatively low, and accuracy is not high, causes the fraction defective of product to increase.
The content of the invention
It is an object of the invention to provide a kind of image smear detection method, it is intended to solves in the prior art to industrial camera
There are problems in the analysis method of the image smear of shooting, such as dust detection is less efficient, and accuracy is not high, causes to produce
The problem of fraction defective increase of product.
The present invention is achieved in that a kind of image smear detection method, and methods described comprises the steps:
Using rectangular coordinate system, position correction is carried out to picture;
The brightness value threshold range of image intermediate region, dust detection calibrated bolck and stain gray value threshold value are carried out in advance
Definition is set;
Image intermediate region is randomly selected by the brightness value threshold range pre-set, to the image intermediate region of selection
Image brightness values carry out brightness value threshold range detection, judge the image brightness values of image intermediate region that randomly select are whether
Meet the brightness value threshold range;
When the image brightness values of the image intermediate region randomly selected meet the brightness value threshold range, search and determine
Image border line, and several pixels are moved to image inside based on described image edge line, form image smear inspection
Survey region;
Described image dust detection region is traveled through by the dust detection calibrated bolck pre-set, and will be traversed
Each block of pixels gray value compared with stain gray value threshold value set in advance, and according to comparative result carry out stain
Judge;
If the gray value of the block of pixels is less than the stain gray value threshold value, it is non-stain to judge the block of pixels
Block;
If the gray value of the block of pixels is more than or equal to the stain gray value threshold value, judge the block of pixels for stain
Block;
It is right when the image brightness values of the image intermediate region randomly selected do not meet the brightness value threshold range
Whole image brightness value is adjusted, and the image brightness values of the image intermediate region randomly selected meet the brightness value threshold
When being worth scope, while return and perform the lookup determination image border line, and based on described image edge line into image
Portion moves several pixels, the step of forming image smear detection zone.
As an improvement scheme, the image brightness values of described pair of image intermediate region randomly selected carry out brightness value
Threshold range detects, and whether the image brightness values for the image intermediate region for judging to randomly select meet the brightness value threshold range
The step of specifically include following step:
It is random to obtain image intermediate region, image brightness values detection zone is used as using this image intermediate region;
Calculate the brightness value of the image intermediate region got at random;
Judgement is compared with brightness value threshold range in the brightness value of described image intermediate region.
As an improvement scheme, it is described to utilize rectangular coordinate system, to picture carry out position correction the step of have
Body includes:
In rectangular coordinate system, the reference edge line of image is obtained;
Calculate the reference edge line and the horizontal stroke of the rectangular coordinate system or the differential seat angle of longitudinal axis datum line of image;
According to the differential seat angle, position correction is carried out to described image.
The another object of the embodiment of the present invention is a kind of image smear detecting system, and the system includes:
Module is corrected in picture position, for using rectangular coordinate system, position correction to be carried out to picture;
Pre-defined setup module, for the brightness value threshold range to image intermediate region, dust detection standard in advance
Block and stain gray value threshold value are defined setting;
Image brightness values detection module, image middle area is randomly selected for the brightness value threshold range by pre-setting
Domain, brightness value threshold range detection is carried out to the image brightness values of the image intermediate region of selection, judges the image randomly selected
Whether the image brightness values of intermediate region meet the brightness value threshold range;
Image smear detection zone forms module, for meeting when the image brightness values of the image intermediate region randomly selected
During the brightness value threshold range, search and determine image border line, and moved based on described image edge line to image inside
Several pixels are moved, form image smear detection zone;
Block of pixels stain judge module, for the dust detection calibrated bolck by pre-setting to described image dust detection
Region is traveled through, and each the block of pixels gray value traversed and stain gray value threshold value set in advance are compared
Compared with, and stain judgement is carried out according to comparative result;
Non- stain determination module, if the gray value for the block of pixels is less than the stain gray value threshold value, judge
The block of pixels is non-stain block;
Stain determination module, if the gray value for the block of pixels is more than or equal to the stain gray value threshold value, sentence
The fixed block of pixels is stain block;
Image brightness values adjusting module, for not met when the image brightness values of the image intermediate region randomly selected
During the brightness value threshold range, whole image brightness value is adjusted, the figure of the image intermediate region randomly selected
When image brightness value meets the brightness value threshold range, while return and perform performed by the dust detection region formation module
Step.
As an improvement scheme, described image brightness value detection module specifically includes:
Image intermediate region acquisition module, for obtaining image intermediate region at random, figure is used as using this image intermediate region
Image brightness value detection zone;
Brightness value computing module, for calculating the brightness value of the image intermediate region got at random;
Contrast judgement module, sentence for the brightness value of described image intermediate region to be compared with brightness value threshold range
It is disconnected.
As an improvement scheme, described image position correct module specifically include:
Reference edge line acquisition module, in rectangular coordinate system, obtaining the reference edge line of image;
Differential seat angle computing module, for calculating the reference edge line of image and the horizontal stroke or longitudinal axis benchmark of the rectangular coordinate system
The differential seat angle of line;
Module is corrected, for according to the differential seat angle, position correction to be carried out to described image.
In embodiments of the present invention, the image brightness values of the image intermediate region to randomly selecting carry out brightness value threshold value model
Enclose detection;When the image brightness values of the image intermediate region randomly selected meet the brightness value threshold range, search and determine
Image border line, and several pixels are moved to image inside based on described image edge line, form image smear inspection
Survey region;Described image dust detection region is traveled through by the dust detection calibrated bolck previously generated, and will be traversed
Each block of pixels gray value and stain gray value threshold value set in advance carry out stain judgement;If the gray scale of the block of pixels
Value is less than the stain gray value threshold value, then it is non-stain block to judge the block of pixels;If the gray value of the block of pixels is more than
Equal to the stain gray value threshold value, then judge the block of pixels for stain block;When the image intermediate region randomly selected
Image brightness values when not meeting the brightness value threshold range, whole image brightness value is adjusted, meets brightness value threshold
It is worth scope, then continues executing with the step of forming image smear detection zone, realize the detection to image smear, its detection process
The detection of producing line is directly applied to, detection efficiency and detection quality are higher, reduce the fraction defective of product, reduce human cost,
Save cost simultaneously.
Brief description of the drawings
Fig. 1 is the implementation process figure of image smear detection method provided in an embodiment of the present invention;
Fig. 2 is that the image brightness values of the image intermediate region provided in an embodiment of the present invention to randomly selecting carry out brightness value
Threshold range detects, and whether the image brightness values for the image intermediate region for judging to randomly select meet the brightness value threshold range
Specific implementation flow chart;
Fig. 3 is the realization stream provided in an embodiment of the present invention for utilizing rectangular coordinate system, position correction being carried out to picture
Cheng Tu;
Fig. 4 and Fig. 5 is the example comparison diagram that picture position provided in an embodiment of the present invention is corrected;
Fig. 6 is the structured flowchart of image smear detecting system provided in an embodiment of the present invention;
Fig. 7 is the structured flowchart of image brightness values detection module provided in an embodiment of the present invention;
Fig. 8 is the structured flowchart that module is corrected in picture position provided in an embodiment of the present invention.
Embodiment
In order to make the purpose , technical scheme and advantage of the present invention be clearer, it is right below in conjunction with drawings and Examples
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.
Fig. 1 shows the implementation process figure of image smear detection method provided by the invention, the following institute of its specific step
State:
In step S101, the image brightness values of the image intermediate region to randomly selecting carry out brightness value threshold range inspection
Survey, whether the image brightness values for the image intermediate region for judging to randomly select meet the brightness value threshold range, are to perform
Step S102, otherwise perform step S107.
In step s 102, when the image brightness values of the image intermediate region randomly selected meet the brightness value threshold value model
When enclosing, search and determine image border line, and several pixels, shape are moved to image inside based on described image edge line
Into image smear detection zone.
In this step, the step be in the picture, it is determined that corresponding image smear detection zone, the detection zone be with
On the basis of the line of image border, move inward several pixels, for example, 5-10 points pixel all can, then region is figure according to this
As dust detection region.
In step s 103, described image dust detection region is carried out by the dust detection calibrated bolck that previously generates time
Go through.
In this step, the process traveled through using dust detection calibrated bolck to image smear detection zone, it is normal
The ergodic process to image seen, as common ergodic process, will not be repeated here, but not limiting the present invention.
In step S104, each the block of pixels gray value traversed is entered with stain gray value threshold value set in advance
Row stain judges, that is, judges whether the gray value of the block of pixels is less than stain gray value threshold value, is then to perform step S105, otherwise
Perform step S106.
Wherein, the gray value of the stain is determined with a standard, i.e. stain gray value threshold value, needs to realize that definition is set herein
Put, as long as the block of pixels for being unsatisfactory for the stain gray value threshold value is all non-stain.
In step S105, if the gray value of the block of pixels is less than the stain gray value threshold value, the picture is judged
Plain block is non-stain block.
In step s 106, if the gray value of the block of pixels is more than or equal to the stain gray value threshold value, institute is judged
It is stain block to state block of pixels.
In step, the subsequent treatment to detecting stain block and non-stain block, position mark or preservation etc. can be carried out,
It will not be repeated here.
In step s 107, when the image brightness values of the image intermediate region randomly selected do not meet the brightness value
During threshold range, whole image brightness value is adjusted, meets the brightness value threshold range;
The lookup performed performed by step S102 is returned simultaneously determines image border line, and using described image edge line as base
Plinth moves several pixels to image inside, the step of forming image smear detection zone.
In embodiments of the present invention, before above-mentioned steps S101 is performed, it is also necessary to be beforehand with following work:
The brightness value threshold range of image intermediate region, dust detection calibrated bolck and stain gray value threshold value are carried out in advance
Definition is set, wherein:
The setting of the brightness value threshold range of image intermediate region, can be according to the setting of programmed algorithm among image one
As region captured, its size, particular location and other items, can limit, be set in image without corresponding
Between the purpose in region be that image is pre-processed, comply with the detection of image smear, meanwhile, ensure the accurate of stain inspection
Property and efficiency, reduce product fraction defective generation;
The determination of dust detection calibrated bolck, can be according to the basic demand of image pixel and the size model of more typical stain
The information such as enclose to be determined, its main purpose is to travel through image;
The setting of stain gray value threshold value can also in this area, the conventional setting of brightness of image and stain and set,
It will not be repeated here.
Fig. 2 is that the image brightness values of the image intermediate region provided in an embodiment of the present invention to randomly selecting carry out brightness value
Threshold range detects, and whether the image brightness values for the image intermediate region for judging to randomly select meet the brightness value threshold range
Specific implementation step, its is specific as follows:
In step s 201, image intermediate region is obtained at random, is detected using this image intermediate region as image brightness values
Region.
In step S202, the brightness value of the image intermediate region got at random is calculated.
In step S203, judgement is compared with brightness value threshold range in the brightness value of image intermediate region.
Wherein, the process of the adjustment judges for automatic cycle, it is possible to is not one-time-reach-place, after adjustment once, if symbol
Conjunction condition then terminates adjustment process, if it is not, step S202 is then continued executing with, until being adjusted within brightness value threshold range.
Wherein, the calculating of the brightness value for the image intermediate region that embodiment provides and the process judged, are for convenience of follow-up
Stain analysis detection, to improve the accuracy of detection, reduces the fraction defective of product.
In embodiments of the present invention, it is above-mentioned right for the accuracy and efficiency of the detection to image smear further
The image brightness values of the image intermediate region randomly selected also include following before carrying out the step of brightness value threshold range detection
Step:
Using rectangular coordinate system, position correction is carried out to picture, wherein, it specifically includes following step, such as Fig. 3 institutes
Show:
In step S301, in rectangular coordinate system, the reference edge line of image is obtained.
In step s 302, reference edge line and the horizontal stroke of the rectangular coordinate system or the angle of longitudinal axis datum line of image are calculated
Degree is poor.
In step S303, according to differential seat angle, position correction is carried out to described image.
Wherein, it is selective for the step, i.e., if the picture is circle, then without considering, if the picture
Image is rectangle, irregular polygon etc., then needs to select the reference edge line of one of them, enter based on this
Row adjustment, wherein, the selection of the reference edge line can be according to the usual manner of the picture, such as Fig. 4 and Fig. 5 institutes
The effect shown:
By taking rectangle as an example, in Fig. 4, rectangle a top edge line and the transverse axis of standard rectangular coordinate system are into certain angle
Degree, after the step shown in above-mentioned Fig. 3, is corrected as the effect shown in Fig. 5, will not be repeated here.
Fig. 6 is the structured flowchart of image smear detecting system provided in an embodiment of the present invention, for convenience of description, in Fig. 6
Only give the part related to the embodiment of the present invention.
The image brightness values of image intermediate region of the image brightness values detection module 11 to randomly selecting carry out brightness value threshold
It is worth range detection, whether the image brightness values for the image intermediate region for judging to randomly select meet the brightness value threshold range;
When the image brightness values of the image intermediate region randomly selected meet the brightness value threshold range, image smear detection zone
Form module 12 and search determination image border line, and several pixels are moved to image inside based on described image edge line
Point, form image smear detection zone;Block of pixels stain judge module 13 is by the dust detection calibrated bolck that pre-sets to institute
Image smear detection zone is stated to be traveled through, and by each the block of pixels gray value traversed and stain gray scale set in advance
It is worth threshold value and carries out stain judgement;If the gray value of the block of pixels is less than the stain gray value threshold value, non-stain determination module
14 judge that the block of pixels is non-stain block;It is dirty if the gray value of the block of pixels is more than or equal to the stain gray value threshold value
Point determination module 15 judges the block of pixels for stain block;When the image intermediate region randomly selected image brightness values not
When meeting the brightness value threshold range, image brightness values adjusting module 16 is adjusted to whole image brightness value, meets institute
Brightness value threshold range is stated, while returns to the step performed by the execution dust detection region formation module.
In embodiments of the present invention, setup module 17 is pre-defined in advance to the brightness value threshold value model of image intermediate region
Enclose, dust detection calibrated bolck and stain gray value threshold value are defined setting.
As shown in fig. 7, image brightness values detection module 11 specifically includes:
Image intermediate region acquisition module 111 obtains image intermediate region at random, and image is used as using this image intermediate region
Brightness value detection zone;Brightness value computing module 112 calculates the brightness value of the image intermediate region got at random;Contrast judgement
Judgement is compared with brightness value threshold range in the brightness value of described image intermediate region by module 113.
In embodiments of the present invention, picture position corrects module 18 and utilizes rectangular coordinate system, and position is carried out to picture
Correct, it is specifically included:
As shown in figure 8, reference edge line acquisition module 181 in rectangular coordinate system, obtains the reference edge line of image;Angle
Spend reference edge line and the horizontal stroke of the rectangular coordinate system or the differential seat angle of longitudinal axis datum line that poor computing module 182 calculates image;
Module 183 is corrected according to the differential seat angle, position correction is carried out to described image.
The function of above-mentioned modules will not be repeated here as described in above-mentioned embodiment of the method.
In embodiments of the present invention, the image brightness values of the image intermediate region to randomly selecting carry out brightness value threshold value model
Enclose detection;When the image brightness values of the image intermediate region randomly selected meet the brightness value threshold range, search and determine
Image border line, and several pixels are moved to image inside based on described image edge line, form image smear inspection
Survey region;Described image dust detection region is traveled through by the dust detection calibrated bolck previously generated, and will be traversed
Each block of pixels gray value and stain gray value threshold value set in advance carry out stain judgement;If the gray scale of the block of pixels
Value is less than the stain gray value threshold value, then it is non-stain block to judge the block of pixels;If the gray value of the block of pixels is more than
Equal to the stain gray value threshold value, then judge the block of pixels for stain block;When the image intermediate region randomly selected
Image brightness values when not meeting the brightness value threshold range, whole image brightness value is adjusted, meets brightness value threshold
It is worth scope, then continues executing with the step of forming image smear detection zone, realize the detection to image smear, its detection process
The detection of producing line is directly applied to, detection efficiency and detection quality are higher, reduce the fraction defective of product, reduce human cost,
Save cost simultaneously.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all essences in the present invention
All any modification, equivalent and improvement made within refreshing and principle etc., should be included in the scope of the protection.
Claims (6)
1. a kind of image smear detection method, it is characterised in that methods described comprises the steps:
Using rectangular coordinate system, position correction is carried out to picture;
The brightness value threshold range of image intermediate region, dust detection calibrated bolck and stain gray value threshold value are defined in advance
Set;
Image intermediate region is randomly selected by the brightness value threshold range pre-set, to the figure of the image intermediate region of selection
Image brightness value carries out brightness value threshold range detection, and whether the image brightness values for the image intermediate region for judging to randomly select meet
The brightness value threshold range;
When the image brightness values of the image intermediate region randomly selected meet the brightness value threshold range, search and determine image
Edge line, and several pixels are moved to image inside based on described image edge line, form image smear detection zone
Domain;
Described image dust detection region is traveled through by the dust detection calibrated bolck pre-set, and it is every by what is traversed
One block of pixels gray value carries out stain according to comparative result and sentenced compared with stain gray value threshold value set in advance
It is disconnected;
If the gray value of the block of pixels is less than the stain gray value threshold value, it is non-stain block to judge the block of pixels;
If the gray value of the block of pixels is more than or equal to the stain gray value threshold value, judge the block of pixels for stain block;
When the image brightness values of the image intermediate region randomly selected do not meet the brightness value threshold range, to whole
Image brightness values are adjusted, when the image brightness values of the image intermediate region randomly selected meet the brightness value threshold value
During scope, while return to described search and determine image border line, and moved based on described image edge line to image inside
Several pixels, formed image smear detection zone the step of.
2. image smear detection method according to claim 1, it is characterised in that among the described pair of image randomly selected
The image brightness values in region carry out brightness value threshold range detection, judge the image brightness values of image intermediate region randomly selected
The step of whether meeting the brightness value threshold range specifically includes following step:
It is random to obtain image intermediate region, image brightness values detection zone is used as using this image intermediate region;
Calculate the brightness value of the image intermediate region got at random;
Judgement is compared with brightness value threshold range in the brightness value of described image intermediate region.
3. image smear detection method according to claim 1, it is characterised in that it is described to utilize rectangular coordinate system, to figure
The step of picture progress position correction, specifically includes:
In rectangular coordinate system, the reference edge line of image is obtained;
Calculate the reference edge line and the horizontal stroke of the rectangular coordinate system or the differential seat angle of longitudinal axis datum line of image;
According to the differential seat angle, position correction is carried out to described image.
4. a kind of image smear detecting system, it is characterised in that the system includes:
Module is corrected in picture position, for using rectangular coordinate system, position correction to be carried out to picture;
Pre-defined setup module, in advance to the brightness value threshold range of image intermediate region, dust detection calibrated bolck and
Stain gray value threshold value is defined setting;
Image brightness values detection module, image intermediate region is randomly selected for the brightness value threshold range by pre-setting,
Brightness value threshold range detection is carried out to the image brightness values of the image intermediate region of selection, judged among the image that randomly selects
Whether the image brightness values in region meet the brightness value threshold range;
Image smear detection zone forms module, described in meeting when the image brightness values of the image intermediate region randomly selected
During brightness value threshold range, search and determine image border line, and if mobile to image inside based on described image edge line
Dry pixel, forms image smear detection zone;
Block of pixels stain judge module, for the dust detection calibrated bolck by pre-setting to described image dust detection region
Traveled through, and by each the block of pixels gray value traversed compared with stain gray value threshold value set in advance, and
Stain judgement is carried out according to comparative result;
Non- stain determination module, if the gray value for the block of pixels is less than the stain gray value threshold value, judge described in
Block of pixels is non-stain block;
Stain determination module, if the gray value for the block of pixels is more than or equal to the stain gray value threshold value, judge institute
It is stain block to state block of pixels;
Image brightness values adjusting module, described in not met when the image brightness values of the image intermediate region randomly selected
During brightness value threshold range, whole image brightness value is adjusted, when the image of the image intermediate region randomly selected
When brightness value meets the brightness value threshold range, while return and perform described image dust detection region formation module.
5. image smear detecting system according to claim 4, it is characterised in that described image brightness value detection module has
Body includes:
Image intermediate region acquisition module, it is bright as image using this image intermediate region for obtaining image intermediate region at random
Angle value detection zone;
Brightness value computing module, for calculating the brightness value of the image intermediate region got at random;
Contrast judgement module, for the brightness value of described image intermediate region to be compared into judgement with brightness value threshold range.
6. image smear detecting system according to claim 4, it is characterised in that it is specific that module is corrected in described image position
Including:
Reference edge line acquisition module, in rectangular coordinate system, obtaining the reference edge line of image;
Differential seat angle computing module, for calculating the horizontal stroke or longitudinal axis datum line of the reference edge line of image and the rectangular coordinate system
Differential seat angle;
Module is corrected, for according to the differential seat angle, position correction to be carried out to described image.
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CN106412573B (en) * | 2016-10-26 | 2019-02-15 | 歌尔科技有限公司 | A kind of method and apparatus of detector lens stain |
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Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103366358A (en) * | 2012-03-30 | 2013-10-23 | Ncr公司 | Stain detection |
CN104143185A (en) * | 2014-06-25 | 2014-11-12 | 东软集团股份有限公司 | Blemish zone detecting method |
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-
2014
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Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103366358A (en) * | 2012-03-30 | 2013-10-23 | Ncr公司 | Stain detection |
CN104143185A (en) * | 2014-06-25 | 2014-11-12 | 东软集团股份有限公司 | Blemish zone detecting method |
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