CN107229960A - A kind of label classified for heparin tube and its recognition methods - Google Patents
A kind of label classified for heparin tube and its recognition methods Download PDFInfo
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- CN107229960A CN107229960A CN201710559412.2A CN201710559412A CN107229960A CN 107229960 A CN107229960 A CN 107229960A CN 201710559412 A CN201710559412 A CN 201710559412A CN 107229960 A CN107229960 A CN 107229960A
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- point pixel
- heparin tube
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K19/00—Record carriers for use with machines and with at least a part designed to carry digital markings
- G06K19/06—Record carriers for use with machines and with at least a part designed to carry digital markings characterised by the kind of the digital marking, e.g. shape, nature, code
- G06K19/06009—Record carriers for use with machines and with at least a part designed to carry digital markings characterised by the kind of the digital marking, e.g. shape, nature, code with optically detectable marking
- G06K19/06037—Record carriers for use with machines and with at least a part designed to carry digital markings characterised by the kind of the digital marking, e.g. shape, nature, code with optically detectable marking multi-dimensional coding
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K7/00—Methods or arrangements for sensing record carriers, e.g. for reading patterns
- G06K7/10—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation
- G06K7/10544—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation by scanning of the records by radiation in the optical part of the electromagnetic spectrum
- G06K7/10712—Fixed beam scanning
- G06K7/10722—Photodetector array or CCD scanning
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K7/00—Methods or arrangements for sensing record carriers, e.g. for reading patterns
- G06K7/10—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation
- G06K7/14—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
- G06K7/1404—Methods for optical code recognition
- G06K7/1408—Methods for optical code recognition the method being specifically adapted for the type of code
- G06K7/1417—2D bar codes
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K7/00—Methods or arrangements for sensing record carriers, e.g. for reading patterns
- G06K7/10—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation
- G06K7/14—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
- G06K7/1404—Methods for optical code recognition
- G06K7/146—Methods for optical code recognition the method including quality enhancement steps
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- Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Electromagnetism (AREA)
- General Health & Medical Sciences (AREA)
- Health & Medical Sciences (AREA)
- Toxicology (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Quality & Reliability (AREA)
- Image Analysis (AREA)
- Measuring And Recording Apparatus For Diagnosis (AREA)
Abstract
A kind of label classified for heparin tube, it is characterised in that：The label is covered on the surface of heparin tube, and two adjacent sides of label are provided with identification starting point pixel bars, and the long side in side is short, is recognizing that the region of starting point pixel bars is set to classified pixels fill area to fill classified pixels close to two sides.The present invention when printing detects blood project can the direct corresponding characteristic of division pixel of setting of printing, without additionally to system progress HardwareUpgring, and these characteristic of division pixels can save as printing template with the blood project to be printed, simply and conveniently.The invention also discloses the recognition methods of the label.
Description
Technical field
The present invention relates to a kind of label classified for heparin tube and its recognition methods.
Background technology
Clinical and outpatient service heparin tube species is a lot, generally can adopt skull and label color by vacuum to represent in heparin tube
Additive types are different with experimental use, that is, can generally adopt skull and label color by vacuum to distinguish the purposes of heparin tube
And the blood correspondence blood project to be detected is deposited in pipe, but there is difference in each hospital again when implementing, therefore, in reality
Depend merely on that skull is adopted in identification and label color management is got up and disunity in Ji Ge hospitals, and depend merely on manual identified label substance to adopting
The working strength of the classificating requirement of blood vessel is again very high, and manual sort's speed is again slow.
At present for recognizing the classification of heparin tube, relatively common is using heparin tube to store classifiedly device in outpatient service, that is, is existed
Collected blood is corresponded into detection project identical during blood sampling to be positioned in same receptacle, between such receptacle just
It is easily discriminated, for example China Patent Publication No.：205633452U heparin tube stores classifiedly device, but when clinical, many blood samplings
Pipe is controlled oneself by sufferer or medical care is placed in a box, and typically a variety of detection projects mix, and this is accomplished by people's work point
Class is also cumbersome, though there is one kind to classify automatically, such as China Patent Publication No.：1260097 heparin tube pretreatment
Device, attaching unit is also needed on label and is matched somebody with somebody with battery limits, equipment price height does not say that label is also needed in addition under the prior system
Upgrading, compatibility is not good.
The content of the invention
The invention provides one kind is simple in construction, without carrying out the label of additional upgrade to existing label, and it is also disclosed
Its recognition methods.
The technical scheme that the present invention to be solved problem is as follows：
A kind of label classified for heparin tube, it is characterised in that：The label is covered on the surface of heparin tube, and label is adjacent
Two sides are provided with identification starting point pixel bars, and the long side in side is short, set in the region that starting point pixel bars are recognized close to two sides
It is classified pixels fill area to fill classified pixels.
The identification starting point pixel bars can be positioned only at the side of label.
Recognize that starting point pixel bars are provided with side slat, side slat extends from identification starting point pixel bars to side.
A kind of recognition methods for the label classified for heparin tube, it is characterised in that：Including a shooting input, with shooting
Provided with dynamic in input connected PC or embedded computer, the client in PC or embedded computer, client
State image capture module, image comparison module and result output module；Recognition methods is as follows：
1st, shooting input is imaged to label, and image is sent in the client in PC or embedded computer.
, the dynamic image capture module in client the image for imaging input transmission is caught, and by seizure
Image reaches image comparison module.
, image comparison module increase picture brightness, slacken the pixel interference beyond feature collected by image, such as background text
Word etc..
, image comparison module carry out RGB curves again to picture and increase dark, highlight characteristic portion.
, to characteristic portion, that is, recognize the identification of starting point pixel bars and classified pixels, only calculate classified pixels to label phase
The distance of the intersection point of adjacent both sides identification starting point pixel bars, or increase classified pixels recognize starting point pixel bars vertical range to a certain
Ratio between several persons, passing ratio numerical value is matched with the numerical value being located in image comparison module, finally serious forgiveness 2% ~
Comparing result is drawn between 5%, and sends structure to result output module.
, result output module can transmit result or signal to external device, label is classified by external device.
Beneficial effects of the present invention are as follows：
Compared with prior art, using the label of the present invention, directly setting of printing it can be corresponded to when printing detects blood project
Characteristic of division pixel, without additionally carrying out HardwareUpgring to system, and these characteristic of division pixels can be with to be printed
Blood project saves as printing template, simply and conveniently.
Compared with prior art, using the label identification method of the present invention, it is not necessary to complicated algorithm, it is only necessary to feature
Pixel calculates its distance proportion, and discrimination is high, and hardware requirement is low, and later stage scalability is good.
Brief description of the drawings：
Fig. 1 is the structural representation of label of the present invention；
Construction module figure when Fig. 2 is tag recognition of the present invention.
Detailed elaboration is made to the present invention below in conjunction with the accompanying drawings.
Refering to Fig. 1, a kind of label classified for heparin tube, the label 1 is covered on the surface of heparin tube, the phase of label 1
Two adjacent sides are provided with identification starting point pixel bars 1a, 1b, and the long side in side is short, and starting point pixel bars are being recognized close to two sides
1a, 1b region are set to classified pixels fill area 1c to fill classified pixels.Classified pixels fill area 1c is set according to grid
Put, classified pixels are filled in grid, grid region can be filled up during filling, can also be filled out with round dot in the middle of grid, institute
Account for size to be advisable more than more than 50%, different grid filling classified pixels represent the blood in the heparin tube that label is pasted
The liquid project to be detected.Set grid can x1 ~ x5 as shown in Figure 1, y1 ~ y5, z1 ~ z5, p1 ~ p5 has 20 lattice altogether, by reality
It is required to increase or decrease lattice number, can be according to equipment because some blood testing projects are to use same equipment in detection
It is adjusted with reference to required detection project, also, even 20 lattice, in identification, wherein more than 1 lattice such as 2 lattice, 3 lattice
Deng can be considered as a classified pixels fill area.
The identification starting point pixel bars can be positioned only at the side of label.Namely only identification starting point pixel bars 1a or
Recognize to be pixel 1b, a side is only stayed in two sides.
Recognize that 1a, 1b are provided with side slat 1d in starting point pixel bars, starting point pixel bars 1a, 1b are upper prolongs to side from identification by side slat 1d
Stretch.When only with an identification starting point pixel bars, side slat 1d can also play a part of a location feature.
For label 1, identification starting point pixel bars 1a, 1b and classified pixels between any two with distance position with
The relation of distance, these relations are all specific, in the case where surveyed project is less, by identification starting point pixel bars 1a or identification
Starting point pixel bars 1b can just reach the purpose of identification with classified pixels.
Refering to Fig. 1, Fig. 2, a kind of recognition methods for the label classified for heparin tube, including a shooting input 2, with taking the photograph
In PC3 or embedded computer that picture input 2 is connected, the client 4 in PC3 or embedded computer, client 4
Provided with dynamic image capture module 41, image comparison module 42 and result output module 43；Recognition methods is as follows：
1st, shooting input 2 is imaged to label 1, and image is sent in the client 4 in PC3 or embedded computer.
2nd, the dynamic image capture module 41 in client 4 is caught the image that shooting input 2 is transmitted, and will be caught
The image caught reaches image comparison module 42.
3rd, the increase of image comparison module 42 picture brightness, slackens the pixel interference beyond feature collected by image, such as carries on the back
Scape word etc..
4th, image comparison module 42 carries out the increasing of RGB curves to picture secretly again, highlights characteristic portion.
5th, to characteristic portion, that is, the identification of starting point pixel bars 1a, 1b and classified pixels point is recognized, classified pixels are only calculated
（Such as y3）The intersection point 1e of starting point pixel bars 1a, 1b is recognized to the adjacent both sides of label 1（For y3 to 1e air line distance）Or increase
Classified pixels（Such as y3）With the classified pixels point（Such as y3）To a certain identification starting point pixel bars (1a or 1b) vertical range（Y3 is extremely
1a, then be y1 ~ y3 length；Y3 to 1b, then be y3 to x3 length）Ratio between several persons, passing ratio numerical value is with being located at
Numerical value in image comparison module is matched, and is finally obtained a result between serious forgiveness 2% ~ 5%, and send structure to result
Output module.
6th, result output module can transmit result or signal to external device, and label is classified by external device.
In identification step 5 of the present invention serious forgiveness 2% ~ 5% set essentially consist in label be pasted on blood sampling pipe surface when
It is curved, is pasted if label is level, so in the horizontal direction, the side as where identification starting point pixel bars 1b is
Horizontal direction, then the classified pixels such as y3 on side to classified pixels fill area 1c where identification starting point pixel bars 1a is from just
Being seen on top will seem shorter than original, and 2% serious forgiveness represents the ratio of y1 ~ y3 distance and will shortened in this case
Just there is a fault-tolerant scope in ratio, and if side and horizontal direction where identification starting point pixel bars 1b are in 60 degree
Angle, so, not only recognize classified pixels such as y3 on the side to classified pixels fill area 1c where starting point pixel bars 1a from
Seen on surface and seem shorter than original, and identification starting point pixel bars 1b to classified pixels y3 can also seem shorter than original, now
5% it is fault-tolerant just can be very good solve this problem.
Certainly, note that, 2% ~ 5% serious forgiveness is not absolute, by data, is filled out in classified pixels
Area 1c is filled the lattice size of classified pixels can be very good to reach low fault-tolerant, high accurately purpose, that is if region table
When the lattice number of lattice is reduced to several lattice, such as only four projects, then serious forgiveness can be controlled between 0 ~ 2%.Here showed
Fault-tolerant principle is expected based on the present invention.
If the angle that certain label 1 is pasted onto on heparin tube is more than 60 degree, label 1 has been pasted not expected interior thinner
Heparin tube, camera input 2 take the photograph picture be possible to classified pixels further away from identification starting point pixel bars 1a or 1b when, such as
P5 points, then be possible to there is a situation where identification less than such a situation is not within the scope of the solution of the present invention, certainly rear
Invention thinking of the phase based on the present invention, adds second shooting input, by rolling heparin tube, first camera input
The image after lower identification starting point pixel bars 1a or 1b and joint 1e occur is grabbed to occur being taken the photograph by second again to classified pixels point
As input is grabbed down, the time between the two, the distance between several persons when drawing rolling by heparin tube caliber, but can so increase
The complexity of addition sheet and software end.
Claims (4)
1. a kind of label classified for heparin tube, it is characterised in that：The label is covered on the surface of heparin tube, and label is adjacent
Two sides provided with identification starting point pixel bars, and the long side in side is short, is recognizing that the region of starting point pixel bars is set close to two sides
Classified pixels fill area is set to fill classified pixels.
2. a kind of label classified for heparin tube according to claim 1, it is characterised in that：The identification starting point pixel
Bar can be positioned only at the side of label.
3. a kind of label classified for heparin tube according to claim 1 or 2, it is characterised in that：Recognize starting point pixel
Bar is provided with side slat, and side slat extends from identification starting point pixel bars to side.
4. a kind of recognition methods for the label classified for heparin tube, it is characterised in that：It is defeated with imaging including a shooting input
Enter in end connected PC or embedded computer, the client in PC or embedded computer, client provided with dynamic
Image capture module, image comparison module and result output module；Identification step is as follows：
One, shooting input is imaged to label, and image is sent in the client in PC or embedded computer；
Two, the dynamic image capture module in client is caught the image for imaging input transmission, and by the figure of seizure
As reaching image comparison module；
Three, image comparison module increase picture brightness slackens the pixel interference beyond feature collected by image, such as background text
Deng；
Four, image comparison module carries out RGB curves to picture and increased secretly again, highlights characteristic portion；
Five, to characteristic portion, that is, the identification of starting point pixel bars and classified pixels point is recognized, only calculate classified pixels to label phase
The distance of the intersection point of adjacent both sides identification starting point pixel bars, or increase classified pixels recognize starting point pixel bars vertical range to a certain
Ratio between several persons, passing ratio numerical value is matched with the numerical value being located in image comparison module, finally serious forgiveness 2% ~
Comparing result is drawn between 5%, and sends structure to result output module；
Six, as a result the transmittable result of output module or signal are classified to external device by external device to label.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710559412.2A CN107229960A (en) | 2017-07-11 | 2017-07-11 | A kind of label classified for heparin tube and its recognition methods |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710559412.2A CN107229960A (en) | 2017-07-11 | 2017-07-11 | A kind of label classified for heparin tube and its recognition methods |
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| Publication Number | Publication Date |
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| CN107229960A true CN107229960A (en) | 2017-10-03 |
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710559412.2A Pending CN107229960A (en) | 2017-07-11 | 2017-07-11 | A kind of label classified for heparin tube and its recognition methods |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107693357A (en) * | 2017-09-18 | 2018-02-16 | 余军辉 | Infusion pump packs and the shelf-life reference disk(-sc) using the packaging bag injection |
| CN111268230A (en) * | 2020-03-16 | 2020-06-12 | 广西华度医用器材有限公司 | Multi-tube type blood collection tube labeling machine and labeling method |
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| CN106372556A (en) * | 2016-08-30 | 2017-02-01 | 西安小光子网络科技有限公司 | Optical label identification method |
| CN106570549A (en) * | 2016-10-28 | 2017-04-19 | 网易（杭州）网络有限公司 | Coding pattern generation and identification methods and coding pattern generation and identification devices |
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2017
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Patent Citations (5)
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| US20060153475A1 (en) * | 2005-01-13 | 2006-07-13 | Ruggiero Carl J | Video processing system and method with dynamic tag architecture |
| CN101726612A (en) * | 2008-10-31 | 2010-06-09 | 希森美康株式会社 | Specimen processing apparatus |
| CN106326619A (en) * | 2015-07-01 | 2017-01-11 | 上海创司杰医疗科技有限公司 | Intelligent blood collection management system |
| CN106372556A (en) * | 2016-08-30 | 2017-02-01 | 西安小光子网络科技有限公司 | Optical label identification method |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107693357A (en) * | 2017-09-18 | 2018-02-16 | 余军辉 | Infusion pump packs and the shelf-life reference disk(-sc) using the packaging bag injection |
| CN111268230A (en) * | 2020-03-16 | 2020-06-12 | 广西华度医用器材有限公司 | Multi-tube type blood collection tube labeling machine and labeling method |
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