CN106897997B - The method of detection ring bobbin tail yarn based on Computer Image Processing and pattern-recognition - Google Patents

The method of detection ring bobbin tail yarn based on Computer Image Processing and pattern-recognition Download PDF

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Publication number
CN106897997B
CN106897997B CN201710078985.3A CN201710078985A CN106897997B CN 106897997 B CN106897997 B CN 106897997B CN 201710078985 A CN201710078985 A CN 201710078985A CN 106897997 B CN106897997 B CN 106897997B
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binary map
spool
projection
width
data
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CN106897997A (en
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敬凌霄
韩孝春
杜德平
李保仓
传波
程郑果
李丽辉
张同华
乔兴梅
徐洪
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CHONGQING SHANXIA TECHNOLOGY TEXTILE Co Ltd
Southwest University
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CHONGQING SHANXIA TECHNOLOGY TEXTILE Co Ltd
Southwest University
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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
    • G06T7/0008—Industrial image inspection checking presence/absence
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10004—Still image; Photographic image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20036—Morphological image processing
    • 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
    • G06T2207/30124—Fabrics; Textile; Paper

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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)
  • Treatment Of Fiber Materials (AREA)

Abstract

A method of the detection ring bobbin tail yarn based on Computer Image Processing and pattern-recognition, including, acquire spool image pattern, binary map is generated to spool image preprocessing, extracts binary map feature, makes binary map feature database, it is incoming to handle spool image, binary map is generated to spool image preprocessing need to be handled, extraction need to handle binary map feature, judge to handle whether binary map feature meets feature planting modes on sink characteristic.First, the management in modern textile factory by the non-professional practitioner of only a few to several spinning frames in workshop may be implemented in the present invention.It reduces enterprise and employs people's quantity, while improving the efficiency of the process.Second, the Image Acquisition tool that the present invention uses is common camera, low in cost without hardware device is additionally added to system.Third, the method for the present invention can whether there is tail yarn in automatic identification and feedback image, not need manual intervention, using being simple and efficient.

Description

The method of detection ring bobbin tail yarn based on Computer Image Processing and pattern-recognition
Technical field
The present invention relates to field of image recognition, and in particular to the detection spun yarn based on Computer Image Processing and pattern-recognition The method of pipe tail yarn.
Background technique
In traditional textile weaving process, the first procedure for spinning Weaving prepartion is winder (also known as doff), and task is By from spinning portion coil or reeled yarn be processed on bobbin-winding machine and meet necessarily required bobbin.Ring bobbin tail yarn is then that spun yarn is fallen When yarn, the remaining yarn on ring bobbin.Since ring bobbin needs to reuse after the completion of winder, ring bobbin is being reused Must assure that before cannot have tail yarn on ring bobbin, it is therefore desirable to be purged to the tail yarn on ring bobbin.Removing tail yarn The process to be completed before is the sorting to ring bobbin, and ring bobbin and the ring bobbin without tail yarn with tail yarn are separated. In traditional textile industry, since the tail yarn removal of ring bobbin is all that manually sorting is removed, this makes relevant industry have to Part manpower is employed to go to complete this procedure.
Computer image recognition technology has been applied in many industries at present, but and textile industry in terms of combination It studies seldom.This to have to employ manpower to go to carry out spool sorting and the processing of tail yarn in most textile company.So that raw It produces efficiency to be difficult to be promoted always, causes the bottleneck of Textile Enterprise Information, production automation.If computer technology can be combined The identification and relevant sorting work that are accomplished manually ring bobbin tail yarn are replaced with digital image processing techniques, this will be effectively Promote the improved efficiency of textile industry.
Summary of the invention
In view of the deficiencies of the prior art, the present invention proposes a kind of detection based on Computer Image Processing and pattern-recognition is thin The method of spool tail yarn, specific as follows:
A method of the detection ring bobbin tail yarn based on Computer Image Processing and pattern-recognition, it is characterised in that: S1: Spool image of the acquisition without containing yarn is as standard spool image pattern；
S2: binary map is generated to the spool image preprocessing；
S3: the binary map is projected in vertical direction, obtains the width data of total upright projection；
S4: the width data of total upright projection is stored in total Database as reference data；
S5: the binary map is uniformly divided at least three sections, three sections of binary maps are respectively perpendicular direction projection, are obtained First projection width's data, second projection width's data and third projection width data；
S6: respectively using first projection width data, second projection width's data and third projection width data as Reference data is stored in first database, the second database and third database；
S7: the incoming spool image that need to be handled, and according to S2It is handled；
S8: by S7Obtained in total upright projection width data compared with the reference data in total Database, if always Upright projection data are greater than the reference data in total Database, then are judged as containing yarn, otherwise enter S9；
S9: the spool that need to be handled uniformly is divided at least three sections, which corresponds to S6In database, And three sections of binary maps are respectively perpendicular direction projection, respectively obtain three sections of new binary map upright projection width datas；
S10: by three sections of new binary map upright projection data respectively with corresponding first database, the second database It is compared with third database, in three sections of new binary map upright projection data, the upright projection of either segment binary map is wide Degree is then judged as containing yarn, is otherwise judged as without yarn according to the reference data for being greater than correspondence database.
Further: the S2Including,
S21: gray processing and binary conversion treatment are carried out to the spool image, obtain bianry image；
S22: to the bianry image noise reduction process；
S23: determine position of the spool in binary map；
S24: the spool position in the bianry image is corrected, so that spool axial direction and the binary map bottom Side is vertical.
Further: the S24Including,
S241: it the spool is rotated clockwise 1 degree in binary map, obtains the 4th upright projection, will then not rotate The spool rotates 1 degree counterclockwise in binary map, obtains the 5th upright projection.
S242If: the width of the 4th upright projection is greater than the width of the 5th upright projection, judges the spool in two-value It is biased as right avertence in figure, it is counterclockwise for setting correction rotation direction, if the width of the 4th upright projection is less than the 5th upright projection Width, then judge that the spool is biased as left avertence in binary map, set correction rotation direction be clockwise.
S243: by being rotation angularly correction rotation direction deflection with 1 degree, while carrying out horizontal direction projection and vertical direction throwing Shadow is determined as the yarn when upright projection width minimum of the spool in binary map, while when floor projection width maximum Pipe axis is in binary map perpendicular to binary map bottom edge.
Further: being using the Glycerine enema and closure operation in mathematical morphology to the bianry image noise reduction process Processing.
The invention has the benefit that first, the present invention may be implemented non-professional by only a few in modern textile factory Management of the practitioner to several spinning frames in workshop.It reduces enterprise and employs people's quantity, while improving the efficiency of the process.Second, The Image Acquisition tool that the present invention uses is common camera, low in cost without hardware device is additionally added to system.The Three, the method for the present invention can whether there is tail yarn in automatic identification and feedback image, not need manual intervention, using being simple and efficient.
Detailed description of the invention
Fig. 1 is flow chart of the invention.
Specific embodiment
The preferred embodiments of the present invention will be described in detail with reference to the accompanying drawing, so that advantages and features of the invention energy It is easier to be readily appreciated by one skilled in the art, so as to make a clearer definition of the protection scope of the present invention.
A kind of method of the detection ring bobbin tail yarn based on Computer Image Processing and pattern-recognition as shown in Figure 1:, packet It includes:
S1: the spool image of yarn is not contained by camera acquisition, uploads to PC machine as standard spool image pattern；
S2: binary map is generated to spool image preprocessing, utilizes formula
Wherein, f (x, y) is the pixel value in original image, and the pixel value of g (x, y) is that treated black white image, T is ash Spend threshold value.The principle of function is, if the grey scale pixel value of image is greater than threshold value, to be set as 255, what is be less than is set as 0.
S3: binary map is projected in vertical direction, obtains the width data of total upright projection；
S4: the width data of total upright projection is stored in total Database as reference data；
S5: binary map is uniformly divided at least three sections, three sections of binary maps are respectively perpendicular direction projection, obtain the first projection Width data, second projection width's data and third projection width data can more accurately go to determine whether deposit on ring bobbin In yarn, while which section that yarn is particularly located in spool can also be determined.
S6: respectively using first projection width's data, second projection width's data and third projection width data as benchmark Data are stored in first database, the second database and third database；
S7: the incoming spool image that need to be handled, and according to S2It is handled；
S8: by S7Obtained in total upright projection width data compared with the reference data in total Database, if always Upright projection data are greater than the reference data in total Database, then are judged as containing yarn, otherwise enter S9；
S9: the spool that need to be handled uniformly is divided at least three sections, which corresponds to S6In database number, And three sections of binary maps are respectively perpendicular direction projection, respectively obtain three sections of new binary map upright projection width datas；
S10: by three sections of new binary map upright projection data respectively with corresponding first database, the second database and Three databases compare, in three sections of new binary map upright projection data, the upright projection width number of either segment binary map According to the reference data for being greater than correspondence database, then it is judged as containing yarn, is otherwise judged as without yarn.
Above-mentioned S2In include step,
S21: gray processing and binary conversion treatment are carried out to spool image, obtain bianry image；
S22: using in mathematical morphology Glycerine enema and closure operation handle to bianry image noise reduction process；
S23: determine position of the spool in binary map；
S24: the spool position in bianry image is corrected, so that spool axial direction and binary map base vertical.
Above-mentioned S24Including step,
S241: spool is rotated clockwise to 1 degree in binary map, obtains the 4th upright projection, the spool that will then not rotate It rotates 1 degree counterclockwise in binary map, obtains the 5th upright projection.
S242If: the width of the 4th upright projection is greater than the width of the 5th upright projection, judges spool in binary map Be biased as right avertence, set correction rotation direction be counterclockwise, if the width of the 4th upright projection is less than the width of the 5th upright projection Degree, then judge that spool is biased as left avertence in binary map, and it is clockwise for setting correction rotation direction.
S243: by being rotation angularly correction rotation direction deflection with 1 degree, while carrying out horizontal direction projection and vertical direction throwing Shadow is determined as that spool axis exists when upright projection width minimum of the spool in binary map, while when floor projection width maximum Perpendicular to binary map bottom edge in binary map.

Claims (4)

1. a kind of method of the detection ring bobbin tail yarn based on Computer Image Processing and pattern-recognition, it is characterised in that: S1: it adopts Spool image of the collection without containing yarn is as standard spool image pattern；
S2: binary map is generated to the spool image preprocessing；
S3: the binary map is projected in vertical direction, obtains the width data of total upright projection；
S4: the width data of total upright projection is stored in total Database as reference data；
S5: the binary map is uniformly divided at least three sections, three sections of binary maps are respectively perpendicular direction projection, obtain first Projection width's data, second projection width's data and third projection width data；
S6: respectively using first projection width data, second projection width's data and third projection width data as base value According to being stored in first database, the second database and third database；
S7: the incoming spool image that need to be handled, and according to S2It is handled；
S8: by S7Obtained in total upright projection width data compared with the reference data in total Database, if it is total vertically Data for projection is greater than the reference data in total Database, then is judged as containing yarn, otherwise enters S9；
S9: the spool that need to be handled uniformly is divided at least three sections, which corresponds to S6In database, and will Three sections of binary maps are respectively perpendicular direction projection, respectively obtain three sections of new binary map upright projection width datas；
S10: by three sections of new binary map upright projection data respectively with corresponding first database, the second database and the Three databases compare, in three sections of new binary map upright projection data, the upright projection width number of either segment binary map According to the reference data for being greater than correspondence database, then it is judged as containing yarn, is otherwise judged as without yarn.
2. the method for the detection ring bobbin tail yarn according to claim 1 based on Computer Image Processing and pattern-recognition, It is characterized in that: the S2Including,
S21: gray processing and binary conversion treatment are carried out to the spool image, obtain bianry image；
S22: to the bianry image noise reduction process；
S23: determine position of the spool in binary map；
S24: the spool position in the bianry image is corrected, is hung down so that the spool is axial with the binary map bottom edge Directly.
3. the method for the detection ring bobbin tail yarn according to claim 2 based on Computer Image Processing and pattern-recognition, It is characterized in that: the S24Including,
S241: the spool is rotated clockwise 1 degree in binary map, obtains the 4th upright projection, will then not rotate described in Spool rotates 1 degree counterclockwise in binary map, obtains the 5th upright projection；
S242If: the width of the 4th upright projection is greater than the width of the 5th upright projection, judges the spool in binary map Be biased as right avertence, set correction rotation direction be counterclockwise, if the width of the 4th upright projection is less than the width of the 5th upright projection Degree, then judge that the spool is biased as left avertence in binary map, and it is clockwise for setting correction rotation direction；
S243: by being the angular correction rotation direction deflection of rotation with 1 degree, while horizontal direction projection and vertical direction projection are carried out, when Upright projection width of the spool in binary map is minimum, while when floor projection width maximum, being determined as the yarn tube axis Line is in binary map perpendicular to binary map bottom edge.
4. the method for the detection ring bobbin tail yarn based on Computer Image Processing and pattern-recognition described in claim 2, feature It is: is Glycerine enema and the closure operation processing used in mathematical morphology to the bianry image noise reduction process.
CN201710078985.3A 2017-02-14 2017-02-14 The method of detection ring bobbin tail yarn based on Computer Image Processing and pattern-recognition Expired - Fee Related CN106897997B (en)

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CN108038858A (en) * 2017-12-26 2018-05-15 青岛大学 The recognition methods of amount of thread on yarn tube in field of textiles NI Vision Builder for Automated Inspection
CN110956656A (en) * 2019-12-17 2020-04-03 北京工业大学 Spindle positioning method based on depth target detection
CN111020766B (en) * 2019-12-19 2020-11-10 夏津仁和纺织科技有限公司 Spinning frame backward spindle searching method based on industrial camera image acquisition
CN113920086B (en) * 2021-10-09 2024-04-05 云路复合材料(上海)有限公司 Yarn state detection method and device in carbon fiber weaving process

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