CN106903075A - A kind of vamp logo multi-directional visions detection method and system - Google Patents

A kind of vamp logo multi-directional visions detection method and system Download PDF

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Publication number
CN106903075A
CN106903075A CN201710282797.2A CN201710282797A CN106903075A CN 106903075 A CN106903075 A CN 106903075A CN 201710282797 A CN201710282797 A CN 201710282797A CN 106903075 A CN106903075 A CN 106903075A
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shoes
vamp
module
logo
detection
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张美杰
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Foshan Nanhai Guangdong Technology University CNC Equipment Cooperative Innovation Institute
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Foshan Nanhai Guangdong Technology University CNC Equipment Cooperative Innovation Institute
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Publication of CN106903075A publication Critical patent/CN106903075A/en
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
    • B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
    • B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
    • B07C5/34—Sorting according to other particular properties
    • B07C5/342—Sorting according to other particular properties according to optical properties, e.g. colour
    • B07C5/3422—Sorting according to other particular properties according to optical properties, e.g. colour using video scanning devices, e.g. TV-cameras
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
    • G01N21/956—Inspecting patterns on the surface of objects
    • G01N21/95607—Inspecting patterns on the surface of objects using a comparative method

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  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Chemical & Material Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Biochemistry (AREA)
  • General Health & Medical Sciences (AREA)
  • General Physics & Mathematics (AREA)
  • Immunology (AREA)
  • Pathology (AREA)
  • Image Analysis (AREA)

Abstract

The present invention relates to a kind of vamp logo multi-directional visions detection method and system, method is shunted including (1) shoes；(2) IMAQ；(3) image detection classification；(4) shoes interflow；(5) sorting is sorted out.The detection of present invention computer vision replaces manual detection, greatly reduces labour cost and workload, can also be carried out without experienced person's detection, and objectivity is strong；In addition, two shoes are separated, every shoes individually use the multiple multi-faceted detection of CCD industrial cameras, it is ensured that the false drop rate and loss of shoes logo are relatively low.

Description

A kind of vamp logo multi-directional visions detection method and system
Technical field
The present invention relates to the technical field of shoes detection, more particularly to a kind of vamp logo multi-directional vision detection methods And system.
Background technology
China is a footwear big trading nation, and annual footwear export volume accounts for 30% of total output or so, be footwear export volume most Many countries, and growth trend year by year is presented.Used as Chinese tradition industry, the quality testing of shoes is always the pain of the sector Point.The missing of logo and dislocation all can cause to have a strong impact on to the outward appearance of shoes and quality, hinder it to sell.For a long time, footwear Class logo detections are general by being accomplished manually, and manual detection relies primarily on the experience of reviewer, and subjectivity is strong, causes evaluation criterion It is inconsistent, flase drop and missing inspection are often produced, even if skilled reviewer can only also have found about 70% logo defects.Separately Outward, footwear logo defects detections are a heavy manual labor, the eyesight of very big damage survey workman for workman.Cause Footwear are carried out defects detection by this using vision instead of human eye, the inexorable trend as Chinese shoemaking development.
However, different from the defects detection of other industry, vamp logo distributions are more and irregular, if every to vamp respectively Logo defects are individually detected at individual position, then workload is extremely huge, and hardware is difficult layout.
The content of the invention
It is an object of the invention to overcome the deficiencies in the prior art, there is provided a kind of labour cost is low, can substantially reduce work Amount, objectivity are strong, false drop rate and the low vamp logo multi-directional vision detection methods of loss.
To achieve the above object, technical scheme provided by the present invention is：Method is comprised the following steps：
(1) shoes of left and right two of a pair of product shoes to be detected are branched to two different detection stations by diverter module；
The vamp image of shoes corresponding to image capture module Real-time Collection on (2) two detection stations；
Image processing module on (3) two detection stations carries out defects detection and classification to the vamp image for collecting, Testing result generation is reported and stored；
(4) the shoes interflow that interflow module has detected separate two is together；
(5) sorting module sorts out simultaneously the product shoes of different logo defects according to the testing result of image processing module Sort out.
Further, the image capture module in the step (2) on two detection stations is using multiple CCD industry phases Machine corresponds to side toe-cap and heel, left and right sides vamp, upside upper of a shoe and vamp before and after shoes respectively, comprehensive so as to reach shoes The purpose of defects detection.
Further, step (2) the vamp IMAQ is concretely comprised the following steps：Detection station is reached after shoes are shunted When, photoelectric sensor is triggered, after servomotor receives signal, the LED light source that driving is fixed with CCD industrial cameras declines, and has treated Complete covering selectively trigger each detecting position CCD industrial cameras after shoes and taken pictures.
Further, step (3) image procossing is comprised the following steps that：
1) masterplate is chosen：
A) color space conversion；
B the ROI region where) choosing all logo of vamp, generates template；
C) selected template is preserved to PC ATLs, as the standard form of subsequent match；
2) stencil matching：
A) color space conversion；
B) the similarity degree of measurement subregion and To Template；
C) Optimizing Search strategy；
D calculating speed) is improved.
Further, the masterplate is chosen and is following steps with the color space conversion in stencil matching：
Image is transformed into hsv color space formula from RGB color is：
V=max
Wherein, (r, g, b) is respectively a red, green, blue coordinate for color, and between (0,1), max is the value of r, g, b Maximum in r, g, b, min is r, g, and the minimum value in b, [0,360 °] of h ∈ are the hue angle of angle, and s, l ∈ [0,1] are full With degree and brightness.
Further, step (3) the stencil matching vacuum metrics subregion and To Template similarity degree are calculated as follows：
Template T (m × n pixel) is overlayed into searched figure S (W × H pixel) upper and lower translation, template covering search graph Subgraph region Sij, wherein, i, j are subgraph SijCoordinate of the upper left corner on search graph S；By comparing the similitude of T and S, degree Quantum region and the similarity degree of To Template.
Further, Optimizing Search strategy is specific as follows in step (3) template matches：According to measurement subregion and mesh The coefficient correlation that mark template similarity degree is obtained, in search, if the coefficient correlation of current location is less than certain threshold value or is somebody's turn to do Position is far from the target's center of previous frame, and the step-length of search will be increased, otherwise then reduce step-size in search.
Further, calculating speed is improved in step (3) template matches specific as follows：Take error threshold E0, work as E (i, j) ＞ E0When, stop the calculating of the point, continue subsequent point and calculate, so as to obtain desired result；The error calculation formula It is as follows：Wherein, masterplate T has m × n pixel, SijFor template is covered The subgraph region of lid search graph, i, j are subgraph SijCoordinate of the upper left corner on search graph S.
To achieve the above object, the present invention additionally provides one kind for realizing above-mentioned vamp logo multi-directional visions detection side The system of method, system includes diverter module, image capture module, image processing module, interflow module and sorting module；
The shoes of left and right two of a pair of product shoes to be detected are branched to two different detection stations by diverter module；
Image capture module, the vamp image of corresponding shoes on two detection stations of Real-time Collection；
Image processing module, the vamp image to being collected on two detection stations carries out defects detection and classification, and will Testing result generation report；
Interflow module, the shoes interflow that separate two have been detected is together；
The product shoes of different logo defects are sorted out and returned by sorting module, the testing result according to image processing module Class；
Wherein, described image processing module includes software interface display module, image processing algorithm unit and database list Unit；
Software interface display module, for man-machine interaction and finally by the position of shoes logo defects and type generation detection Report；
Image processing algorithm unit, defects detection and classification are carried out by algorithm to the vamp image for collecting；
Database Unit, stores the examining report on shoes logo defective locations and type.
Further, described image acquisition module include LED light source, multiple CCD industrial cameras, Z axis servo module and Servomotor；Wherein, LED light source is spherical semiclosed case, and bottom opens, and light source side wall is provided with multiple for fixing CCD industry The fixing hole of camera, corresponds to multiple detecting positions of product shoes respectively；The Z axis servo module is connected with LED light source, is placed in Z axis Servomotor above servo module drives the Z axis servo module to drive LED light source to realize vertical direction elevating movement.
Compared with prior art, this programme principle and advantage is as follows：
Detected with computer vision and replace manual detection, labour cost and workload are greatly reduced, without experienced Personnel's detection can also be carried out, and objectivity is strong；In addition, two shoes are separated, every shoes individually use multiple CCD industrial cameras Multi-faceted detection, it is ensured that the false drop rate and loss of shoes logo are relatively low.
Brief description of the drawings
Fig. 1 is a kind of structural representation of vamp logo multi-directional vision detecting systems of the embodiment of the present invention；
Fig. 2 is the structure of image capture module in a kind of vamp logo multi-directional vision detecting systems of the embodiment of the present invention Figure；
Fig. 3 is a kind of workflow diagram of vamp logo multi-directional vision detection methods of the embodiment of the present invention；
Fig. 4 is the image processing algorithm flow in a kind of vamp logo multi-directional vision detection methods of the embodiment of the present invention Figure.
Specific embodiment
With reference to specific embodiment, the invention will be further described：
Referring to shown in accompanying drawing 1-2, a kind of vamp logo multi-directional vision detecting systems described in the present embodiment, including shunting Module 1, image capture module 2, image processing module 3, interflow module 4 and sorting module 5.Wherein,
Image capture module 2 includes 9, five CCD industrial cameras 10 of LED light source, Z axis servo module 11 and servomotor 12；LED light source 9 is spherical semiclosed case, and bottom opens, and light source side wall is provided with five for fixing consolidating for CCD industrial cameras 10 Determine hole, five detecting positions of product shoes are corresponded to respectively；Z axis servo module 11 is connected with LED light source 9, is placed in Z axis servo module 11 The servomotor 12 of top drives the Z axis servo module 11 to drive LED light source 9 to realize vertical direction elevating movement.
Image processing module 3 includes software interface display module 6, image processing algorithm unit 7 and Database Unit 8.
Workflow is as shown in Figure 3-4, specific as follows：
(1) left and right two shoes a, b of a pair of product shoes to be detected are branched to two different detection works by diverter module 1 Position；
The vamp image of shoes corresponding to the Real-time Collection of image capture module 2 on (2) two detection stations：
When detection station is reached after shoes a, b shunting, triggering photoelectric sensor (without display in figure), servomotor 12 After receiving signal, decline the LED light source 9 for being fixed with CCD industrial cameras 10, each is selectively triggered after shoes are covered completely Detecting position CCD industrial cameras 10 are taken pictures；Five CCD industrial cameras 10 (CCD1, CCD2, CCD3, CCD4, CCD5) are right respectively Side toe-cap and heel, left and right sides vamp, upside upper of a shoe and vamp before and after shoes are answered, so as to reach the comprehensive defects detection of shoes Purpose (a CCD industrial camera of shoes b sides is blocked due to angle)；After the completion of taking pictures, servomotor 12 drives Z axis Servo module 11 drives LED light source 9 to rise；
The vamp image that image processing module 3 pairs on (3) two detection stations is collected carries out defects detection and classification, Testing result generation is reported and stored；Comprise the following steps that：
First passing through software interface display module 6 carries out man-machine interaction, then carries out defect inspection by image processing algorithm unit 7 Survey, image detection is comprised the following steps that：
1) masterplate is chosen：
A) color space conversion：
Image is transformed into hsv color space formula from RGB color is：
V=max
Wherein, (r, g, b) is respectively a red, green, blue coordinate for color, and between (0,1), max is the value of r, g, b Maximum in r, g, b, min is r, g, and the minimum value in b, [0,360 °] of h ∈ are the hue angle of angle, and s, l ∈ [0,1] are full With degree and brightness；
B the ROI region where) choosing all logo of vamp, generates template, and the ratio that logo accounts for ROI region is 40%；
C) selected template is preserved to PC ATLs, as the standard form of subsequent match：
In initialization procedure, after template is chosen, PC model libraries are saved to, as the standard form of subsequent match；Just The template of beginningization is chosen and is only carried out once, and follow-up logo detections need not be chosen again；
2) stencil matching：
A) color space conversion, the color space conversion step during the switch process is chosen with masterplate is consistent；
B) the similarity degree of measurement subregion and To Template：
Stencil matching vacuum metrics subregion and To Template similarity degree are calculated as follows：
Template T (m × n pixel) is overlayed into searched figure S (W × H pixel) upper and lower translation, template covering search graph Subgraph region Sij, wherein, i, j are subgraph SijCoordinate of the upper left corner on search graph S；By comparing the similitude of T and S, degree Quantum region and the similarity degree of To Template；
C) Optimizing Search strategy：
According to the coefficient correlation that measurement subregion and To Template similarity degree are obtained, in search, if current location Coefficient correlation is far from the target's center of previous frame less than certain threshold value or the position, and the step-length of search will be increased, otherwise then Reduce step-size in search；
D calculating speed) is improved：
Take error threshold E0, as E (i, j) ＞ E0When, stop the calculating of the point, continue subsequent point and calculate, so as to be wanted Result；The error calculation formula is as follows：Wherein, masterplate T has M × n pixel, SijThe subgraph region of search graph, i are covered for template, j is subgraph SijCoordinate of the upper left corner on search graph S；
Database Unit 8 stores the examining report of shoes logo defective locations and type.
(4) shoes that interflow module 4 has detected separate two after detection classification collaborate together；
(5) sorting module 5 sorts out the product shoes of different logo defects according to the testing result of image processing module And sort out.
The detection of the present embodiment computer vision replaces manual detection, labour cost and workload is substantially reduced, without having Personnel's detection of experience can also be carried out, and objectivity is strong；In addition, two shoes are separated, every shoes individually use multiple CCD works The multi-faceted detection of industry camera, it is ensured that the false drop rate and loss of shoes logo are relatively low.
The examples of implementation of the above are only the preferred embodiments of the invention, not limit implementation model of the invention with this Enclose, therefore the change that all shapes according to the present invention, principle are made, all should cover within the scope of the present invention.

Claims (10)

1. a kind of vamp logo multi-directional vision detection methods, it is characterised in that：Comprise the following steps：
(1) shoes of left and right two of a pair of product shoes to be detected are branched to two different detection stations by diverter module；
The vamp image of shoes corresponding to image capture module Real-time Collection on (2) two detection stations；
Image processing module on (3) two detection stations carries out defects detection and classification to the vamp image for collecting, and will examine Result generation is surveyed to report and store；
(4) the shoes interflow that interflow module has detected separate two is together；
(5) product shoes of different logo defects are sorted out and returned by sorting module according to the testing result of image processing module Class.
2. a kind of vamp logo multi-directional vision detection methods according to claim 1, it is characterised in that：The step (2) image capture module on two detection stations corresponds to side toe-cap before and after shoes respectively using multiple CCD industrial cameras With heel, left and right sides vamp, upside upper of a shoe and vamp, so as to reach the purpose of the comprehensive defects detection of shoes.
3. a kind of vamp logo multi-directional vision detection methods according to claim 1, it is characterised in that：The step (2) vamp IMAQ is concretely comprised the following steps：When detection station is reached after shoes shunting, photoelectric sensor, servo electricity are triggered After machine receives signal, the LED light source that driving is fixed with CCD industrial cameras declines, and selectively triggers each after shoes are covered completely Individual detecting position CCD industrial cameras are taken pictures.
4. a kind of vamp logo multi-directional vision detection methods according to claim 1, it is characterised in that：The step (3) image procossing is comprised the following steps that：
1) masterplate is chosen：
A) color space conversion；
B the ROI region where) choosing all logo of vamp, generates template；
C) selected template is preserved to PC ATLs, as the standard form of subsequent match；
2) stencil matching：
A) color space conversion；
B) the similarity degree of measurement subregion and To Template；
C) Optimizing Search strategy；
D calculating speed) is improved.
5. a kind of vamp logo multi-directional vision detection methods according to claim 4, it is characterised in that：The masterplate choosing Take and be following steps with the color space conversion in stencil matching：
Image is transformed into hsv color space formula from RGB color is：
s = 0 , i f max = 0 max - min max = 1 - min max , o t h e r w i s e
V=max
Wherein, (r, g, b) is respectively a red, green, blue coordinate for color, and between (0,1), max is r, g to the value of r, g, b, Maximum in b, min is r, g, and the minimum value in b, [0,360 °] of h ∈ are the hue angle of angle, and s, l ∈ [0,1] are saturation degree And brightness.
6. a kind of vamp logo multi-directional vision detection methods according to claim 4, it is characterised in that：The step (3) stencil matching vacuum metrics subregion and To Template similarity degree are calculated as follows：
R ( i , j ) = Σ m = 1 M S i j ( m , n ) × T ( m , n ) Σ m = 1 M Σ n = 1 N [ S i j ( m , n ) ] 2 Σ m = 1 M Σ n = 1 N [ T ( m , n ) ] 2 ,
Template T (m × n pixel) is overlayed into searched figure S (W × H pixel) upper and lower translation, template covers the son of search graph Graph region Sij, wherein, i, j are subgraph SijCoordinate of the upper left corner on search graph S；By comparing the similitude of T and S, measurement Region and the similarity degree of To Template.
7. a kind of vamp logo multi-directional vision detection methods according to claim 4, it is characterised in that：The step (3) Optimizing Search strategy is specific as follows in template matches：It is related to what To Template similarity degree was obtained according to measurement subregion Coefficient, in search, if the coefficient correlation of current location less than certain threshold value or the position from previous frame target's center very Far, the step-length of search will be increased, otherwise then reduce step-size in search.
8. a kind of vamp logo multi-directional vision detection methods according to claim 4, it is characterised in that：Step (3) mould It is specific as follows calculating speed to be improved in plate matching：Take error threshold E0, as E (i, j) ＞ E0When, stop the calculating of the point, continue next Point is calculated, so as to obtain desired result；The error calculation formula is as follows： Wherein, masterplate T has m × n pixel, SijThe subgraph region of search graph, i are covered for template, j is subgraph SijThe upper left corner is being searched Coordinate on rope figure S.
9. a kind of system for realizing vamp logo multi-directional vision detection methods described in claim 1, it is characterised in that：Bag Include diverter module (1), image capture module (2), image processing module (3), interflow module (4) and sorting module (5)；
The shoes of left and right two of a pair of product shoes to be detected are branched to two different detection stations by diverter module (1)；
Image capture module (2), the vamp image of corresponding shoes on two detection stations of Real-time Collection；
Image processing module (3), the vamp image to being collected on two detection stations carries out defects detection and classification, and will inspection Survey result generation report；
Interflow module (4), the shoes interflow that separate two have been detected is together；
The product shoes of different logo defects are sorted out and returned by sorting module (5), the testing result according to image processing module Class；
Wherein, described image processing module (3) includes software interface display module (6), image processing algorithm unit (7) and data Library unit (8)；
Software interface display module (6), for man-machine interaction and finally by the position of shoes logo defects and type generation detection Report；
Image processing algorithm unit (7), defects detection and classification are carried out by algorithm to the vamp image for collecting；
Database Unit (8), stores the examining report on shoes logo defective locations and type.
10. a kind of vamp logo multi-directional vision detecting systems according to claim 9, it is characterised in that：Described image Acquisition module (2) includes LED light source (9), multiple CCD industrial cameras (10), Z axis servo module (11) and servomotor (12)；Wherein, LED light source (9) is spherical semiclosed case, and bottom opens, and light source side wall is provided with multiple for fixing CCD industry phases The fixing hole of machine (10), corresponds to multiple detecting positions of product shoes respectively；The Z axis servo module (11) is with LED light source (9) even Connect, the servomotor (12) being placed in above Z axis servo module (11) drives Z axis servo module (11) to drive LED light source (9) real Existing vertical direction elevating movement.
CN201710282797.2A 2017-04-26 2017-04-26 A kind of vamp logo multi-directional visions detection method and system Withdrawn CN106903075A (en)

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CN107677682A (en) * 2017-11-07 2018-02-09 泉州创力模具有限公司 A kind of footwear mould surface damage detection device and detection method
CN108816810A (en) * 2018-07-03 2018-11-16 青岛永悦光迅技术有限责任公司 A kind of express delivery security check passage, rays safety detection apparatus and system
CN109839381A (en) * 2017-11-28 2019-06-04 宝成工业股份有限公司 The vision inspection apparatus of shoes part
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Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107677682A (en) * 2017-11-07 2018-02-09 泉州创力模具有限公司 A kind of footwear mould surface damage detection device and detection method
CN107677682B (en) * 2017-11-07 2024-03-08 泉州创力模具有限公司 Shoe mold surface damage detection device and detection method
CN109839381A (en) * 2017-11-28 2019-06-04 宝成工业股份有限公司 The vision inspection apparatus of shoes part
CN108816810A (en) * 2018-07-03 2018-11-16 青岛永悦光迅技术有限责任公司 A kind of express delivery security check passage, rays safety detection apparatus and system
CN116952303A (en) * 2023-07-27 2023-10-27 浙江卓诗尼鞋业有限公司 Comprehensive detection equipment for multiple functions of shoes
CN116952303B (en) * 2023-07-27 2024-04-30 浙江卓诗尼鞋业有限公司 Comprehensive detection equipment for multiple functions of shoes
CN117517314A (en) * 2024-01-04 2024-02-06 歌尔股份有限公司 Visual inspection apparatus
CN117517314B (en) * 2024-01-04 2024-04-30 歌尔股份有限公司 Visual inspection apparatus

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