DE19824304A1 - Apparatus for classifying pieces of leather, having a camera to scan the leather on a digitizing bed and a computer to evaluate the data - Google Patents

Apparatus for classifying pieces of leather, having a camera to scan the leather on a digitizing bed and a computer to evaluate the data

Info

Publication number
DE19824304A1
DE19824304A1 DE19824304A DE19824304A DE19824304A1 DE 19824304 A1 DE19824304 A1 DE 19824304A1 DE 19824304 A DE19824304 A DE 19824304A DE 19824304 A DE19824304 A DE 19824304A DE 19824304 A1 DE19824304 A1 DE 19824304A1
Authority
DE
Germany
Prior art keywords
leather
data
evaluation
bed
digitizing
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
DE19824304A
Other languages
German (de)
Inventor
Friedrich Roell
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
MAASS RUTH
Original Assignee
MAASS RUTH
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by MAASS RUTH filed Critical MAASS RUTH
Priority to DE19824304A priority Critical patent/DE19824304A1/en
Publication of DE19824304A1 publication Critical patent/DE19824304A1/en
Ceased legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/0002Inspection of images, e.g. flaw detection
    • G06T7/0004Industrial image inspection
    • G06T7/001Industrial image inspection using an image reference approach
    • CCHEMISTRY; METALLURGY
    • C14SKINS; HIDES; PELTS; LEATHER
    • C14BMECHANICAL TREATMENT OR PROCESSING OF SKINS, HIDES OR LEATHER IN GENERAL; PELT-SHEARING MACHINES; INTESTINE-SPLITTING MACHINES
    • C14B1/00Manufacture of leather; Machines or devices therefor
    • C14B1/28Machines for treating leather combined with devices for measuring and printing
    • CCHEMISTRY; METALLURGY
    • C14SKINS; HIDES; PELTS; LEATHER
    • C14BMECHANICAL TREATMENT OR PROCESSING OF SKINS, HIDES OR LEATHER IN GENERAL; PELT-SHEARING MACHINES; INTESTINE-SPLITTING MACHINES
    • C14B17/00Details of apparatus or machines for manufacturing or treating skins, hides, leather, or furs
    • C14B17/16Inspecting hides or furs
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/44Resins; rubber; leather
    • G01N33/447Leather
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30108Industrial image inspection
    • G06T2207/30124Fabrics; Textile; Paper

Abstract

Scanning device for evaluating pieces of leather using a digital camera. A device for classifying pieces of leather comprising a digitizing bed (12) to accommodate at least one piece of leather (36); at least one device for clamping the piece of leather (36) to the digitizing bed (12); at least one camera (14) to scan the digitizing bed (12); and an evaluation unit (16) receiving data supplied by the camera (14), containing detectors, particularly edge detectors, to determine the shape of the piece of leather, and containing a neuronal network having first stage brightness- and/or color detectors to detect irregularities in the piece of leather (36) by comparison with a reference data storage unit (18) and enabling the piece of leather to be classified as belonging to a particular quality grade. In a further claimed embodiment the evaluation unit (16) is used to program the control unit (28) of a cutter (30).

Description

The present invention relates to a device and a Procedure for classifying pieces of leather.

So far it is Classification and cutting pieces of leather a job which is done manually by more or less trained Per is made. Here, the skin is digitalized fixed bed where the contours are first removed and on be made visible to the screen. Then crosses the the person entrusted with the marking identifies the fault points of the Le derstücks on the z. B. cracks, hubs, chafing or structure door errors in the leather. Then be manual the contours of the leather to be cut on the screen of the Art inserted that the defects in the cutting waste ver stay. So far, this evaluation has been very time-consuming and personal complex and also burdened with uncertainties, because the fault investigation is not always by extremely trained Personnel is carried out and is often entered on the screen Personnel takes place who have no idea about the leather processing Has.

It is therefore an object of the present invention, a Vorrich tion and a process to create a largely self active classification of the leather pieces and possibly a direct after-treatment, e.g. B. erlau on a cutting machine ben.

The object is achieved by a device according to claim 1 and solved a method according to claim 8. Advantageous training Applications of the invention are the subject of the associated Unteran claims.

The device according to the invention comprises a digitizing bed, on which the leather piece is stretched. Furthermore, min  at least a camera to capture the area of the digitali sierbetts provided. That from the camera or cameras held image is fed to an evaluation device which for a detector, usually gray value or black / white de tectors or edge detectors, contains the contour of the Le to determine. The contour, which is also the size The information for the leather piece is saved in one file cher the evaluation device filed. Furthermore, the Evaluation device a neural network, on the first Level brightness and / or color detectors are provided with which brightness and / or color differences in that telten image can be determined. The brightness and / or color deviations of the leather based on the optical loading condition or defects such as cracks, scars and abrasion places are now compared with the starting dates in Re reference data stores, which the associated classification information included. So it is based on size, intensity, type and Frequency of identified errors an assignment of the leather taken to a quality level.

Even if the optical quality of the leather piece as Gan should be assessed and not just the fault points should be known, it is advantageous if the evaluations direction a control for the exposure of the digitizer has beds. This way either the lighting and / or the exposure by the evaluation device be put. A reference surface is preferably on for this the digitizing bed. The lighting and / or loading Light is set so that the reference surface determined value corresponds to a predetermined reference value. On this way it is ensured that always under exactly identi lighting conditions is measured. Only through this is the assessment of the optical nature of the leather piece as a whole possible.  

The assignment process of the neural network is preferred monitored and corrected in a learning phase so that the classi The data of the reference data storage is constantly changing and be adjusted. This learning can be done by known learners drive also carried out automatically with neural networks become.

The evaluation device is preferably finished processing machine, e.g. B. a cutter connected from the leather cut out the required contours. The cutter has a control system that takes into account the quali data from the evaluation device the Kon to be cut tures automatically in the contour of the leather piece without the defects are in the contours to be cut. Of the The manufacturing process can thus be automated up to the cutting stage Siert, the accuracy and reliability of the Quality mapping and error detection improved considerably can be based on the experiences that the neural network in its detection activity, especially in the learning phase, wins over time.

The invention is described below, for example, using an off management example described in the schematic drawing. In this shows

Fig. 1 is a schematic representation of a device for classifying and cutting leather pieces.

Fig. 1 shows a device 10 for classifying and cutting the pieces of leather. The device contains a digitizing bed 12 , over which a digital camera 14 is fixed. The digital camera 14 is connected to an evaluation device 16 , which has a reference data memory 18 with classification data and a data memory 20 for storing the data of detected and / or classified objects. Wei terhin is the evaluation device 16 with an input device, for. B. a keyboard 22 connected and an output device, for. B. a screen 24 . In the area of the digitizing bed 12 , a reference surface 26 is provided, by means of which an automatic exposure control takes place. With the data memory 20 of the evaluation device 16 and the evaluation device 16 itself, a controller 28 for a cutter 30 is connected, the z. B. can be designed as a laser cutting device. The cutter 30 is on a longitudinal guide 32 and arranged on both sides transverse guides 34 , controlled by the controller 28 , freely movable over the digitizing bed 12 . Both the activity and the path of the cutter 30 are controlled by the controller 28 . On the digitizing bed 12 by a suitable Aufspannvorrich device, z. B. a vacuum device or an electrostatic cal clamping device a leather piece 36 stretched.

The activity of the device 10 when detecting, classifying and cutting the leather piece will be described below.

The camera 14 captures a complete image of the digital bed 12 including the reference surface 26 . The brightness value of the reference surface 26 obtained from the camera 14 is compared with a value lying in the reference data memory 18 and the exposure of the camera 14 and / or the actuation of a lighting, not shown, is adjusted so that the brightness value of the reference surface 26 matches the reference value .

Now it is ensured that the leather piece 36 is detected under the same chen lighting conditions as previous Le derstücke. The evaluation device contains detectors, in particular special edge detectors, which detect the contour of the leather bed 36 lying on the digitizing bed 12 . Such detector detectors recognize the difference in brightness between the leather piece and the digitizing bed underneath. In this regard, the digitizing bed can be provided with special dyes or phosphors, which ensure a more precise response of the edge detectors. The contour and thus the size of the leather piece and also the location of the leather piece 36 on the digitizing bed 12 are detected by the edge detectors. By recognizing the gray value or the color value or the distribution of the gray and color value on the leather piece 36 , a first assessment regarding the optical condition of the leather piece as a whole can be made. In addition, the evaluation device contains brightness and / or color detectors, which form the first stage of a neural network. With these brightness and / or color detectors changes in the gray or color value in the leather piece, based on the total gray or color value, and evaluated in terms of their size and their gray or color value as well as their frequency in the leather piece. For this, the values obtained in the neural network can be reduced in frequency values using errors of different sizes in order to only list one type of data reduction. The error data thus obtained by the neural network are compared with error data from the reference value memory 18 , where the leather piece 36 is matched by class. The class assignment determined in this way together with the sizes and location information of the errors on the digitizing bed 12 and in the leather piece 36 are stored in a data memory 20 . In this data memory 20 , the controller 28 accesses the cutter 30 when the previous quality inspection has shown that the leather piece 36 belongs to a quality level to be used. In this case, the contours to be cut are placed by an algorithm known per se over the leather piece in such a way that the error points ascertained lie outside the contours to be cut, ie in the cutting waste. The cutting control data thus obtained are now used directly to control the operation of the cutter 30 and the longitudinal guide 32 and transverse guides 34 , which are operated by a motor. The use of a vacuum device or an electrostatic device prevents the leather piece from shifting relative to the digitizing bed 12 when it is cut.

Of course, the application of the device and that The process is not limited to pieces of leather. It can also plastic or textile pieces or other natural products classified and edited in this way, which of have a not completely homogeneous external structure in advance.

Claims (10)

1. Device for classifying pieces of leather, comprising a digitizing bed ( 12 ) for receiving at least one piece of leather ( 36 ),
at least one device for clamping the leather piece ( 36 ) on the digitizing bed ( 12 ),
at least one camera ( 14 ) for detecting the digitizing bed ( 12 ), and
an evaluation device ( 16 ) for the image provided by the camera ( 14 ), which evaluation device ( 16 ) contains detectors, in particular edge detectors, for determining the shape of the leather piece ( 36 ) and a neural network, the first stage of which is brightness and / or color detectors for determining irregularities of the leather piece ( 36 ),
the neural network classifies these irregularities by comparing them with initial data located in reference data memories ( 18 ) and assigning them to a certain quality level.
2. Device according to claim 1, characterized, that the initial data gray value and / or color data, shape, size ß data and frequency data included.
3. Apparatus according to claim 1 or 2, characterized in that the evaluation device ( 16 ) has a control for a lighting device and / or the exposure of the camera ( 14 ) which the lighting / exposure depending on egg ner in the area of the digitizing bed ( 12 ) arranged reference surface ( 26 ) controls.
4. Device according to one of the preceding claims, characterized in that the evaluation device ( 16 ) has a machine code reader for detecting markings applied to the leather piece ( 36 ).
5. The device according to claim 4, characterized in that the evaluation device ( 16 ) has a memory ( 20 ), preferably as a mobile data carrier for storing the leather piece ( 36 ) relevant classification data.
6. Device according to one of the preceding claims, characterized in that the evaluation device ( 16 ) controls a cutter ( 30 ).
7. The device according to claim 6, characterized in that a controller ( 28 ) for the cutter ( 30 ) is provided, which is connected to the evaluation device ( 16 ) via a data interface or a data memory ( 20 ), the control ( 28 ) has a circuit for optimized setting of the cuts for contours to be cut, taking into account the classification data obtained from the evaluation device ( 16 ), in particular error points.
8. Procedure for classifying leather pieces with a Device according to one of the preceding claims, in which the assignment process by the neural network in one monitored and corrected the first learning stage in the initial phase becomes.  
9. The method according to claim 8, characterized, that the initial data is modified automatically during the learning process become.
10. The method according to claim 3 and 8 or 9, characterized in that at least before the evaluation of the image by the camera ( 14 ) he holding the lighting / exposure is controlled such that the brightness value obtained on the reference surface corresponds to a predetermined reference value.
DE19824304A 1998-05-28 1998-05-28 Apparatus for classifying pieces of leather, having a camera to scan the leather on a digitizing bed and a computer to evaluate the data Ceased DE19824304A1 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
DE19824304A DE19824304A1 (en) 1998-05-28 1998-05-28 Apparatus for classifying pieces of leather, having a camera to scan the leather on a digitizing bed and a computer to evaluate the data

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
DE19824304A DE19824304A1 (en) 1998-05-28 1998-05-28 Apparatus for classifying pieces of leather, having a camera to scan the leather on a digitizing bed and a computer to evaluate the data

Publications (1)

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DE19824304A1 true DE19824304A1 (en) 1999-12-02

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Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2003076915A1 (en) * 2002-03-14 2003-09-18 Basf Aktiengesellschaft Method for conducting automated surface inspection and surface correction
DE102005050302A1 (en) * 2005-10-17 2007-04-26 Yara International Asa Method and device for non-contact determination of the current nutritional status of a crop and for processing this information on fertilizer recommendations
CN102249086A (en) * 2011-03-25 2011-11-23 江苏连港皮革机械有限公司 Leather sorting system and use method thereof
DE102013005489A1 (en) 2013-04-02 2014-10-02 Capex Invest GmbH Method and device for the automatic detection of defects in limp bodies
US10297018B2 (en) * 2017-07-14 2019-05-21 Lear Corporation Method of digitally grading leather break
EP3594666A1 (en) * 2018-07-12 2020-01-15 Aibi Dynamics Co., Ltd. Artificial intelligence-based leather inspection method and leather product production method
EP3594682A1 (en) * 2018-07-12 2020-01-15 Aibi Dynamics Co., Ltd. Leather inspection equipment

Citations (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4901359A (en) * 1985-12-14 1990-02-13 Durkopp System Technik Gmbh Method and apparatus for automatically cutting material in standard patterns
US4982437A (en) * 1987-01-20 1991-01-01 Manufacture Francaise Des Chaussures Eram Method of cutting an object as a function of particularities of said object
DE4012462C2 (en) * 1990-04-19 1992-04-30 Duerkopp Systemtechnik Gmbh, 4800 Bielefeld, De
DE4216469A1 (en) * 1992-05-19 1993-11-25 Diehl Gmbh & Co Defect classification system for skin to be used to make leather - analyses infrared radiation distribution transmitted through tanned stretched skin in wet-blue state and passed between heat-radiating quartz lamps and CCD or line camera.
DE4231222C1 (en) * 1992-09-18 1994-01-13 Duerkopp System Technik Gmbh Leather fault marking - has balls in quality zones with structured flats
DE4241990A1 (en) * 1992-12-12 1994-06-16 Rwe Entsorgung Ag Method for recognizing objects and device for carrying out the method
DE4313258A1 (en) * 1993-04-23 1994-10-27 Beiersdorf Ag Method and device for the quantitative measurement of the texture of the human skin surface by means of registration, reproduction and analysis of image information
DE4415004A1 (en) * 1993-04-30 1994-11-03 Univ Schiller Jena Arrangement and method for characterising surfaces and for characterising and classifying surface defects and near-surface defects as well as inhomogeneities in the volume of transparent media
DE3639636C2 (en) * 1986-11-20 1996-04-18 Robert Prof Dr Ing Massen Automatic inspection of textile webs
DE19609045C1 (en) * 1996-03-08 1997-07-24 Robert Prof Dr Ing Massen Optical test for wood sample using camera and image-processing system
DE19637234A1 (en) * 1996-09-13 1998-03-26 Michael F Braun Reducing optical definition for colour measurements of moving, textured, patterned objects for quality control
DE19642712A1 (en) * 1996-10-16 1998-04-23 Saechsisches Textilforsch Inst Method and device for measuring and quality evaluation of surface effects on textile webs
DE19650234C1 (en) * 1996-12-04 1998-04-30 Duerkopp Adler Ag Object for marking a selection area in a work piece, in particular an animal skin
DE19643406A1 (en) * 1996-10-21 1998-04-30 Deutsches Textilforschzentrum Fast, high resolution optical surface scanner for textile webs, etc.

Patent Citations (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4901359A (en) * 1985-12-14 1990-02-13 Durkopp System Technik Gmbh Method and apparatus for automatically cutting material in standard patterns
DE3639636C2 (en) * 1986-11-20 1996-04-18 Robert Prof Dr Ing Massen Automatic inspection of textile webs
US4982437A (en) * 1987-01-20 1991-01-01 Manufacture Francaise Des Chaussures Eram Method of cutting an object as a function of particularities of said object
DE4012462C2 (en) * 1990-04-19 1992-04-30 Duerkopp Systemtechnik Gmbh, 4800 Bielefeld, De
DE4216469A1 (en) * 1992-05-19 1993-11-25 Diehl Gmbh & Co Defect classification system for skin to be used to make leather - analyses infrared radiation distribution transmitted through tanned stretched skin in wet-blue state and passed between heat-radiating quartz lamps and CCD or line camera.
DE4231222C1 (en) * 1992-09-18 1994-01-13 Duerkopp System Technik Gmbh Leather fault marking - has balls in quality zones with structured flats
DE4241990A1 (en) * 1992-12-12 1994-06-16 Rwe Entsorgung Ag Method for recognizing objects and device for carrying out the method
DE4313258A1 (en) * 1993-04-23 1994-10-27 Beiersdorf Ag Method and device for the quantitative measurement of the texture of the human skin surface by means of registration, reproduction and analysis of image information
DE4415004A1 (en) * 1993-04-30 1994-11-03 Univ Schiller Jena Arrangement and method for characterising surfaces and for characterising and classifying surface defects and near-surface defects as well as inhomogeneities in the volume of transparent media
DE19609045C1 (en) * 1996-03-08 1997-07-24 Robert Prof Dr Ing Massen Optical test for wood sample using camera and image-processing system
DE19637234A1 (en) * 1996-09-13 1998-03-26 Michael F Braun Reducing optical definition for colour measurements of moving, textured, patterned objects for quality control
DE19642712A1 (en) * 1996-10-16 1998-04-23 Saechsisches Textilforsch Inst Method and device for measuring and quality evaluation of surface effects on textile webs
DE19643406A1 (en) * 1996-10-21 1998-04-30 Deutsches Textilforschzentrum Fast, high resolution optical surface scanner for textile webs, etc.
DE19650234C1 (en) * 1996-12-04 1998-04-30 Duerkopp Adler Ag Object for marking a selection area in a work piece, in particular an animal skin

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
ERSÜ,E.: Rationelle 100% optische Warenkontrolle der Vlies- und Textilproduktion mit der digitalen Bildverarbeitung COSS. In: textil praxis international 1994, Juni, S.425-428 *
SCHICKTANZ,K.: Automatische Warenschau. In: Textilveredlung 29, 1994, Nr.10, S.300-304 *
TSAI,I-Shou, u.a.: Erkennung von Flächengebildestrukturen durch elektronische Bildverarbeitung. In: Melliand Textilberichte 1, 1993, S.77-80 *
VEIT,Dieter, u.a.: Einsatz der digitalen Bildverarbeitung zur Optimierung des Öffnungs- und Reinigungsprozesses. In: Melliand Textilberichte 11, 1996, S.746,747 *
WOOD,E.J., u.a.: Objektive Messung des Aussehens von Teppichoberflächen durch Bildanalyse. In: Melliand Textilberichte 7-8, 1996, S.452-459 *

Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2003076915A1 (en) * 2002-03-14 2003-09-18 Basf Aktiengesellschaft Method for conducting automated surface inspection and surface correction
DE102005050302A1 (en) * 2005-10-17 2007-04-26 Yara International Asa Method and device for non-contact determination of the current nutritional status of a crop and for processing this information on fertilizer recommendations
DE102005050302B4 (en) * 2005-10-17 2007-07-26 Yara International Asa Method and device for non-contact determination of the current nutritional status of a crop and for processing this information on fertilizer recommendations
CN102249086A (en) * 2011-03-25 2011-11-23 江苏连港皮革机械有限公司 Leather sorting system and use method thereof
DE102013005489A1 (en) 2013-04-02 2014-10-02 Capex Invest GmbH Method and device for the automatic detection of defects in limp bodies
EP2787485A1 (en) 2013-04-02 2014-10-08 Capex Invest GmbH Method and device for automatic detection of defects in flexible bodies
DE102013005489B4 (en) 2013-04-02 2019-06-27 Capex Invest GmbH Method and device for the automatic detection of defects in limp bodies
US10297018B2 (en) * 2017-07-14 2019-05-21 Lear Corporation Method of digitally grading leather break
EP3594666A1 (en) * 2018-07-12 2020-01-15 Aibi Dynamics Co., Ltd. Artificial intelligence-based leather inspection method and leather product production method
EP3594682A1 (en) * 2018-07-12 2020-01-15 Aibi Dynamics Co., Ltd. Leather inspection equipment

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