Today all Vendors have unified the main design for all-around (360º) CCD-camera equipped inspection of bottles’ sidewall, necks and finishes (labels, fill level and closure), in a stainless cabinet which can be opened for maintenance on both lateral sides and by the top with bottles passing through


In the fast Labeller Machines >50000 bottles-per-hour the missing plus malpositioned Collars account typical rates as high as ~80 % of the total rejects, with missing and malpositioned Body and Black labels summing up to the remaining ~20 % of the detected defects (image credit CARLSBERG Group, 2014)

Label Inspection

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            74 pages, 55 MB

Introduction

A real jump-up on Label Inspection's performances is obtained changing technology from Photoscanners to Machine Vision.   Reason is the much greater amount of Information about the label properties that it results possible to register with a camera.  Amount established correlating a label with hundredths of thousands (or, millions) of individual photo-detectors, rather than just one.   The figure above shows an example of the equipments’ for final inspection using CCD- or CMOS-technology cameras to inspect the labels’ presence and position.   At left side, a typical example of labelling where Machine Vision becomes nearly unavoidable.


Performances

The performances to expect depend on:

  •   the optic configuration, 
  •   amount of cameras, 
  •   eventual adoption of Artificial Intelligence algorithms,
  •   amount of CPUs devoted to the task or, availability of GPUs.

As an example, for the final inspection equipment depicted above, they are close to:

  • (1.0 ± 0.1) mm malpositioned labels, detected at >96 % with an associated false reject ratio < 0.01 %,
  • missing- or flagging-labels, detected at >99.5 % with an associated false reject ratio < 0.01 %.


 In the fast Labeller Machines >50000 bottles-per-hour, Collars missing and mal-positioned, account peak at ~80 % of the total rejects, with missing and malpositioned Body and Black labels summing up to remaining ~20 % of the detected defects (  CARLSBERG Group/2014)




To detect the entire external sidewall of the container, means to use two CCD- or CMOS- cameras equipped with some megapixels each. Notoriously, each pixel emulates an elementary (passive-only, no light source) analog photoscanner, whose dynamical range following its model ranges today (4096 - 65535) grey levels. By these digits, millions of individual analog photo detectors, and the fact that from each one we are capable to discriminate thousands of grey levels, it is easy to infer why the performances jump-up from the mere presence or absence of a label detectable with a single photoscanner, to positions whose accuracy level rounds 0.1 mm.




Transparent Labels, Collars, Neck and Foils: 

Machine Vision Shows its Best

Collars, like those visible in the figure below shot at a SABMiller™ plc brewery in Colombia, when flagging are a typical challenge fronted daily in the breweries.  impossible to counter with a single Label Presence photoscanner in-the-Labeller Machine.  On the opposite, a truly easy  application where the same defect is detected by mean of Machine Vision in an external final inspection system at-the-Conveyor.   In today’s fast (>50000 bottles-per-hour) rotary Labeller Machines, the missing plus malpositioned collars account typically for ~80 % of the total rejects, with missing and mal positioned Body and Black labels summing up to the remaining ~20 % of the detected defects.   One of the reasons lies in the difficulty to label the most curved  surface of the bottles’ external sidewall.   Also, a non-cylindrical shape, rather a conical section.    


  Transparent self-adhesive labels.  Their reflective area reduced to a small text and logo.  An application prone to cause false rejects yet adopting the best and most modern photoscanners today existing.  A natural area of application for camera-systems





Same is true also for the Label Presence inspection in-the-Labeller Machine.  It’ll be established a correlation of the shortest duration between the single photoscanner and label, in an area of the bottle so curved to result unavoidably that one featuring the highest luminous diffusion, due to known laws of Geometric Optic.  Then resulting a minimum for the luminous re-emission infeeding photoscanner's phototransistor. 


 Flagging Collars are a typical challenge impossible to counter with a single Label Presence photoscanner in-the-Labeller Machine.  On the opposite, an easy application where the same defect is detected by mean of Machine Vision in an external final inspection system at-the-Conveyor, in this image shot at a SABMiller PLC Colombia, Grupo Bavaria (   Tom Parker/OneRedEye/2012)


What is a “Good Label Inspection”?

The Correlated Label-Pixel State

 Projection of a quantum state-vector | ψ⟩ into a vector subspace S  by a projector P(S ).  Here shown the projection of  | ψ⟩ onto a ray corresponding to | ψm⟩, with which it makes an angle θ.  The probability for this transition to occur is cos2θ, thus illustrating von Neumann’s concept of probabilities evaluated by the measurement of angles.  A von Neumann Measurement is the set of possible such projections onto a complete orthogonal set rays of the Hilbert space being measured (  abridged by Jaeger/2009)



We saw with plenty of details elsewhere in this web site in what a way a physical object like a common plastic Cap relates itself to a Cap Presence photodetector.  We’ll now see, as a further example, how a system as complex as an industrial camera, including millions of Pixels, determines if a bottle is labelled. Pixels accumulate one-by-one the photons reflected by the sidewall, neck and closure of the bottle.  Later discharging the potential accumulated to an A/D conversion circuit whose outfeed is sequentially read by the following circuits to deduce what to a level of illumination has been subjected each individual pixel during the limited photon integration Time determined by a gating circuit.  [There also exist particularly fast Electronic Inspectors, adopted to inspect plastic empty bottles, whose Pixels’ photons integration Time is forcedly limited to tens of microseconds…]  Whatever physical system, label included, is represented by its wave function or state vectors.  The physical meaning of the state vector becomes apparent when making a measurement. Then the state of the system assumes one of the eigenstates, with probability given by the Born rule, and the result of the measurement is the corresponding eigenvalue.

To definetely perceive and record a correlated Label-Pixel State, they are necessary:

  1. Timeto transform the previous state, in which all possible kinds of correlation of the pixel coexist, in a following state in which a camera inspection is “aware” to be correlated to a Label, because having recorded eigenvalues for the eigenfunction ΦiS1 describing a Label.  The correlation between the two systems, camera inspection and Label, is progressively established during interaction and proportional to the natural logarithm (ln t) of the interaction time t.   

 To establish a relation between a label (“Label”) and a Photoscanner (“Photoscanner”), both differentially related with the Environment (“Environment1”, Environment2”), is necessary Time.  Time to transform the previous state, in which all possible kinds of correlation of the Photoscanner coexist, in a following state in which the Photoscanner is “aware” to be correlated to a label, because having recorded eigenvalues for the eigenfunction ΦiS1 describing a cap.   The vertexes represent interferences








  • An ideal correlation, one corresponding to a maximised information of the inspection about the Label, can only be reached allowing an infinite time.  The fact we cannot wait for an infinite time causes the measurements’ fluctuations, a synonimous of the spectrum of the eigenvalues, resulting in the Electronic Inspector's false positives (false rejects).  Time, for what?  To transform the previous state, in which all possible kinds of correlation (superpositions) of each one of the many pixels composing a camera sensor coexist, in a following state in which the inspection is aware to be correlated to a Label, because having recorded eigenvalues for the eigenfunction ΦiS1 describing a Label by the camera pixels;

  When containers’ speed exceeds 2 m/s, the Time available to establish the correlation between Object and each Detector, following the kind of Detector and Object reduces itself to < 12 ms


  1. Interaction between the systems such that the Information in the marginal distribution of the object inspected is never decreased.  In a probability distribution deriving by two random variables, we remember that marginal distribution is where we are only interested in one of them.   Otherwise, we’d have forced a reduction in the sample space of one of the random variables and then, we could not have any more repeatability of the following measurements.  As an example, this should be the case if to interact with the Label we’d erroneously try to use a beam of high energy neutrons, rather than strobo flashers’ or LED-matrices's low energy photons.  The neutrons should modify the molecular structure of the Label, modifying its eigenstates and then the eigenvalues we expected to derive by the measurement.

What before is the scientific background explaining why also double, triple or quadruple photoscanners, and also if of the best Quality (i.e., ~260 $ each), can result insufficient to reach satisfactory results.  Satisfactory in terms of defects' rejection ratio with minimum false positives.  Be wary of proposals for systems which could later leave only you and your Company with the nightmare to have the products' store, filled with yet palletised flagging-, malpositioned- or missing-labels. 





 To detect a Label they are necessary Time and a kind of interaction which do not reduce the information in the marginal distribution of the Label.  The second requirement is always fulfilled in the Electronic Inspectors but a real problem exists in relation to the first, depending on design choices of the Labeller and of the Bottling Line layout (  CARLSBERG Group/2014)



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This website has no affiliation with, endorsement, sponsorship, or support of Heuft Systemtechnik GmbH, MingJia Packaging Inspection Tech Co., Pressco Technology Inc., miho Inspektionsysteme GmbH, Krones AG, KHS GmbH, Bbull Technology, Industrial Dynamics Co., FT System srl, Cognex Co., ICS Inex Inspection Systems, Mettler-Toledo Inc., Logics & Controls srl, Symplex Vision Systems GmbH, Teledyne Dalsa Inc., Microscan Systems Inc., Andor Technology plc, Newton Research Labs Inc., Basler AG, Datalogic SpA, Sidel AG, Matrox Electronics Systems Ltd. 

                                                                                                                                                                                                                                                                                                                                                                                                                                                         
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