EP2283937A1 - Procédé et dispositif de transport d'objets sur des points cible dépendant de motifs - Google Patents

Procédé et dispositif de transport d'objets sur des points cible dépendant de motifs Download PDF

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Publication number
EP2283937A1
EP2283937A1 EP10172124A EP10172124A EP2283937A1 EP 2283937 A1 EP2283937 A1 EP 2283937A1 EP 10172124 A EP10172124 A EP 10172124A EP 10172124 A EP10172124 A EP 10172124A EP 2283937 A1 EP2283937 A1 EP 2283937A1
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EP
European Patent Office
Prior art keywords
image
pattern
image pattern
transported
sorting
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.)
Granted
Application number
EP10172124A
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German (de)
English (en)
Other versions
EP2283937B1 (fr
Inventor
Zhe Li
Martin Neschen
Matthias Schulte-Austum
Wolf-Stephan Wilke
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.)
Siemens AG
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Siemens AG
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Publication date
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Publication of EP2283937A1 publication Critical patent/EP2283937A1/fr
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Publication of EP2283937B1 publication Critical patent/EP2283937B1/fr
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Classifications

    • 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
    • B07C3/00—Sorting according to destination
    • B07C3/10—Apparatus characterised by the means used for detection ofthe destination
    • B07C3/14—Apparatus characterised by the means used for detection ofthe destination using light-responsive detecting means

Definitions

  • the invention relates to a method and a device for transporting objects, in particular postal items, to target points which depend on image patterns.
  • a mail carrier determines that a catalog transported as a mail item can not be delivered to the recipient specified on the mailpiece and provides the mailpiece with a return label.
  • This mail again goes through a sorting process.
  • An image of each mail item to be returned is generated. These images contain areas of images of sender addresses. Similarities of those areas in the images showing sender addresses are determined. Those images that are sufficiently similar are treated as images of postal items, all of which are to be returned to the same sender.
  • a video coding station an editor reads the sender information in one of these images and enters it into a data acquisition device. All mail with similar sender images, a recognized sender is sent back to them.
  • DE 102007038186 B4 describes a method in which a sender sends a lot of many similar mailings an image of a surface of these similar mailings to a transporter. These mail items are sorted together with other mail items in a sorting system. Using the image, it is decided whether or not a mail item to be sorted belongs to this quantity.
  • US 20080008376 A1 For example, a method is described for identifying a postal indicia on the envelope of a mailpiece. A "region of interest" is identified and at least one candidate is found in this "region of interest”. Each candidate calculates a set of feature values for which an image of the envelope is generated and evaluated. Each candidate is classified using these characteristic values.
  • the invention is based on the object, a method and an apparatus for transporting objects to target points in which image patterns on objects are evaluated during transport, avoiding the need to manually enter computer-readable descriptions of image patterns.
  • the classifying apparatus includes an image pickup device and a grouper.
  • the sorting system also has an image pickup device and a picture pattern recognizer.
  • a training phase and then a sorting phase are carried out.
  • the sorting system is used at least in the sorting phase.
  • the items to be transported in the sample pass through the classification device.
  • the image capture device generates at least one image of each subject of the sample.
  • the grouper automatically determines which different image patterns are displayed on at least one subject of the sample. In doing so, the grouper applies a clustering method to the images of the sample.
  • the thus determined image patterns are stored in the image pattern data memory.
  • the invention eliminates the need for a processor to make computer-available descriptions of image patterns available in a training phase so that the sorting system can use those image patterns for the sorting phase. This is particularly advantageous if new patterns are added to objects on an ongoing basis, so that a training phase with manual input would always be too late.
  • the invention further eliminates the need for a mailer of items to communicate a computer-accessible description of a picture pattern to the sorting system. It is enough that the sender - or a third party - provides items with the image pattern.
  • the sorting system is also used for the training phase.
  • the imaging device use in both phases.
  • the clustering method is performed to form groups of images, each group comprising at least two images that show the same image pattern. It is also possible to set a minimum number of images per cluster that is significantly larger than 2.
  • image features are specified.
  • By evaluating an image it is determined which value each feature assumes for this image. This creates a feature value vector for the image.
  • Characteristic feature value vectors for the image patterns are stored in the image data memory.
  • a feature value vector is generated for each object to be transported and compared with the stored feature value vectors. This makes it particularly easy to decide whether and, if so, which image pattern is displayed on the object.
  • the solution according to the method and the device according to the solution can be z. B. for the transport of flat mail, packages, packages, pieces of luggage or workpieces in a manufacturing use.
  • the method is used to recognize image patterns on mailpieces.
  • the mailpieces are copies of an issue of a journal or a catalog that will be sent by post.
  • the mailpieces can be flat or even packages or freight items.
  • a postal service provider is to send many identical copies together with other mailpieces to their respective recipients.
  • the picture patterns are z. As logos or emblems, with which sender provide their mail.
  • the image pattern identifies the sender and is z. B. a protected figurative mark. Of course, the pattern may contain letters of a natural language or other characters.
  • the image pattern on a mailpiece should be recognized, in particular, if the mailpiece can not be delivered to the recipient whose postal address is specified on the mailpiece.
  • the receiver is unknown warped.
  • the recipient has moved and has communicated his new address to the postal service provider.
  • the mailpiece should not be forwarded to the new address due to a sender's "endorsement". Rather, either the mailpiece should be destroyed, and a notification about the non-delivery of the mailpiece should be sent to the sender ("sender notification").
  • the mailing provided with information about the new address should be returned to the sender. It is possible that the item of mail is provided with an "endorsement", which determines what should happen to the item of mail if the item of mail can not be sent to the address specified on the item of mail.
  • the sender address it is necessary to determine the sender address. If an image pattern of the sender can be recognized on the mail piece, it is easier to sort the mailpieces to be returned according to the respective sender.
  • the addresses and image patterns of registered senders are stored in an image address database of the postal service provider. It is also possible to perform a procedure like this in DE 19836767 C1 is described. Recognized are those mail items that are each provided with a representation of the same postal item.
  • the delivery address of the sender who has provided mailpieces with this image mark is determined, for which purpose an image of a mailpiece with this image mark is evaluated.
  • the delivery address of the sender is z. B. automatically by character recognition ("Optical Character Recognition", OCR) or manually determined by video encoding.
  • the recognized image patterns as well as further details of the sender on the mailpiece are compared with this database. After a successful comparison, it is possible to group the mail items by sender to be able to deliver all the mailpieces to the same sender. In the simplest case, it suffices to sort the mailpieces to be returned according to sender image patterns without necessarily automatically deciphering the sender address during sorting.
  • a sender delivers a lot of similar mailings, e.g. As the magazine copies of an issue, without delivery address and provided with its own pattern to the postal service provider.
  • the sender sends an address list with delivery addresses to the postal service provider, preferably in computer-available form. At least one copy of the quantity of similar mailpieces is to be delivered to each delivery address in this address list. It is possible that the address list for each delivery address contains the number of copies to be delivered to this delivery address.
  • the postal service provider evaluates the address list and assigns each copy with an address from the address list. In this case, the similar mailpieces are to be distinguished from other mailpieces due to the same image pattern.
  • a random sample with image pattern images is generated and evaluated.
  • Fig. 1 illustrates the first process step.
  • image patterns are recognized by clustering.
  • a camera 1 of the sorting system generates from each mail item Ps-a, Ps-b, ... at least one image Abb-a, Abb-b, .... It is possible that several cameras produce multiple images of the same mail item from different directions to also capture sender information on the back of a flat mail piece or because the mail piece is a package and six surfaces are eligible to show sender details. It is also possible for an image Abb-a, Abb-b,... To be generated and evaluated first and only if this image does not show the recipient address or the sender address, the item of mail is turned over and another image is generated ,
  • the n images Abb-a, Abb-b, ... are evaluated.
  • the n images are oriented and scaled before the actual evaluation. Orientation ensures that in all images with the same image pattern, the image pattern appears in the same orientation, ie not even standing upright and once standing upside down.
  • the images are oriented on the basis of the respective recipient address in the image. Scaling normalizes all images to the same size, even if the images come from different sizes of mail. It is also possible, the actual evaluation without first orienting and scaling the images.
  • each image is first searched for the area containing information about the sender of the mailpiece.
  • This area could contain an image of a sender's image pattern. It is of course possible that individual images do not contain any sender information.
  • the image is displayed on a video display device of a video coding station.
  • An engineer marks the area containing the sender details in the displayed image, or specifies that the image does not contain any sender information.
  • the sender uses a mouse to position a rectangle around the sender specified area.
  • the processor enters the sender address himself. However, he can not enter an image pattern, at least if it consists of more than one text or shows a text in a specific typography.
  • Predetermined m characteristics that can be calculated by evaluating a mailpiece image. For each one postal item of the random sample, a feature value vector with m feature values is generated in each case by the respective image Abb-a, Abb-b,... Of the mail item being automatically evaluated. This feature value vector indicates which m values assume the m features for this mail item.
  • color gamut area For each color range, parameters of that area in the image Abb-a, Abb-b, ... are calculated, which includes pixels with hues from this color range ("color gamut area"). These parameters include, for. For example, the size of the color area area itself, the edge length of a square circumscribing the area, the diagonal of a circumscribing ellipse, the centroid, and the perimeter length of the color area area. It is possible to divide the image of the mail item into areas, eg. In four quadrants, and calculate the respective parameters of the gamut area in each quadrant.
  • a cluster educator 3 applies a clustering method.
  • Cluster analysis or “clustering” is generally understood to mean a method in which a set of objects, which are each described by a feature value vector, are divided into groups, the objects of a group being similar to one another.
  • Clustering is a method of "unsupervised learning” and is z. In the fields of machine learning, data mining, pattern recognition, image analysis, and bioinformatics Examples of clustering methods are k-means clustering, fuzzy c-means clustering, "QT clustering algorithm”, "locality-sensitive hashing” and graph theory models.
  • a distance measure between two feature value vectors is specified.
  • the distances between two characteristic value vectors of the sample are calculated.
  • n images Abb-a, Abb-b, ... of the sample these are n * (n-1) / 2 distance calculations. All images whose distances according to this distance measure are smaller than a predetermined limit are treated as images of a group (a "cluster") showing the same image pattern.
  • the groups are calculated so that at least two images of the sample fall into each group.
  • the cluster-forming device 3 automatically recognizes which different image patterns are contained in the images Abb-a, Abb-b,.... The same picture pattern, z. As the same logo of a magazine publisher, can occur on different mailings of the same sender in different sizes and - due to variations in the printing process and environmental conditions when recording the images - in different configurations. Therefore, when applying the clustering method, the clustering device 3 forms groups of approximately similar image patterns.
  • the identified groups of similar image patterns are stored in an image database 4 or other suitable data storage.
  • an image data base 4 with reference image patterns is automatically generated.
  • each group is stored by storing in the image pattern database 4 a computer-accessible description of that area in the space of the possible feature value vectors in which all the feature value vectors of this group are located. It is also possible to store a characteristic feature value vector or a characteristic image from this group. It is possible, but not necessary, to additionally extract one image pattern from the images and to store a description of this image pattern.
  • a sorting phase that is to say a second method step of the exemplary embodiment, mailpieces again pass through the sorting system.
  • Fig. 2 illustrates the second pass of mail through the sorting system of FIG Fig. 1 , wherein the recognition results from the training phase, ie the first pass are applied
  • An image pattern recognizer 5 identifies an image pattern on a mailpiece and compares this image pattern with those reference image patterns which were automatically determined in the first method step and stored in the image pattern database 4.
  • all mail items are spent from the same sorting end in a transport container, z. B. a postal parcel.
  • This transport container is provided with the postal address of the sender and transported to this postal address.
  • the common sender information is not necessarily determined during sorting, but only when the transport container is labeled.
  • the common sender address of all mail items that are to be returned to the same sender is additionally determined during the sorting, that is, in the sorting phase. For this purpose, one of these mailings selected.
  • the sender address applied to the mailpiece is determined. First, an attempt is made to automatically determine and decipher the sender address on the selected mail piece. If this is not successful, an image of the surface of the mail item is displayed on a screen of a video coding station. An engineer marks the area in the image that shows the sender details. It is attempted to automatically read the address in this area. If this fails, the processor enters the sender details.
  • the mailings of a particular sender do not contain sender information, at least not on an externally visible page.
  • an issue of a journal may show a picture pattern of the issuing publisher in the cover page, but no sender address.
  • an image pattern address database 6 is therefore additionally specified in the second pass.
  • This image pattern address database 6 contains several data records. Each record comprises a reference image pattern of a sender as well as a delivery address of this sender. The record may contain additional information, e.g. B. Billing information for transportation services provided to this sender.
  • the image pattern of the selected mailpiece is determined. This image pattern is compared with reference image patterns of data sets of the image pattern address database 6. The record with the most similar reference image pattern is automatically selected. If this automatic selection does not succeed, an editor selects the correct image pattern under automatically selected similar reference image patterns. The delivery address that is included in the record with the most similar reference image pattern is used as the delivery address for all mailpieces with this image pattern. The mailpieces are preferably transported together to this delivery address of the sender.

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EP10172124.9A 2009-08-07 2010-08-06 Procédé et dispositif de transport d'objets sur des points cible dépendant de motifs Active EP2283937B1 (fr)

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
DE200910036626 DE102009036626A1 (de) 2009-08-07 2009-08-07 Verfahren und Vorrichtung zum Transportieren von Gegenständen an von Bildmustern abhängende Zielpunkte

Publications (2)

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EP2283937A1 true EP2283937A1 (fr) 2011-02-16
EP2283937B1 EP2283937B1 (fr) 2013-12-18

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EP (1) EP2283937B1 (fr)
DE (1) DE102009036626A1 (fr)
DK (1) DK2283937T3 (fr)

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE19836767C1 (de) 1998-08-13 1999-11-18 Siemens Ag Verfahren und Vorrichtung zum Bearbeiten von an den Absender zurückzuschickenden Sendungen
DE20218212U1 (de) * 2002-08-12 2003-12-24 Mit Management Intelligenter Technologien Gmbh Vorrichtung zur automatischen Adressblockmarkierung
AU2005203141A1 (en) 2004-07-20 2006-02-09 Solystic A method of detecting streams of postal items
US20070239848A1 (en) 2006-04-11 2007-10-11 John Avery Uniform resource locator vectors
US20080008376A1 (en) 2006-07-07 2008-01-10 Lockheed Martin Corporation Detection and identification of postal indicia
DE102006059525B3 (de) 2006-12-14 2008-04-17 Siemens Ag Verfahren und Vorrichtung zur Steuerung des Transports von Gegenständen sowie Anordnung zum Transport mehrerer Gegenstände
EP1927937A2 (fr) * 2006-12-01 2008-06-04 NEC Corporation Système d'identification d'un timbre officiel et procédé d'identification de timbre officiel
DE102007038186A1 (de) * 2007-08-13 2009-02-19 Siemens Ag Verfahren und Vorrichtung zum Transportieren von Massensendungen

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE4320331A1 (de) * 1993-06-20 1994-12-22 Robert Prof Dr Ing Massen Flexible optische Sortierung von Hohlkörpern
BR9406727A (pt) * 1993-05-28 1996-01-30 Axiom Bildverarbeit Syst Aparelho de inspeção automática para classificar artigo de acordo com caracteristica superficial de artigo aparelho de seleção automática aparelho de inspeção automática para categorizar peça de trabalho com base em seu padrão superficial e/ou de core/ou de textura processo para inspecionar artigo automaticamente para classificar o artigo de acordo com uma caracteristica superficical do mesmo
DE19501996C2 (de) * 1995-01-11 1996-12-12 Mannesmann Ag Steuerung für fördertechnische Anlagen
DE19751862C2 (de) * 1997-11-22 2002-09-19 Lutz Priese Verfahren und Vorrichtung zum Identifizieren und Sortieren von bandgeförderten Objekten

Patent Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE19836767C1 (de) 1998-08-13 1999-11-18 Siemens Ag Verfahren und Vorrichtung zum Bearbeiten von an den Absender zurückzuschickenden Sendungen
DE20218212U1 (de) * 2002-08-12 2003-12-24 Mit Management Intelligenter Technologien Gmbh Vorrichtung zur automatischen Adressblockmarkierung
AU2005203141A1 (en) 2004-07-20 2006-02-09 Solystic A method of detecting streams of postal items
EP1622065B1 (fr) 2004-07-20 2009-05-27 Solystic Procédé pour la détection de filantes
US20070239848A1 (en) 2006-04-11 2007-10-11 John Avery Uniform resource locator vectors
US20080008376A1 (en) 2006-07-07 2008-01-10 Lockheed Martin Corporation Detection and identification of postal indicia
EP1927937A2 (fr) * 2006-12-01 2008-06-04 NEC Corporation Système d'identification d'un timbre officiel et procédé d'identification de timbre officiel
DE102006059525B3 (de) 2006-12-14 2008-04-17 Siemens Ag Verfahren und Vorrichtung zur Steuerung des Transports von Gegenständen sowie Anordnung zum Transport mehrerer Gegenstände
DE102007038186A1 (de) * 2007-08-13 2009-02-19 Siemens Ag Verfahren und Vorrichtung zum Transportieren von Massensendungen
DE102007038186B4 (de) 2007-08-13 2009-05-14 Siemens Ag Verfahren und Vorrichtung zum Transportieren von Massensendungen

Also Published As

Publication number Publication date
EP2283937B1 (fr) 2013-12-18
DE102009036626A1 (de) 2011-02-10
DK2283937T3 (da) 2014-03-10

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