WO2000070540A1 - Partial ocr note confirmation methods - Google Patents

Partial ocr note confirmation methods Download PDF

Info

Publication number
WO2000070540A1
WO2000070540A1 PCT/US2000/012901 US0012901W WO0070540A1 WO 2000070540 A1 WO2000070540 A1 WO 2000070540A1 US 0012901 W US0012901 W US 0012901W WO 0070540 A1 WO0070540 A1 WO 0070540A1
Authority
WO
WIPO (PCT)
Prior art keywords
note
character
serial code
identifying
read
Prior art date
Application number
PCT/US2000/012901
Other languages
French (fr)
Inventor
Richard Glen Haycock
Original Assignee
Currency Systems International
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 Currency Systems International filed Critical Currency Systems International
Priority to AU48390/00A priority Critical patent/AU4839000A/en
Publication of WO2000070540A1 publication Critical patent/WO2000070540A1/en

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00Payment architectures, schemes or protocols
    • G06Q20/08Payment architectures
    • G06Q20/10Payment architectures specially adapted for electronic funds transfer [EFT] systems; specially adapted for home banking systems
    • G06Q20/108Remote banking, e.g. home banking
    • G06Q20/1085Remote banking, e.g. home banking involving automatic teller machines [ATMs]
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V30/00Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
    • G06V30/10Character recognition
    • G06V30/26Techniques for post-processing, e.g. correcting the recognition result
    • G06V30/262Techniques for post-processing, e.g. correcting the recognition result using context analysis, e.g. lexical, syntactic or semantic context
    • G06V30/274Syntactic or semantic context, e.g. balancing
    • GPHYSICS
    • G07CHECKING-DEVICES
    • G07DHANDLING OF COINS OR VALUABLE PAPERS, e.g. TESTING, SORTING BY DENOMINATIONS, COUNTING, DISPENSING, CHANGING OR DEPOSITING
    • G07D7/00Testing specially adapted to determine the identity or genuineness of valuable papers or for segregating those which are unacceptable, e.g. banknotes that are alien to a currency
    • G07D7/17Apparatus characterised by positioning means or by means responsive to positioning
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V30/00Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
    • G06V30/10Character recognition
    • GPHYSICS
    • G07CHECKING-DEVICES
    • G07DHANDLING OF COINS OR VALUABLE PAPERS, e.g. TESTING, SORTING BY DENOMINATIONS, COUNTING, DISPENSING, CHANGING OR DEPOSITING
    • G07D7/00Testing specially adapted to determine the identity or genuineness of valuable papers or for segregating those which are unacceptable, e.g. banknotes that are alien to a currency
    • G07D7/06Testing specially adapted to determine the identity or genuineness of valuable papers or for segregating those which are unacceptable, e.g. banknotes that are alien to a currency using wave or particle radiation
    • G07D7/12Visible light, infrared or ultraviolet radiation

Definitions

  • the present invention relates to methods for identifying a currency note using a partial read
  • OCR optical character recognition
  • a stack of currency can be fed into the high speed currency processing
  • an OCR device reads the serial number or code
  • One of the functions of the high speed currency processor may be to sort currency by denomination and stack fit notes for bundling. As the fit notes are stacked, the data processing capabilities of the currency processing machine track the location in the stack of each currency note by serial number. For example, for a processed stack or bundle of one hundred notes in twenty dollar denominations, data is accumulated that will indicate the specific serial number on each note in the stack or bundle and position of each note in the stack. This information can be particularly useful in a number of potential applications. For
  • ATM automatic teller machine
  • OCR technology Another example of a potential application of OCR technology is to assist in the identity
  • central bank in groupings of one hundred notes per bundle. If the central bank determines that there are only ninety-nine notes in a bundle that should have contained one hundred, it is extremely useful to be able to identify the serial number of the ninety-nine notes that were received and compare that data, with the serial numbers recorded by the commercial institution to the one
  • Such a method should be capable of identifying notes through a high level
  • serial number or code of a note have been read. This is accomplished by recording the position of each field read along with the character identifier found in that field. The method can also combine this information with the position of the note in a specific stack of currency to provide
  • the method can determine which
  • Figure 1 is an illustration of a note
  • FIGS 2a and 2b are flow charts showing the steps of one of the methods disclosed.
  • Figure 1 illustrates a typical twenty dollar bill or note. Figure 1 shows identical serial
  • This code 20 located in the upper left and lower right hand corners of the note. This code 20 can be
  • An OCR device (in combination with sensors that identify the position of the note relative to the OCR device) is capable, however, of determining the field position of each character read, because the serial code is located in the same relative position on a note. Therefore, additional
  • One embodiment of the invention uses only the combination of characters read along with their respective field positions to assist in identifying or negatively discriminating notes.
  • a second embodiment of the invention adds to this information the position of the note in question in a given currency bundle or stack. Again using the example note of Figure 1, it is assumed that the
  • the ATM can typically identify and record the position of each note
  • the ATM can record the account information associated with such withdrawal. Consequently, if an account
  • the bank first requests the account holder's account number and the date and location of
  • the bank can determine the position in the stack
  • a simple example involves an account holder that withdrew one single note which the bank identifies as the example note of Figure 1 and where this is the note recorded to the eighth position in a stack of one hundred notes
  • note will have the same three characters identified to their respective three fields 3, 8, 10, as the note that was identified as being distributed by its location in the stack is one in two thousand six hundred, or less than a .04% chance.
  • a bundle of unprocessed notes are fed into a processing device, such as a high speed currency processing machine.
  • a processing device such as a high speed currency processing machine.
  • an OCR device reads 30 the serial code of all identifiable characters on each note as it passes the device.
  • the position of each character read is associated 40 with a known field position. This information is retained by a computer or separate data processing function while the note is further processed.
  • each note is stacked with -other processed notes in a bundle.
  • a record 50 is made of the
  • Figure 2a is correlated for each of the individual notes processed.
  • the ATM records 70 the position of the note from the stack as it is distributed.
  • the ATM also associates 80 account information regarding the account holder to
  • the invention has applications beyond OCR lift and high speed currency processing issues.
  • OCR devices could be installed to record serial numbers on notes as they are being

Abstract

Methods of identifying a note with a partial optical character recognition of one or more characters in the notes serial code (20). The method records the characters read (3, 8, 10) and associates each character read with its field position in the serial code (20). The method can use this information or combine the character and field information with positional information of the note within a stack in order to identify a note with a reasonable degree of statistical probability.

Description

BACKGROUND OF THE INVENTION
1. Technical Field
The present invention relates to methods for identifying a currency note using a partial read
of the note's serial number or code. Individual numbers are identified to specific fields in the serial number in order to provide a statistically accurate identification of a note despite an inability to read the entire serial number.
2. Description of Related Art
Optical character recognition ("OCR") is a technology commonly used in the currency processing field for lifting the serial number or code from processed notes. OCR technology is used, for example, for identifying specific notes processed by a high speed currency processing
machine, such as those machines manufactured and marketed by Currency Systems International
of Irving, Texas, by lifting a note's serial code using a camera device and then recording the serial code to the note processed.
By way of example, a stack of currency can be fed into the high speed currency processing
machine. As one of the functions of the machine, an OCR device reads the serial number or code
of notes passed through the machine for processing. These serial numbers can be recorded and
identified to specific notes as they are processed. One of the functions of the high speed currency processor may be to sort currency by denomination and stack fit notes for bundling. As the fit notes are stacked, the data processing capabilities of the currency processing machine track the location in the stack of each currency note by serial number. For example, for a processed stack or bundle of one hundred notes in twenty dollar denominations, data is accumulated that will indicate the specific serial number on each note in the stack or bundle and position of each note in the stack. This information can be particularly useful in a number of potential applications. For
example, if this bundle is later distributed by an automatic teller machine ("ATM"), the ATM can
identify the specific notes distributed to a specific account by recording the position of the notes
in the stack as they are distributed. The ATM might record that the eighth note in the stack was
distributed to a specific account holder on a specific day and time. If later that particular account
holder contacts the bank to indicate that the account holder received a counterfeit note, the bank
can confirm such claim by requesting that the account holder identify the serial number of the note in question. The bank will be able to tell which note was distributed to the account holder if it
knows the position of the note in the bundle and the serial number recorded for the note at that
position provided by the high speed currency processing machine. If the serial number provided
by the account holder matches the serial number identified to the note distributed, then the bank has confirmed that a counterfeit note was in fact distributed to the account holder.
Another example of a potential application of OCR technology is to assist in the identity
of missing notes. For example, a commercial institution might transfer bundles of notes to a
central bank in groupings of one hundred notes per bundle. If the central bank determines that there are only ninety-nine notes in a bundle that should have contained one hundred, it is extremely useful to be able to identify the serial number of the ninety-nine notes that were received and compare that data, with the serial numbers recorded by the commercial institution to the one
hundred notes that it shipped. By identifying the serial number of the missing note, it may be possible to identify the location of the note in the bundle and determine if there had been a problem at some stage of note processing.
Another example of a potential use of OCR technology involves notes deposited from a till when the till depositor later claims that the depositee did not properly credit all the notes deposited. If the till depositor can identify the serial numbers of each note deposited, the accounting problem might be more easily resolved.
While there are many potentially useful applications incorporating the ability of OCR
devices to identify a note's serial number, unfortunately a consistently accurate read of the entire
field of every note's serial number in a high speed currency processing environment is not feasible
given present OCR technology. This difficulty increases with worn or unfit notes. Consequently,
it is not uncommon for OCR devices to obtain only a partial read of a note's serial number. The
fact that extremely worn or soiled notes will always need to be processed along with more fit notes
makes it unlikely that any improvement in OCR technology will ever provide the capability of a one hundred percent accuracy rate in reading the entire field of every note processed. Presently,
none of the above examples of useful applications of OCR technology can be reliably applied in
light of the inability to read the entire serial code of every note processed.
Consequently, a need exists for a method that will accurately identify a note even though
the note's entire serial number could not be obtained by OCR technology. This method should provide positive note identification or negative note discrimination even though only a portion of
the OCR is successful. Such a method should be capable of identifying notes through a high level
of statistical probability having read only two or more of the identifying fields and should be able to provide some level- of discrimination when even only one field is read.
SUMMARY OF INVENTION
The invention involves methods for identifying a currency note when not all fields of the
serial number or code of a note have been read. This is accomplished by recording the position of each field read along with the character identifier found in that field. The method can also combine this information with the position of the note in a specific stack of currency to provide
an additional data point.
By way of example, United States currency notes, such as the one illustrated in Figure 1,
generally have serial numbers with ten fields. An OCR lift on a soiled or worn note might only identify one or two characters of the serial number accurately. However, because the field
position of each character read on the note can also be identified, the method can determine which
fields have been read and then associate the character within each field to the field position. The
method then uses this information in order to statistically identify a serial number of a note to the note processed. This information can also be combined with the position of the note in the currency stack. By knowing a small percentage of the characters associated with a specific serial
number, the respective field position of each character, and the position of the note in a stack,
notes can be identified with a high statistical probability of accuracy. This method, therefore, greatly enhances the usefulness of OCR technology without the necessity of improving on the accuracy of OCR devices.
The above as well as additional features and advantages of the present invention will become apparent in the following written detailed description. BRIEF DESCRIPTION OF THE DRAWINGS
The novel features believed characteristic of the invention are set forth in the appended claims. The invention itself, however, as well as preferred mode of use, further objectives and advantages thereof, will be best understood by reference to the following detailed description of illustrative embodiments when read in conjunction with the accompanying drawings, wherein:
Figure 1 is an illustration of a note; and
Figures 2a and 2b are flow charts showing the steps of one of the methods disclosed.
DETAILED DESCRIPTION Figure 1 illustrates a typical twenty dollar bill or note. Figure 1 shows identical serial
codes 20 located in the upper left and lower right hand corners of the note. This code 20 can
consist of combinations of number and/or letters. Also identified for illustrative purposes are the
third 3, eighth 8, and tenth 10 fields in the serial code 20.
Currency processing machines presently use one or more OCR devices in order to read one or both of the identical serial codes 20. Because of soiling on the note or damage to the note, it
may not be possible for even the most accurate OCR devices to read the entire serial code for a
specific note. For illustration of the method involved, it is assumed that the note shown in Figure
1 was soiled or damaged to the point that only the characters in the third 3, eighth 8, and tenth 10 fields of the serial code 20 can be read. In this instance the characters "0," "5," and "A," respectively. The information that these three characters provide in and of themselves is of limited
value. It would be difficult to identify any note knowing only that the characters "0," "5," and
"A" appeared somewhere in a ten field serial code.
An OCR device (in combination with sensors that identify the position of the note relative to the OCR device) is capable, however, of determining the field position of each character read, because the serial code is located in the same relative position on a note. Therefore, additional
information can be provided along with the characters read. Using the note example illustrated
in Figure 1, data can be recorded indicating that the number "0" was found in the third field 3 of the serial code, that the number "5" was found in the eighth field 8 of the serial code, and that the letter "A" was found in the tenth field 10 of the serial code.
Assuming that the numbers zero through nine are available for each of the fields displaying numbers 3, 8, and that all twenty-six letters of the alphabet are available for the fields displaying letter characters 10, only one in two thousand six hundred notes would have the number zero in the third field 3, the number five in the eighth field 8, and the letter "B" in the tenth field 10.
Consequently, by knowing just three characters and their position in the serial code 20, a note can
be positively identified to a full serial code string with a 99.96% accuracy rate. Conversely, in
attempting to negatively discriminate between a known serial code and the example note in Figure
1, the probability of a note having the same three characters read in the same three field positions
is less than .04%. Even when only two field positions are read, for example the eighth field 8 and
the tenth field 10, the ability to negatively discriminate between a partial read serial code is still
statistically significant. For example, if an account holder withdrew a note from an ATM and later called the bank to indicate that such note was a counterfeit, the account holder would have less than .4% chance of guessing at the accurate serial code when the bank knows that the number
five and the letter "A" are found in the eighth 8 and tenth 10 fields, respectively.
One embodiment of the invention uses only the combination of characters read along with their respective field positions to assist in identifying or negatively discriminating notes. A second embodiment of the invention adds to this information the position of the note in question in a given currency bundle or stack. Again using the example note of Figure 1, it is assumed that the
information has already been provided on the characters found in three field positions. During currency processing, it can also be recorded that the note identified to this partial read serial code has been placed, for example, as the eight note in a bundle of one hundred notes. Likewise, all of the notes in a particular stack are associated with either complete or partial serial code information obtained during processing and positional information in the stack. This process can
be assimilated by a computer or the data processing functions of the currency processing machine. The benefit of knowing the position of the note in the stack is again illustrated by the
example involving the ATM. The ATM can typically identify and record the position of each note
withdrawn and associate that note's position with each specific withdrawal. Further, the ATM can record the account information associated with such withdrawal. Consequently, if an account
holder contacts the bank complaining that a counterfeit had been distributed from one of the bank's
ATM, using applicants method the bank would be equipped with all the information required to
determine if this claim is valid even though only a partial serial code read has been obtained on the note in question.
The bank first requests the account holder's account number and the date and location of
the ATM withdrawal. Using this information, the bank can determine the position in the stack
loaded in the ATM of the notes withdrawn by the account holder. A simple example involves an account holder that withdrew one single note which the bank identifies as the example note of Figure 1 and where this is the note recorded to the eighth position in a stack of one hundred notes
loaded into the ATM. To confirm that the note is a counterfeit, the bank then requests that the
account holder provide the serial number of the note. The statistical probability that any given
note will have the same three characters identified to their respective three fields 3, 8, 10, as the note that was identified as being distributed by its location in the stack is one in two thousand six hundred, or less than a .04% chance.
The steps of the above method are further understood by reference to figures 2a and 2b.
A bundle of unprocessed notes are fed into a processing device, such as a high speed currency processing machine. During the processing cycle, an OCR device reads 30 the serial code of all identifiable characters on each note as it passes the device. Next, the position of each character read is associated 40 with a known field position. This information is retained by a computer or separate data processing function while the note is further processed. At the end of the processing cycle each note is stacked with -other processed notes in a bundle. A record 50 is made of the
position of each note in the bundle. All of the information obtained during the steps illustrated
by Figure 2a is correlated for each of the individual notes processed.
Later, the note stack or bundle is fed 60 into an ATM. As each individual note is
subsequently distributed, the ATM records 70 the position of the note from the stack as it is distributed. The ATM also associates 80 account information regarding the account holder to
whom the note from a said position is distributed. By knowing this account information, the bank
can use the positional information to identify 90 a partially read serial code to each individual note distributed.
The invention has applications beyond OCR lift and high speed currency processing issues.
For example, OCR devices could be installed to record serial numbers on notes as they are being
distributed from an ATM or other consumer currency distribution type machines. Identification
of serial code information, even if it is only a partial read of the serial code, could then be
associated by the ATM machine with each individual withdrawal. Using the method described of recording not just the characters found by the partial read but also the characters' position in the serial code, a bank would be able to identify each note distributed to a reasonable degree of
statistical probability even without knowing the position of the note in the bundle loaded into the
ATM.
While the invention has been particularly shown and described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention.

Claims

CLAIMS:What is claimed is:
1. A method for identifying a note having a serial code, said method comprising the steps of:
(a) identifying at least one character of the note's serial code;
(b) identifying the field position of said at least one character read; and
(c) identifying the recorded field position and characters to the note.
2. The method of claim 1 further comprising:
(d) identifying the note to a position in a stack of notes.
3. The method of claim 1 wherein the serial code characters are identified using an optical character recognition device.
4. The method of claim 1 wherein the position identified in step (d) is correlated to account information when the note is distributed.
5. The method of claim 1 wherein the position identified in step (d) is correlated to account information when the note is deposited.
. A method for correlating a partially read serial code to a note, comprising the steps of:
(a) reading at least one character of a serial code;
(b) identifying the field position of at least one character read; and
(c) comparing the read character and identified field position with the serial code of a note.
7. The method of claim 6 further comprising:
(d) identifying the note by its position in a stack of notes.
8. The method of claim 7 further comprising:
(e) identifying account data to the note when distributed from said stack.
9. The method of claim 7 further comprising:
(e) identifying account data to the note when the stack is deposited.
0. A method for identifying notes distributed from an automated teller machine comprising the steps of:-
a) reading at least one character of a note's serial code b) identifying the field position in the serial code of the character read;
c) recording the field position identified and character read; and d) correlating account data with the recorded field character and field position data.
11. The method of claim 10 wherein the reading of step (a) and identifying of step (b) occurs
before the notes are installed in the automated teller machine.
12. The method of claim 11 wherein the correlating of step (d) further comprises identifying the note by its position in a stack of notes.
AMENDED CLAIMS
[received by the International Bureau on 20 October 2000 (20.10.00); original claims 1, 4 -7 and 10 amended; new claims 13 and 14 added; remaining claims unchanged (3 pages)]
1. A method for identifying a note having a serial code, said method comprising the steps of:
(a) reading at least one character of the note's serial code;
(b) identifying the field position of said at least one character read; and
(c) responsive to a determination that at least one character of said serial code cannot be read, identifying the note by using the at least one character read and the field position of said at least one character read.
2. The method of claim 1 further comprising:
(d) identifying the note to a position in a stack of notes.
3. The method of claim 1 wherein the serial code characters are identified using an optical character recognition device.
4. The method of claim 2 wherein the position identified in step (d) is correlated to account information when the note is distributed.
5. The method of claim 2 wherein the position identified in step (d) is correlated to account information when the note is deposited.
6. A method for determining the correlation of a partially read serial code to a complete serial code, comprising the steps of:
(a) reading at least one character of a serial code;
(b) identifying the field position of said at least one character read: and
(c) responsive to a determination that at least one character of said serial code cannot be read, comparing said at least one character read and said field position with said complete serial code.
7. The method of claim 6 further comprising:
(d) comparing a position of a note in a stack of notes to a recorded position associated with said complete serial code wherein said partially read serial code and said complete serial code do not correlate if said position and said recorded position are not equal.
8. The method of claim 7 further comprising:
(a) identifying account data to the note when distributed from said stack.
9. The method of claim 7 further comprising:
(e) identifying account data to the note when the stack is deposited.
10. A method for identifying notes distributed from an automated teller machine comprising the steps of: a) reading at least one character of a note's serial code; b) identifying a field position in the serial code of the at least one character; c) recording the field position and the character; d) correlating account data with the recorded character and field position data; and e) comparing a complete serial code to said recorded character and field position data to determine if there is a match, wherein a match may be determined even though at least one character of said serial code cannot be read.
11. The method of claim 10 wherein the reading of step (a) and identifying of step (b) occurs before the notes are installed in the automated teller machine.
12. The method of claim 11 wherein the correlating of step (d) further comprises identifying the note by its position in a stack of notes.
13. The method of claim 1 wherein the note is identified in step (c) by eliminating all serial codes not having said at least one character located in said field position.
14. The method of claim 6 wherein if said complete serial code contains said at least one character in said field position, then said partially read serial code correlates with said complete serial code.
PCT/US2000/012901 1999-05-13 2000-05-11 Partial ocr note confirmation methods WO2000070540A1 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
AU48390/00A AU4839000A (en) 1999-05-13 2000-05-11 Partial ocr note confirmation methods

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US09/311,322 1999-05-13
US09/311,322 US6510238B2 (en) 1999-05-13 1999-05-13 Partial OCR note confirmation methods

Publications (1)

Publication Number Publication Date
WO2000070540A1 true WO2000070540A1 (en) 2000-11-23

Family

ID=23206373

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2000/012901 WO2000070540A1 (en) 1999-05-13 2000-05-11 Partial ocr note confirmation methods

Country Status (3)

Country Link
US (2) US6510238B2 (en)
AU (1) AU4839000A (en)
WO (1) WO2000070540A1 (en)

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1436979A2 (en) * 2001-09-27 2004-07-14 Cummins-Allison Corporation Document processing system using full image scanning
EP2330569A1 (en) * 2008-08-08 2011-06-08 Glory Ltd. Paper notes management system, paper notes identification apparatus, paper notes management apparatus, method for managing paper notes, and program for managing paper notes
CN102800148A (en) * 2012-07-10 2012-11-28 中山大学 RMB sequence number identification method
CN103042822A (en) * 2013-01-11 2013-04-17 西安印钞有限公司 Control system and method of double identification code dynamic digit of presswork
US9129271B2 (en) 2000-02-11 2015-09-08 Cummins-Allison Corp. System and method for processing casino tickets
US9818249B1 (en) 2002-09-04 2017-11-14 Copilot Ventures Fund Iii Llc Authentication method and system
CN110895849A (en) * 2018-09-13 2020-03-20 深圳怡化电脑股份有限公司 Method and device for cutting and positioning crown word number, computer equipment and storage medium

Families Citing this family (35)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6363164B1 (en) * 1996-05-13 2002-03-26 Cummins-Allison Corp. Automated document processing system using full image scanning
US20050276458A1 (en) 2004-05-25 2005-12-15 Cummins-Allison Corp. Automated document processing system and method using image scanning
US7903863B2 (en) * 2001-09-27 2011-03-08 Cummins-Allison Corp. Currency bill tracking system
US8162125B1 (en) 1996-05-29 2012-04-24 Cummins-Allison Corp. Apparatus and system for imaging currency bills and financial documents and method for using the same
US8478020B1 (en) 1996-11-27 2013-07-02 Cummins-Allison Corp. Apparatus and system for imaging currency bills and financial documents and method for using the same
US6510238B2 (en) * 1999-05-13 2003-01-21 Currency Systems International, Inc. Partial OCR note confirmation methods
US7006257B1 (en) * 1999-11-19 2006-02-28 Canon Kabushiki Kaisha Image processing apparatus, image processing method, and storage medium
DE10049435A1 (en) * 2000-10-06 2002-04-18 Giesecke & Devrient Gmbh Procedure for processing sheet material
US7899243B2 (en) 2000-11-06 2011-03-01 Evryx Technologies, Inc. Image capture and identification system and process
US9310892B2 (en) 2000-11-06 2016-04-12 Nant Holdings Ip, Llc Object information derived from object images
US7680324B2 (en) 2000-11-06 2010-03-16 Evryx Technologies, Inc. Use of image-derived information as search criteria for internet and other search engines
US8224078B2 (en) 2000-11-06 2012-07-17 Nant Holdings Ip, Llc Image capture and identification system and process
US7565008B2 (en) 2000-11-06 2009-07-21 Evryx Technologies, Inc. Data capture and identification system and process
US7647275B2 (en) 2001-07-05 2010-01-12 Cummins-Allison Corp. Automated payment system and method
US7873576B2 (en) * 2002-09-25 2011-01-18 Cummins-Allison Corp. Financial document processing system
US8437530B1 (en) 2001-09-27 2013-05-07 Cummins-Allison Corp. Apparatus and system for imaging currency bills and financial documents and method for using the same
US8433123B1 (en) 2001-09-27 2013-04-30 Cummins-Allison Corp. Apparatus and system for imaging currency bills and financial documents and method for using the same
US8944234B1 (en) 2001-09-27 2015-02-03 Cummins-Allison Corp. Apparatus and system for imaging currency bills and financial documents and method for using the same
US8437529B1 (en) 2001-09-27 2013-05-07 Cummins-Allison Corp. Apparatus and system for imaging currency bills and financial documents and method for using the same
US8428332B1 (en) 2001-09-27 2013-04-23 Cummins-Allison Corp. Apparatus and system for imaging currency bills and financial documents and method for using the same
US20030139994A1 (en) * 2002-01-22 2003-07-24 Jones John E. Financial institution system
US8627939B1 (en) * 2002-09-25 2014-01-14 Cummins-Allison Corp. Apparatus and system for imaging currency bills and financial documents and method for using the same
EP1437692B1 (en) * 2003-01-08 2006-03-22 Glory Ltd. Bill serial number reading device and bill serial number reading method
US20050169511A1 (en) * 2004-01-30 2005-08-04 Cummins-Allison Corp. Document processing system using primary and secondary pictorial image comparison
US8417017B1 (en) 2007-03-09 2013-04-09 Cummins-Allison Corp. Apparatus and system for imaging currency bills and financial documents and method for using the same
GB2486832A (en) 2007-03-09 2012-06-27 Cummins Allison Corp Document processing system using blind balancing
US8538123B1 (en) 2007-03-09 2013-09-17 Cummins-Allison Corp. Apparatus and system for imaging currency bills and financial documents and method for using the same
US8184893B2 (en) 2007-12-05 2012-05-22 Bank Of America Corporation Enhanced note processing
US8437532B1 (en) 2009-04-15 2013-05-07 Cummins-Allison Corp. Apparatus and system for imaging currency bills and financial documents and method for using the same
US8391583B1 (en) 2009-04-15 2013-03-05 Cummins-Allison Corp. Apparatus and system for imaging currency bills and financial documents and method for using the same
US8929640B1 (en) 2009-04-15 2015-01-06 Cummins-Allison Corp. Apparatus and system for imaging currency bills and financial documents and method for using the same
JP5302933B2 (en) * 2010-06-07 2013-10-02 日立オムロンターミナルソリューションズ株式会社 Paper sheet discrimination device
DE102010045879A1 (en) * 2010-09-17 2012-03-22 Giesecke & Devrient Gmbh Method for processing banknotes
US9563811B2 (en) * 2012-07-31 2017-02-07 Lg Cns Co., Ltd. Character recognition method, character recognition apparatus and financial apparatus
US9141876B1 (en) 2013-02-22 2015-09-22 Cummins-Allison Corp. Apparatus and system for processing currency bills and financial documents and method for using the same

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5570465A (en) * 1993-07-22 1996-10-29 Tsakanikas; Peter J. Apparatus, method and system for printing of legal currency and negotiable instruments
US5615280A (en) * 1992-12-28 1997-03-25 Japan Cash Machine Co., Ltd. Apparatus for recording symbols printed on documents or the like
US5917930A (en) * 1996-07-31 1999-06-29 Currency Systems International Method for semi-continuous currency processing using separator cards

Family Cites Families (23)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
IT941586B (en) 1971-10-15 1973-03-10 Martelli M EQUIPMENT VERIFYING VALUE CARDS AND IN SPECIES OF BANKNOTES WITH PHOTOELECTRIC OPERATION
US3916194A (en) 1974-01-07 1975-10-28 Ardac Inc Infrared note validator
US4139219A (en) * 1975-11-21 1979-02-13 Marked Money Systems, Inc. Money marking system
US4264808A (en) 1978-10-06 1981-04-28 Ncr Corporation Method and apparatus for electronic image processing of documents for accounting purposes
US4315246A (en) * 1979-07-11 1982-02-09 Magnetic Pheripherals, Inc. Document character recognition system for identifying magnetic ink characters on bank checks and the like
JPS5854433B2 (en) * 1980-09-11 1983-12-05 日本電気株式会社 Difference detection device
JPS5785179A (en) * 1980-11-17 1982-05-27 Mitsubishi Electric Corp Optical character reading method
US4587434A (en) 1981-10-22 1986-05-06 Cubic Western Data Currency note validator
US5099423A (en) 1985-06-27 1992-03-24 Diebold, Incorporated Method and apparatus for account settlement in an ATM
US5548110A (en) * 1986-04-18 1996-08-20 Cias, Inc. Optical error-detecting, error-correcting and other coding and processing, particularly for bar codes, and applications therefor such as counterfeit detection
JPS62251987A (en) * 1986-04-25 1987-11-02 Mitsubishi Electric Corp Optical character reader
JPH0196779A (en) * 1987-10-09 1989-04-14 Mitsubishi Electric Corp Word reader
JP2685817B2 (en) * 1988-07-11 1997-12-03 株式会社東芝 Automatic transaction equipment
US4991008A (en) 1988-12-01 1991-02-05 Intec Video Systems, Inc. Automatic transaction surveillance system
US5295196A (en) 1990-02-05 1994-03-15 Cummins-Allison Corp. Method and apparatus for currency discrimination and counting
JP2740335B2 (en) * 1990-05-18 1998-04-15 富士ファコム制御株式会社 Table reader with automatic cell attribute determination function
JP3204967B2 (en) * 1990-08-29 2001-09-04 株式会社日立製作所 Paper sheet management device and cash automatic transaction device
US5545885A (en) 1992-06-01 1996-08-13 Eastman Kodak Company Method and apparatus for detecting and identifying coded magnetic patterns on genuine articles such as bank notes
JP3080149B2 (en) * 1996-12-03 2000-08-21 日本電気株式会社 Pattern encoding method and decoding method, and encoding apparatus and decoding apparatus using the method
JPH09259219A (en) * 1996-03-26 1997-10-03 Sharp Corp Character recognition method
US6015087A (en) * 1996-10-04 2000-01-18 First Data Corporation Apparatus and method for leasing documents of value
SG71018A1 (en) * 1997-03-01 2000-03-21 Inst Of Systems Science Nat Un Robust identification code recognition system
US6510238B2 (en) * 1999-05-13 2003-01-21 Currency Systems International, Inc. Partial OCR note confirmation methods

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5615280A (en) * 1992-12-28 1997-03-25 Japan Cash Machine Co., Ltd. Apparatus for recording symbols printed on documents or the like
US5570465A (en) * 1993-07-22 1996-10-29 Tsakanikas; Peter J. Apparatus, method and system for printing of legal currency and negotiable instruments
US5917930A (en) * 1996-07-31 1999-06-29 Currency Systems International Method for semi-continuous currency processing using separator cards

Cited By (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9129271B2 (en) 2000-02-11 2015-09-08 Cummins-Allison Corp. System and method for processing casino tickets
EP1436979A4 (en) * 2001-09-27 2007-12-19 Cummins Allison Corp Document processing system using full image scanning
US7881519B2 (en) 2001-09-27 2011-02-01 Cummins-Allison Corp. Document processing system using full image scanning
US8041098B2 (en) 2001-09-27 2011-10-18 Cummins-Allison Corp. Document processing system using full image scanning
US8103084B2 (en) 2001-09-27 2012-01-24 Cummins-Allison Corp. Document processing system using full image scanning
EP1436979A2 (en) * 2001-09-27 2004-07-14 Cummins-Allison Corporation Document processing system using full image scanning
US9818249B1 (en) 2002-09-04 2017-11-14 Copilot Ventures Fund Iii Llc Authentication method and system
EP2330569A4 (en) * 2008-08-08 2012-06-06 Glory Kogyo Kk Paper notes management system, paper notes identification apparatus, paper notes management apparatus, method for managing paper notes, and program for managing paper notes
US8634632B2 (en) 2008-08-08 2014-01-21 Glory Ltd. Paper sheet management system, paper sheet recognition apparatus, paper sheet management apparatus, paper sheet management method and paper sheet management program
EP2330569A1 (en) * 2008-08-08 2011-06-08 Glory Ltd. Paper notes management system, paper notes identification apparatus, paper notes management apparatus, method for managing paper notes, and program for managing paper notes
CN102800148A (en) * 2012-07-10 2012-11-28 中山大学 RMB sequence number identification method
CN103042822A (en) * 2013-01-11 2013-04-17 西安印钞有限公司 Control system and method of double identification code dynamic digit of presswork
CN103042822B (en) * 2013-01-11 2015-02-25 西安印钞有限公司 Control system and method of double identification code dynamic digit of presswork
CN110895849A (en) * 2018-09-13 2020-03-20 深圳怡化电脑股份有限公司 Method and device for cutting and positioning crown word number, computer equipment and storage medium

Also Published As

Publication number Publication date
US6697511B1 (en) 2004-02-24
US6510238B2 (en) 2003-01-21
AU4839000A (en) 2000-12-05
US20010053241A1 (en) 2001-12-20
US20040037456A1 (en) 2004-02-26

Similar Documents

Publication Publication Date Title
US6697511B1 (en) Partial read confirmation method
CN101567112B (en) Bill transaction system
US5917930A (en) Method for semi-continuous currency processing using separator cards
JP5914687B2 (en) Paper sheet processing apparatus, paper sheet sorting apparatus, and paper sheet sorting system
US11783659B2 (en) Method and device for storing information about objects fed to a self-service terminal
CN101354808B (en) Automatic teller machine and tracking method of paper currency
US7518517B2 (en) Verification method of goods using IC tags and equipment using the method
KR101554252B1 (en) Method of banknote management with banknote serial number recognition in ATM and the ATM the method applied thereto
KR101237220B1 (en) Bill recognition device, bill recognition system, and recording medium
JPWO2008056404A1 (en) Paper sheet identification device and paper sheet identification method
US20040245066A1 (en) Bill handling system and bill handling method
US7422117B2 (en) Continuous change order processing
JP2010086006A (en) Sheet processing system and method for checking the same
USRE38663E1 (en) Method for semi-continuous currency processing using separator cards
JP2006209163A (en) Control of cash automatic transaction device
JPH08249524A (en) Method for discriminating paper money and method for detecting plural number of paper moneys
JP2008140262A (en) Paper sheet transaction system
JP2005085134A (en) Paper currency processing device
JPH05250546A (en) Paper money managing device for automatic equipment
KR20180062824A (en) apparatus and method for counting medium
CN104952147A (en) Banknote processing device
CN112907240A (en) Cash counter dispensing method, device, equipment and medium based on counterfeit identification equipment
TW556127B (en) A learning method for detecting money
AU722106C (en) Method for semi-continuous currency processing using separator cards
JPS62180495A (en) Automatic cash depositor/dispensor

Legal Events

Date Code Title Description
AK Designated states

Kind code of ref document: A1

Designated state(s): AE AL AM AT AU AZ BA BB BG BR BY CA CH CN CR CU CZ DE DK DM EE ES FI GB GD GE GH GM HR HU ID IL IN IS JP KE KG KP KR KZ LC LK LR LS LT LU LV MA MD MG MK MN MW MX NO NZ PL PT RO RU SD SE SG SI SK SL TJ TM TR TT TZ UA UG US UZ VN YU ZA ZW

AL Designated countries for regional patents

Kind code of ref document: A1

Designated state(s): GH GM KE LS MW SD SL SZ TZ UG ZW AM AZ BY KG KZ MD RU TJ TM AT BE CH CY DE DK ES FI FR GB GR IE IT LU MC NL PT SE BF BJ CF CG CI CM GA GN GW ML MR NE SN TD TG

121 Ep: the epo has been informed by wipo that ep was designated in this application
REG Reference to national code

Ref country code: DE

Ref legal event code: 8642

122 Ep: pct application non-entry in european phase
NENP Non-entry into the national phase

Ref country code: JP