Source: http://www.google.com/patents/US20050175221?dq=6,370,566
Timestamp: 2016-08-30 22:52:20
Document Index: 317291767

Matched Legal Cases: ['art 100', 'art 100', 'art 100', 'art 100', 'art 100', 'art 100', 'art 200', 'art 200', 'art 200', 'art 200', 'art 200', 'art 200', 'art 300', 'art 300', 'art 300', 'art 300', 'art 300', 'art 400']

Patent US20050175221 - Method of determining usability of a document image and an apparatus therefor - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign inPatentsA method of processing a document comprises the steps of (a) scanning a document to capture image data associated with the document, (b) processing at least a portion of the captured image data to calculate a first count of pixels associated with a corner of the document, (c) processing at least a portion...http://www.google.com/patents/US20050175221?utm_source=gb-gplus-sharePatent US20050175221 - Method of determining usability of a document image and an apparatus thereforAdvanced Patent SearchPublication numberUS20050175221 A1Publication typeApplicationApplication numberUS 11/098,826Publication dateAug 11, 2005Filing dateApr 5, 2005Priority dateApr 16, 2001Also published asUS6912297, US7457440, US20020150279Publication number098826, 11098826, US 2005/0175221 A1, US 2005/175221 A1, US 20050175221 A1, US 20050175221A1, US 2005175221 A1, US 2005175221A1, US-A1-20050175221, US-A1-2005175221, US2005/0175221A1, US2005/175221A1, US20050175221 A1, US20050175221A1, US2005175221 A1, US2005175221A1InventorsDennis Scott, Nancy Stefanuk, Slawomir WesolkowskiOriginal AssigneeDennis Scott, Stefanuk Nancy B., Wesolkowski Slawomir B.Export CitationBiBTeX, EndNote, RefManPatent Citations (6), Referenced by (29), Classifications (17), Legal Events (4) External Links: USPTO, USPTO Assignment, EspacenetMethod of determining usability of a document image and an apparatus therefor
US 20050175221 A1Abstract
A method of processing a document comprises the steps of (a) scanning a document to capture image data associated with the document, (b) processing at least a portion of the captured image data to calculate a first count of pixels associated with a corner of the document, (c) processing at least a portion of the captured image data to calculate a second count of pixels associated with the corner of the document, and (d) determining if the corner of the document is missing or has a fold based upon the first count of pixels associated with the corner of the document and the second count of pixels associated with the corner of the document. The usability of the captured image data associated with the document is determined based upon the amount of information found missing from the image of the document due to, for examples, a torn or folded corner. If the torn or folded corner is determined to be large enough, then the corresponding image of the document is determined to be unusable. Images(11) Claims(14)
BRIEF DESCRIPTION OF THE DRAWINGS [0007] The foregoing and other features of the present invention will become apparent to one skilled in the art to which the present invention relates upon consideration of the following description of the invention with reference to the accompanying drawings, wherein: [0008] FIG. 1 is a block diagram representation of an image-based check processing system embodying the present invention; [0009] FIG. 2 is a diagram of a missing corner detection program shown in the system of FIG. 1; [0010] FIG. 3 is a flowchart depicting a missing corner size test which may be used in the missing corner detection program of FIG. 2 to determine if a corner of a check image is missing; [0011] FIG. 4 is a diagram which illustrates the missing corner size test shown in the flowchart of FIG. 3; [0012] FIG. 5 is a flowchart depicting another missing corner size test which may be used in the missing corner detection program of FIG. 2 to determine if a corner of a check image is missing; [0013] FIG. 6 is a diagram which illustrates the missing corner size test shown in the flowchart of FIG. 5; [0014] FIG. 7 is a flowchart depicting still another missing corner size test which may be used in the missing corner detection program of FIG. 2 to determine if a corner of a check image is missing; [0015] FIG. 8 is a diagram which illustrates the missing corner size test shown in the flowchart of FIG. 7; [0016] FIG. 9 is a flowchart depicting a fold/tear test which may be used in the missing corner detection program of FIG. 2 to determine if a missing corner of a document is a tear or a fold; and [0017] FIG. 10 is a diagram which illustrates the fold/tear test shown in the flowchart of FIG. 9.
DETAILS OF THE INVENTION [0018] The present invention is directed to a method of determining usability of a document image and an apparatus therefor. The document image may be provided in an image-based document processing system such as an image-based check processing system. The document may be of any type. By way of example, a document in the form of a bank check is processed in accordance with the present invention. [0019] Referring to FIG. 1, an image-based check processing system 10 includes a processing unit 18 which is electrically connected via bus line 20 to a display 22. The processing unit 18 is also electrically connected via bus line 32 to a keyboard 24 and via bus line 34 to a system memory 40. The system memory 40 includes memory space which stores, inter alia, scanned gray scale image data 42, and a number of application programs including a missing corner detection program 50 in accordance with the present invention which will be described in detail later. [0020] The check processing system 10 further includes a scanner device 30 which is electrically connected via bus line 28 to the processing unit 18. Preferably, the processing unit 18 is a microcomputer, and the system memory 40 is a random access type of memory. Suitable microcomputers and memories are readily available in the marketplace. Their structure and operation are well known and, therefore, will not be described. [0021] During operation, the scanner device 30 lifts an image of a bank check 12 when the check is moved past the scanner device. The scanner device 30 produces pixels each pixel having a particular gray level associated therewith. The gray level of the pixel is stored as gray scale image data 42 in the system memory 40 as shown in FIG. 1. The process of lifting an image of the check 12 and storing the image as gray scale image data 42 in system memory 40 is known and, therefore, will not be described. The gray scale image data 42 associated with all the pixels form a gray scale image of the check 12. The gray scale image of the check 12 is displayed on the display 22. The missing corner detection program 50 then processes the gray scale image data 42, as described in detail hereinbelow, to determine usability of the gray image of the check 12. [0022] Referring to FIG. 2, the missing corner detection program 50 shown in FIG. 1 includes a first subprogram 60 and a second subprogram 70. The first subprogram 60 comprises a missing corner size test, and the second subprogram 70 comprises a fold/tear test. Preferably, the missing corner size test 60 is executed before the fold/tear test 70. However, it is contemplated that the fold/tear test 70 may be executed before the missing corner size test 60. [0023] Referring to FIG. 3, a flowchart 100 depicts one form of the missing corner size test 60 which may be carried out by the missing corner detection program 50 to determine if a corner of the gray scale image of the check 12 is missing. The form of the test depicted in the flowchart 100 is referred to herein as the one-line test. By way of example, the one-line test depicted in the flowchart 100 is applied to the upper left corner of the check 12. The one-line test depicted in the flowchart 100 can be easily modified to apply to other corners of the check 12. Before the one-line test depicted in flowchart 100 is run, the gray scale image is cropped correctly both horizontally and vertically. When the image is cropped, the width of the image and the height of the image are known. [0024] In step 102 of the flowchart 100, a pixel counter is initialized to zero. The program proceeds to step 104 in which a pixel at the upper left corner extremity of the document (i.e., the check 12 in this instance) is examined. The pixel at the upper left corner extremity of the check 12 is shown in FIG. 4 as reference numeral 190. In step 106, a determination is made as to whether the pixel (i.e., the pixel at the upper left corner extremity in this instance) is part of the check 12. If the determination in step 106 is affirmative, then this particular corner of the check 12 is considered a good corner (as indicated in step 107) and the program proceeds to step 108 in which a determination is made as to whether all corners of the check 12 have been looked at and tested. If the determination in step 108 is affirmative, then the gray scale image data representative of the gray scale image of the check 12 is deemed to be of good enough quality to provide a good usable image, as shown in step 110. An indication of a good usable image of the check 12 is provided on the display 22. However, if the determination in step 108 is negative, the program 60 proceeds look at the next corner of the check 12, as shown in step 112, and returns back to step 102 to repeat the same previous program steps for this next corner. [0025] However, if the determination back in step 106 is negative, the program proceeds to step 114 in which the pixel counter is incremented by a count of one before proceeding to step 116. In step 116, a determination is made as to whether the pixel counter is now greater than a predetermined fold/tear threshold. This predetermined fold/tear threshold may be set to any positive integer value. If the determination in step 116 is negative, the program proceeds to step 118 in which the next pixel which lies diagonally from the present pixel is examined. This next pixel is shown in FIG. 4 as reference numeral 191. The program returns back to step 106 to repeat the same previous program steps for this next pixel. However, if the determination back in step 116 is affirmative, the program proceeds to step 120 in which the corner of document presently under consideration is deemed to be missing. The program then proceeds to the fold/tear test 70 of FIG. 9, as shown in step 122, which will be described in detail below. [0026] Referring to FIG. 5, a flowchart 200 depicts another form of the missing corner size test 60 which may be carried out by the missing corner detection program 50 to determine if a corner of the gray scale image of the check 12 is missing. The form of the test depicted in the flowchart 200 is referred to herein as the area test. By way of example, the area test depicted in the flowchart 200 is applied to the upper left corner of the check 12. The area depicted in the flowchart 200 can be easily modified to apply to other corners of the check 12. Before the area test depicted in flowchart 200 is run, the gray scale image is cropped correctly both horizontally and vertically. When the image is cropped, the width of the image and the height of the image are known. [0027] In step 202 of the flowchart 200, three counters designated “i”, “j”, and “k” are initialized to zero. The program proceeds to step 204 in which a pixel at a corner extremity of the document (i.e., the check 12 in this instance) is examined. An example of a pixel at a corner extremity of the check 12 is shown in FIG. 6 as reference numeral “290”. In step 206, a determination is made as to whether the pixel (i.e., the pixel at the corner extremity in this instance) is part of the check 12. If the determination in step 206 is affirmative, then this particular corner of the check 12 is considered a good corner (as indicated in step 207) and the program proceeds to step 208 in which a determination is made as to whether all corners of the check 12 have been looked at and tested. If the determination in step 208 is affirmative, then the gray scale image data representative of the gray scale image of the check 12 is deemed to be of good enough quality to provide a good usable image, as shown in step 210. An indication of a good usable image of the check 12 is provided on the display 22. However, if the determination in step 208 is negative, the program proceeds to look at the next corner of the check 12, as shown in step 212, and returns back to step 202 to repeat the same previous program steps for this next corner. [0028] However, if the determination back in step 206 is negative, the program proceeds to step 214 in which the counter “i” is incremented by a count of one and the counter “k” is also incremented by a count of one before proceeding to step 216. In step 216, a determination is made as to whether the counter “k” is now greater than a predetermined fold/tear threshold. This predetermined fold/tear threshold may be set to any positive integer value. If the determination in step 216 is affirmative, the program proceeds to step 218 in which the corner of the check 12 presently under consideration is deemed to be missing. The program then proceeds to the fold/tear test 70 of FIG. 9, as shown in step 220, which will be described in detail below. [0029] However, if the determination back in step 216 is negative, the program proceeds to step 222 in which a determination is made as to whether the counter “i” is less the width of the image. If the determination in step 222 is affirmative, the program proceeds to step 224 in which the next pixel which lies horizontally from the present pixel is examined. This next pixel is shown in FIG. 6 as reference numeral 291. The program returns back to step 206 to repeat the same previous program steps for this next pixel. [0030] However, if the determination back in step 222 is negative, the program proceeds to step 226 in which the counter “j” is incremented by a count of one before proceeding to step 228. In step 228, a determination is made as to whether the counter “j” is less than the height of the image. If the determination in step is affirmative, the program proceeds to step 230 in which the next pixel which lies one line vertically and to the beginning of the next line of pixels from the present pixel is examined. This next pixel is shown in FIG. 6 as reference numeral 292. The program returns back to step 206 to repeat the same previous program steps for this next pixel. [0031] However, if the determination back in step 228 is negative, then this corner of the check 12 is deemed to be a good corner, as shown in step 232. A determination is then made in step 234 as to whether all corners of the check 12 have been looked at and tested. If the determination in step 234 if affirmative, then the gray scale image data representative of the gray scale image of the check 12 is deemed to be of good enough quality to provide a good usable image, as shown in step 236. An indication of a good usable image of the check 12 is provided on the display 22. However, if the determination in step 234 is negative, the program proceeds to look at the next corner of the check 12, as shown in step 238, and returns back to step 202 to repeat the same previous program steps for this next corner. [0032] Referring to FIG. 7, a flowchart 300 depicts still another form of the missing corner size test 60 which may be carried out by the missing corner detection program 50 to determine if a missing corner of a check is either a fold or a tear. The form of the test depicted in the flowchart 300 is referred to herein as the two-line test. By way of example, the two-line test depicted in the flowchart 300 is applied to the upper left corner of the check 12. The two-test depicted in the flowchart 300 can be easily modified to apply to other corners of the check 12. Before the two-line test depicted in flowchart 300 is run, the gray scale image is cropped correctly both horizontally and vertically. When the image is cropped, the width of the image and the height of the image are known. [0033] In step 302, counters and flags are initialized. More specifically, counter “i” and counter “j” are set to zero, and flags “xFLAG” and “yFLAG” are cleared. The program proceeds to step 303 in which a pixel at the upper left corner extremity of the document (i.e., the check 12 in this instance) is examined. The pixel at the upper left corner extremity of the check 12 is shown in FIG. 8 as reference numeral 390. A determination is made in step 304 as to whether xFLAG is set. If the determination in step 304 is affirmative, the program proceeds directly to step 310. However, if the determination in step 304 is negative, the program proceeds to step 306 in which a determination is made as to whether the pixel at coordinates position (i, j) is part of the check 12. If the determination in step 306 is negative, the program proceeds to step 310. However, if the determination in step 306 is affirmative, the program proceeds to step 308 in which the xFLAG is set before proceeding to step 310. [0034] In step 310, a determination is made as to whether the yFLAG is set. If the determination in step 310 is affirmative, the program proceeds directly to step 316. However, if the determination in step 310 is negative, the program proceeds to step 312 in which a determination is made as to whether the pixel at coordinates position (j, i) is part of the check 12. If the determination in step 312 is negative, the program proceeds to step 316. However, if the determination in step 312 is affirmative, the program proceeds to step 314 in which the yFLAG is set before proceeding to step 316. [0035] In step 316, a determination is made as to whether both flags xFLAG and yFLAG are set. If the determination in step 316 is affirmative, then this particular corner of the check 12 is considered a good corner (as indicated in step 318) and the program proceeds to step 320 in which a determination is made as to whether all corners of the check 12 have been looked at and tested. If the determination in step 320 is affirmative, then the gray scale image data representative of the gray scale image of the check 12 is deemed to be of good enough quality to provide a good usable image, as shown in step 322. An indication of a good usable image of the check 12 is provided on the display 22. However, if the determination in step 320 is negative, the program 60 proceeds to look at the next corner of the check 12, as shown in step 324, and returns back to step 302 to repeat the same previous program steps for this next corner. [0036] However, if the determination back in step 316 is negative, the program proceeds to step 326 in which the counter “i” is incremented by a count of one before proceeding to step 328. In step 328, a determination is made as to whether the remainder of “i” divided by “N” (which is represented mathematically as “i MOD N”) is equal to zero, wherein “i” is the value of counter “i” and “N” is an integer representing the number of pixels in a row (or a column) to be considered. As shown in FIG. 8, the integer “N” is equal to three. Although the integer “N” is chosen to be three in this example, it is contemplated that “N” could have been chosen to be some other integer. [0037] If the determination in step 328 is negative, the program proceeds directly to step 332. However, if the determination in step 328 is affirmative, the program proceeds to step 330 in which the counter “j” is incremented by a count of one before proceeding to step 332. In step 332, a determination is made as to whether the counter “i” is greater than or equal to a predetermined fold/tear threshold. If the determination in step 332 is negative, the program returns back to step 304 to repeat steps previously described. However, if the determination in step 332 is affirmative, the program proceeds to step 334 in which the corner of the check 12 presently under consideration is deemed to be missing. The program then proceeds to the fold/tear test 70 of FIG. 9, as shown in step 336, which will be described in detail. [0038] Referring to FIG. 9, a flowchart 400 depicts the fold/tear test 70 which may be carried out by the missing corner detection program 50 to determine if a missing corner of a check is either a fold or a tear. In step 402, a “first” pixel which is part of the check 12 and which lies along the horizontal edge of the check 12 is identified. Such a pixel is designated with reference numeral 490 in FIG. 10. Then in step 404, a “first” pixel which is part of the check 12 and which lies along the vertical edge of the check 12 is identified. Such a pixel is designated with reference numeral 491 in FIG. 10. The program proceeds to step 406 in which a straight line is drawn between the pixel 490 identified in step 402 and the pixel 491 identified in step 404. This straight line is designated with reference numeral 492 shown in FIG. 10. The program then proceeds to step 408. [0039] In step 408, the number of pixels between each point along the straight line 492 and the actual edge of the check 12 is counted. For example, as shown in FIG. 10, the number of pixels between point 493 on the straight line 492 to the actual edge of the check 12 is one. Similarly, the number of pixels between point 494 on the straight line 492 to the actual edge of the check 12 is two, the number of pixels between point 495 on the straight line 492 to the actual edge of the check 12 is four, and the number of pixels between point 496 on the straight line 492 to the actual edge of the check 12 is three. [0040] A determination is then made in step 410 as to whether the average count of the pixels between the straight line 492 and the actual edge of the check 12 is greater than a predetermined threshold. If the determination in step 410 is affirmative, the missing corner of the check 12 is deemed to be a tear, as shown in step 416. Then, as shown in step 418, the program returns to the earlier run missing corner size test 60 and is run again another predetermined fold/tear threshold to determine if the image is considered to be a good usable image. This predetermined fold/tear threshold may be the same or different from the earlier described predetermined fold/tear thresholds. However, if the determination in step 410 is negative, the missing corner of the check 12 is deemed to be a fold, as shown in step 412, and the image is considered to be unusable, as shown in step 414. [0041] It should be apparent from the above description that the usability of captured image data associated with a document is determined based upon the amount of information found missing from the image of the document due to, for examples, a torn or folded corner. If the torn or folded corner is determined to be large enough, then the corresponding image of the document is determined to be unusable. [0042] The above description provides three forms of the missing corner size test 60 (i.e., the one-line test, the area test, and the two-line test) and one form of the fold/tear test 70. It is contemplated that other forms of the missing corner size test 60 and/or the fold/tear test 70 may be used. It is also contemplated that the missing corner size test 60 and the fold/tear test 70 may be combined into a single program. Alternatively, either one of the programs may be broken out into a number of subprograms. [0043] Although the above description describes the missing corner detection program 50 as being applied to a gray scale image of a check, it is contemplated that the missing corner detection program 50 may be applied to different types of images of a check, such as a color image of a check or a binary image of a check, for examples. [0044] Also, it is contemplated that the missing corner detection program 50 may be applied to other types of image-enabled environments. For example, the missing corner detection program 50 may be applied to images in an electronic check presentment (ECP) system. In an ECP system, the missing corner detection program 50 may be applied by either the sending bank or the receiving bank to determine usability of images. [0045] A number of advantages result by determining usability of a check image as described hereinabove. One advantage is that folded and torn corners of documents are detected quickly and with high accuracy. Another advantage is that documents with no missing corners are processed very quickly. Yet another advantage is that the missing corner detection program 50 may be tuned to different types of documents since parameters are configurable. For example, if an application has a priori knowledge of the design of documents, then parameters may be tuned to accurately determine whether a document image is usable when there is missing information. [0046] From the above description of the invention, those skilled in the art to which the present invention relates will perceive improvements, changes and modifications. Numerous substitutions and modifications can be undertaken without departing from the true spirit and scope of the invention. Such improvements, changes and modifications within the skill of the art to which the present invention relates are intended to be covered by the appended claims. Patent CitationsCited PatentFiling datePublication dateApplicantTitleUS4429991 *Aug 17, 1981Feb 7, 1984The Perkin-Elmer CorporationMethod for detecting physical anomalies of U.S. currencyUS4623975 *Nov 17, 1982Nov 18, 1986Tokyo Shibaura Denki Kabushiki KaishaMethod and apparatus for detecting the profile and feeding state of paper sheetsUS5323473 *Apr 2, 1992Jun 21, 1994Ncr CorporationMethod and apparatus for detecting the leading and trailing edges of a document in an image based systemUS5751841 *Feb 20, 1996May 12, 1998Ncr CorporationMethod and apparatus for scanning bank notesUS6408094 *Nov 4, 1997Jun 18, 2002Eastman Kodak CompanyDocument image assessment system and methodUS6845288 *Apr 15, 2002Jan 18, 2005Heidelberger Druckmaschinen AgMethod and device for measuring a position of a passing sheet* Cited by examinerReferenced byCiting PatentFiling datePublication dateApplicantTitleUS7283656Mar 14, 2005Oct 16, 2007Federal Reserve Bank Of ClevelandAssessing electronic image qualityUS7594600Feb 22, 2006Sep 29, 2009Federal Reserve Bank Of AtlantaExpanded mass data sets for electronic check processingUS7686209Mar 30, 2010Federal Reserve Bank Of DallasCash letter print streams with audit dataUS7689004Sep 12, 2006Mar 30, 2010Seiko Epson CorporationMethod and apparatus for evaluating the quality of document imagesUS7802717Sep 28, 2010Federal Reserve Bank Of DallasElectronic image cash letter monitoringUS7918386Nov 6, 2007Apr 5, 2011Federal Reserve Bank Of Kansas CityCash letter print verificationUS8032462Jul 7, 2006Oct 4, 2011Federal Reserve Bank Of Kansas CityElectronic image cash letter balancingUS8112357Feb 7, 2012Federal Reserve Bank Of AtlantaSystems and methods for preventing duplicative electronic check processingUS8167196May 1, 2012Federal Reserve Bank Of AtlantaExpanded mass data sets for electronic check processingUS8196814Mar 24, 2010Jun 12, 2012Federal Reserve Bank Of DallasCash letter print streamsUS8238638Aug 7, 2012Federal Reserve Bank Of Kansas CityTag validation for efficiently assessing electronic check image qualityUS8296223Oct 23, 2012Federal Reserve Bank Of AtlantaSystem and method for processing duplicative electronic check reversal filesUS8387862May 16, 2007Mar 5, 2013Federal Reserve Bank Of DallasElectronic image cash letter validationUS8573498Nov 6, 2007Nov 5, 2013Federal Reserve Bank Of Kansas CityIdentifying duplicate printed paper cash lettersUS8595096Nov 6, 2007Nov 26, 2013Federal Reserve Bank Of RichmondPrioritizing checks for electronic check processingUS20050213805 *Mar 14, 2005Sep 29, 2005Blake James AAssessing electronic image qualityUS20060191998 *Feb 22, 2006Aug 31, 2006Federal Reserve Bank Of AtlantaCash letter print streams with audit dataUS20060237526 *Feb 22, 2006Oct 26, 2006Federal Reserve Bank Of AtlantaExpanded mass data sets for electronic check processingUS20070235518 *Jul 7, 2006Oct 11, 2007Federal Reserve Bank Of AtlantaElectronic image cash letter monitoringUS20080006687 *May 16, 2007Jan 10, 2008Federal Reserve Bank Of AtlantaElectronic image cash letter validationUS20080063240 *Sep 12, 2006Mar 13, 2008Brian KengMethod and Apparatus for Evaluating the Quality of Document ImagesUS20080159655 *Nov 6, 2007Jul 3, 2008Federal Reserve Bank Of RichmondPrioritizing checks for electronic check processingUS20080162319 *Nov 6, 2007Jul 3, 2008Breeden Benjamin TSystem and method for processing duplicative electronic check reversal filesUS20080162320 *Nov 6, 2007Jul 3, 2008Federal Reserve Bank Of AtlantaSystems and methods for preventing duplicative electronic check processingUS20080162321 *Nov 6, 2007Jul 3, 2008Breeden Benjamin TSystem and method for processing duplicative electronic check return filesUS20080162322 *Nov 6, 2007Jul 3, 2008Federal Reserve Bank Of RichmondAutomated return item re-clearUS20090114711 *Nov 6, 2007May 7, 2009Randall Lee MuellerCash letter print verificationUS20090196485 *Jan 31, 2008Aug 6, 2009Federal Reserve Bank Of Kansas CityTag validation for efficiently assessing electronic check image qualityUS20100176192 *Jul 15, 2010Federal Reserve Bank Of DallasCash Letter Print Streams* Cited by examinerClassifications U.S. Classification382/112International ClassificationG06T5/00, G06T7/60, B65H43/00, G06T7/00Cooperative ClassificationG06T7/0006, B65H2701/1912, G06T2207/10008, B65H2553/40, B65H43/00, B65H2511/16, G06T7/602, G06T2207/30176, B65H2701/1322European ClassificationB65H43/00, G06T7/60A, G06T7/00B1DLegal EventsDateCodeEventDescriptionJan 23, 2012FPAYFee paymentYear of fee payment: 4Jan 15, 2014ASAssignmentOwner name: JPMORGAN CHASE BANK, N.A., AS ADMINISTRATIVE AGENTFree format text: SECURITY AGREEMENT;ASSIGNORS:NCR CORPORATION;NCR INTERNATIONAL, INC.;REEL/FRAME:032034/0010Effective date: 20140106Apr 18, 2016ASAssignmentOwner name: JPMORGAN CHASE BANK, N.A., ILLINOISFree format text: SECURITY AGREEMENT;ASSIGNORS:NCR CORPORATION;NCR INTERNATIONAL, INC.;REEL/FRAME:038646/0001Effective date: 20160331May 25, 2016FPAYFee paymentYear of fee payment: 8RotateOriginal ImageGoogle Home - Sitemap - USPTO Bulk Downloads - Privacy Policy - Terms of Service - About Google Patents - Send FeedbackData provided by IFI CLAIMS Patent Services