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An image compression method based on symbol matching is disclosed. Precompression of the image is performed prior to symbol matching to improve efficiency. A voting scheme is used in conjunction with a plurality of novel similarity tests to improve symbol matching accuracy. A template composition scheme achieves image enhancement. Other disclosed features provide further advantages. Apparatus for implementing the image compression method for image transmission, storage, and enhancement are included.

Inventors: Peter B. Mark, Stuart M. Shieber
Original Assignee: Cartesian Products, Inc.
Primary Examiner: Jon C. Chang
Current U.S. Classification: 382/235; 358/426.13; 382/209; 382/243
International Classification: G06K 936; G06K 946

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Citations

Cited PatentFiling dateIssue dateOriginal AssigneeTitle
US4091424Feb 18, 1977May 23, 1978Compression Labs, Inc.Facsimile compression system
US4288782Aug 24, 1979Sep 8, 1981Compression Labs, Inc.High speed character matcher and method
US4410916Jul 9, 1981Oct 18, 1983Compression Labs, Inc.Dual mode facsimile coding system and method
US4426731Oct 16, 1981Jan 17, 1984International Business Machines CorporationCharacter recognition employing compressed image data
US4463386May 3, 1982Jul 31, 1984International Business Machines CorporationFacsimile data reduction
US4499499Dec 29, 1982Feb 12, 1985International Business Machines CorporationMethod for identification and compression of facsimile symbols in text processing systems
US4606069Jun 10, 1983Aug 12, 1986AT&T Bell LaboratoriesApparatus and method for compression of facsimile information by pattern matching
US4628534Jul 6, 1984Dec 9, 1986Honeywell Information Systems Inc.Method for changing the resolution of compressed image data
US4773098Aug 1, 1983Sep 20, 1988Texas Instruments IncorporatedMethod of optical character recognition
US4887304Mar 16, 1989Dec 12, 1989Raytheon CompanyLibrary image optimization
US5109432Dec 27, 1989Apr 28, 1992Fujitsu Limited
Fujitsu Tohoku Electronics
Honda Electron Co., Ltd.		Character recognition method
US5121444Jun 6, 1990Jun 9, 1992Eastman Kodak CompanyPattern recognition apparatus

Referenced by

Citing PatentFiling dateIssue dateOriginal AssigneeTitle
US5384643Mar 4, 1994Jan 24, 1995Automate Medical Access CorporationImage transmission system with patterned data compression
US5577183Dec 1, 1995Nov 19, 1996Hewlett-Packard CompanyPrinter system that stores compressed font glyphs in data blocks and decompressed glyphs in each data block together using same decompression procedure
US5594809Apr 28, 1995Jan 14, 1997Xerox CorporationAutomatic training of character templates using a text line image, a text line transcription and a line image source model
US5689620Apr 28, 1995Nov 18, 1997Xerox CorporationAutomatic training of character templates using a transcription and a two-dimensional image source model
US5706364Apr 28, 1995Jan 6, 1998Xerox CorporationMethod of producing character templates using unsegmented samples
US5764808Oct 26, 1995Jun 9, 1998Motorola, Inc.Method and device for compact representation of a discrete region contour
US5778095Dec 20, 1995Jul 7, 1998Xerox CorporationClassification of scanned symbols into equivalence classes
US5784284Dec 29, 1995Jul 21, 1998Snap-on Tools CompanyTechnique for plotting a variable-width signal in a fixed-width plot area
US5809167Jan 8, 1997Sep 15, 1998Canon Kabushiki KaishaPage segmentation and character recognition system
US5818965Dec 20, 1995Oct 6, 1998Xerox CorporationConsolidation of equivalence classes of scanned symbols
US5832126Jul 3, 1996Nov 3, 1998Oki Data CorporationMethod and apparatus for compressing mixed text and image data
US5835638May 30, 1996Nov 10, 1998Xerox CorporationMethod and apparatus for comparing symbols extracted from binary images of text using topology preserved dilated representations of the symbols
US5883986Jun 2, 1995Mar 16, 1999Xerox CorporationMethod and system for automatic transcription correction
US5884014May 23, 1996Mar 16, 1999Xerox CorporationFontless structured document image representations for efficient rendering
US5898794Jun 18, 1997Apr 27, 1999Fujitsu LimitedImage compression method and image processing system
US5901246Jun 6, 1995May 4, 1999Ergonomic man-machine interface incorporating adaptive pattern recognition based control system
US5920658Mar 11, 1997Jul 6, 1999Ricoh Company Ltd.Efficient image position correction system and method
US5956419Apr 28, 1995Sep 21, 1999Xerox CorporationUnsupervised training of character templates using unsegmented samples
US6011905Nov 8, 1996Jan 4, 2000Xerox CorporationUsing fontless structured document image representations to render displayed and printed documents at preferred resolutions
US6016361Nov 5, 1997Jan 18, 2000NEC CorporationMethod and apparatus for compressing binary data using pattern matching encoding
US6020972Nov 14, 1997Feb 1, 2000Xerox CorporationSystem for performing collective symbol-based compression of a corpus of document images
US6041137Aug 25, 1995Mar 21, 2000Microsoft CorporationRadical definition and dictionary creation for a handwriting recognition system
US6064774Jan 20, 1998May 16, 2000Ricoh Company, Ltd.Image processing method and system and computer program product therefor
US6094453Jan 16, 1997Jul 25, 2000Digital Accelerator CorporationDigital data compression with quad-tree coding of header file
US6185330Mar 18, 1998Feb 6, 2001NEC CorporationDevice and record medium for pattern matching encoding/decoding of binary still images
US6252993Sep 17, 1997Jun 26, 2001Sony CorporationVideo signal coding and decoding method
US6275301May 14, 1999Aug 14, 2001Xerox CorporationRelabeling of tokenized symbols in fontless structured document image representations
US6275610Oct 8, 1997Aug 14, 2001Convey CorporationFile structure for scanned documents
US6324305Dec 22, 1998Nov 27, 2001Xerox CorporationMethod and apparatus for segmenting a composite image into mixed raster content planes
US6327384Nov 13, 1997Dec 4, 2001NEC CorporationCharacter recognition apparatus and method for recognizing characters
US6343152Mar 27, 1997Jan 29, 2002Peerless Systems CorporationBi-level image compression by gray scale encoding
US6373981Dec 21, 1998Apr 16, 2002Xerox CorporationMethod and apparatus for segmenting data to create mixed raster content planes
US6381368Dec 1, 1998Apr 30, 2002Canon Kabushiki KaishaImage processing apparatus and method
US6400844Dec 2, 1998Jun 4, 2002Xerox CorporationMethod and apparatus for segmenting data to create mixed raster content planes
US6400996Feb 1, 1999Jun 4, 2002Adaptive pattern recognition based control system and method
US6418424May 4, 1999Jul 9, 2002Ergonomic man-machine interface incorporating adaptive pattern recognition based control system
US6539113Dec 29, 1999Mar 25, 2003Microsoft CorporationRadical definition and dictionary creation for a handwriting recognition system
US6574367Jan 7, 1998Jun 3, 2003NEC CorporationMethod and apparatus for pattern matching encoding
US6614939Aug 4, 1998Sep 2, 2003Matsushita Electric Industrial Co., LTDImage compression apparatus and decoding apparatus suited to lossless image compression
US6640145Jun 3, 2002Oct 28, 2003Media recording device with packet data interface
US6658148Jun 6, 2000Dec 2, 2003Matsushita Electric Works, Ltd.Image processing method and apparatus
US6701022Jan 17, 2001Mar 2, 2004NEC CorporationPattern matching coding device and method thereof
US6748115Jun 18, 1999Jun 8, 2004Cvision Technologies LLCPerceptually lossless image compression
US6778291Jun 12, 2000Aug 17, 2004Hewlett-Packard Development Company, L.P.Fast page analyzer for proper selection of compression engine for rendered data
US6778712Aug 29, 2000Aug 17, 2004Fujitsu LimitedData sheet identification device
US6832007Nov 21, 2000Dec 14, 2004Xerox CorporationMethod and system for compensating for scaling artifacts in mixed raster content (MRC) representations
US7017816Sep 30, 2003Mar 28, 2006Hewlett-Packard Development Company, L.P.Extracting graphical bar codes from template-based documents
US7024049Jan 16, 2002Apr 4, 2006Xerox CorporationMethod and apparatus for improving image appearance
US7068844Nov 15, 2001Jun 27, 2006The University of ConnecticutMethod and system for image processing for automatic road sign recognition
US7076109Mar 28, 2002Jul 11, 2006International Business Machines CorporationSystem and method of automatically determining the dominant periodicity in sequential binary data
US7164369Jun 19, 2001Jan 16, 2007Sharp Laboratories of America, Inc.System for improving storage efficiency of digital files
US7242988Mar 2, 1999Jul 10, 2007Adaptive pattern recognition based controller apparatus and method and human-factored interface therefore
US7492957Aug 29, 2005Feb 17, 2009Symantec CorporationUsing run length encoding to detect target images
US7974714Aug 29, 2006Jul 5, 2011Intelligent electronic appliance system and method
US8019164Jan 29, 2008Sep 13, 2011Hitachi High-Technologies CorporationApparatus, method and program product for matching with a template
US8046313Nov 13, 2006Oct 25, 2011Ergonomic man-machine interface incorporating adaptive pattern recognition based control system
US8155312Sep 14, 2006Apr 10, 2012The University of ConnecticutOptical data storage device and method

Claims

1. A method for compressing images comprising:

precompressing a first representation of an image, said first representation based on pixels of a first type and a second type, to generate a precompressed representation of said image,
identifying symbols in said precompressed representation of said image,
comparing a plurality of identified symbols to each of at least one template from a library of templates to match identified symbols to templates, and
generating a compressed representation of said image including a representation of templates, and an indication of a location and a template for symbols in said image.

2. The method of claim 1 wherein said first representation of an image is precompressed by rim-length encoding.

3. The method of claim 2 wherein said first representation is based on rows and columns of pixels, and symbols are identified by associating runs of said first type of pixel in adjacent rows of said precompressed representation which have at least one pixel of said first type in the same column or in the same or adjacent columns.

4. A method for compressing images comprising:

identifying symbols in a first representation of an image,
comparing a plurality of identified symbols to each of at least one template from a library of templates to match identified symbols to templates, wherein said library is augmented during image compression by storing in said library symbols for which no matching template is found as new templates, and wherein each template is defined by a representation determined by a plurality of the symbols which match, wherein each template is defined by a unique spatial distribution of pixels, said distribution determined by the distributions of pixels of a plurality of the symbols which match said template, and
generating a compressed representation of said image including a representation of templates, and an indication of a location and a template for symbols in said image.

5. The method of claim 4 wherein the distribution of pixels defining a template is determined by averaging the distributions of pixels of a plurality of the symbols which match said template.

6. The method of claim 4 wherein the distribution of pixels defining a template is determined by taking one symbol matching the template and changing a pixel in that symbol only if more than a predetermined fraction of the other symbols matching the template disagree with that pixel.

7. A method for compressing images comprising:

identifying symbols in a first representation of an image,
comparing a plurality of identified symbols to each of at least one template in a library of templates to match identified symbols to templates, said comparing step including identifying error locations, performing at least one test on said error locations and on other global features of the symbol and the template, and declaring a match between a symbol and a template only if all of the tests in at least one of a set of predetermined groups of tests are passed, and
generating a compressed representation of said image including a representation of templates, and an indication of a location and a template for symbols in said image.

8. The method of claim 7 wherein said first representation is based on rows and columns of pixels of a first type and a second type, said comparing step including identifying error pixel locations which have a pixel of said first type in only said symbol or said template, but not both, and performing at least one test on said error pixel locations and other global features of the symbol and the template, a match between a symbol and a template being declared only if all of the tests in at least one of a set of predetermined groups of tests are passed.

9. The method of claim 8 wherein said error locations are run-length encoded.

10. The method of claim 8 wherein one of said at least one test is passed if the distance between each error pixel location and the nearest pixel of the first type in the template or symbol having a pixel of the second type at the error pixel location is less than a predetermined value.

11. The method of claim 8 wherein one of said at least one test is passed if the distance between each error pixel location and the nearest pixel of the second type in the template or symbol having a pixel of the first type at the error pixel location is less than a predetermined value.

12. The method of claim 8 wherein one of said at least one test depends on the sizes, shapes, and orientations of contiguous groups of error pixels in some error map.

13. The method of claim 12 wherein one of said at least one test is passed if all contiguous groups of error pixel locations are smaller than predetermined patterns of pixels.

14. The method of claim 7 wherein one of said at least one test is passed if inferred shifts of the symbol relative to the template are consistent.

15. The method of claim 14 wherein shifts are inferred from the sizes, shapes, and orientations of contiguous groups of error pixel locations and their relation to adjacent pixels.

16. The method of claim 15 wherein shifts are inferred from triangles of pixels in the template and symbol error maps such that the inferred shift is towards or away from the fourth pixel in the square bounding the triangle depending on whether said fourth pixel has the same or different parity, respectively, as the triangle pixels in the template.

17. The method of claim 8 wherein one of said at least one test is passed if the difference in heights between a template and a symbol is less than a predetermined value.

18. The method of claim 8 wherein one of said at least one test is passed if the difference in widths between a template and a symbol is less than a predetermined value.

19. The method of claim 8 wherein one of said at least one test is passed if the ratio of the number of pixels of the first type in the symbol and the number of pixels of the first type in the template is within a redetermined range.

20. The method of claim 8 wherein one of said at least one test is passed if the ratio of the number of error pixel locations to the number of pixels of the first type in said template or said symbol, or the minimum or maximum of the two, is less than a predetermined value.

21. The method of claim 8 wherein one of said at least one test is passed if the ratio of the number of error pixel locations to the number of pixels of the first type adjacent to a pixel of said second type in said template or said symbol, or the minimum or maximum of the two, is less than a predetermined value.

22. The method of claims 7 or 8 wherein at least one of said at least one test depends on symbol size.

23. A method for compressing images comprising:

identifying symbols in a first representation of an image,
comparing a plurality of identified symbols to each of at least one template in a library of templates to match identified symbols to templates, wherein each said template is defined by a representation based on a spatial distribution of pixels of a first type, and
generating a compressed representation of said image including a representation of templates, and an indication of a location and a template for symbols in said image, wherein the representation of a plurality of said templates is a representation of the boundary of the spatial distribution of pixels of the first type for the templates.

24. A method for compressing images comprising:

identifying symbols in a first representation of an image,
comparing a plurality of identified symbols to each of at least one template in a library of templates to match identified symbols to templates, and
generating a compressed representation of said image including a representation of templates, and an indication of a location and a template for symbols in said image, wherein the representation of a plurality of said templates comprises a reference to a frame template for defining an outer boundary of said template and a list of hole templates with associated positions within said frame template for defining any inner boundaries of said template.

25. The method of claim 24 wherein said frame templates and hole templates are represented by representations of the boundary of said frame templates and hole templates.

26. A method for compressing images comprising:

identifying symbols in a first representation of an image,
comparing a plurality of identified symbols to each of at least one template in a library of templates to match identified symbols to templates, wherein the templates are indexed in said library according to template features, and wherein said step of comparing proceeds according to the index, whereby those templates more likely, based on features, to match a symbol are compared to the symbol before templates less likely to match, and those templates whose indexed features indicate that the likelihood of a match falls below a predetermined threshold are not compared, and
generating a compressed representation of said image including a representation of templates, and an indication of a location and a template for symbols in said image.

27. The method of claims 1, 2, or 3 wherein each template is defined by a unique spatial distribution of pixels, said distribution determined by the distributions of pixels of a plurality of the symbols which match said template.

28. The method of claim 4 wherein said comparing step includes identifying error locations, performing at least one test on said error locations and on other global features of the symbol and the template, and declaring a match between a symbol and a template only if all of the tests in at least one of a set of predetermined groups of tests are passed.

29. The method of claims 1, 2, or 3 wherein said comparing step includes identifying error pixel locations which have a pixel of said first type in only said symbol or said template, but not both, and performing at least one test on said error pixel locations and on other global features of the symbol and the template, a match between a symbol and a template being declared only if all of the tests in at least one of a set of predetermined groups of tests are passed.

30. The method of claims 1, 2, 3, 4, 7 or 8 wherein said first representation is based on pixels of a first type and a second type, and the representation of a plurality of said templates is a representation of the boundary of the spatial distribution of pixels of the first type for the template.

31. The method of claims 1, 2, 3, 4, 7 or 8 wherein the representation of each said template comprises a reference to a frame template for defining an outer boundary of said template and a list of hole templates with associated positions within said frame template for defining any inner boundaries of said template.

32. The method of claims 1, 2, 3, 4, 7, 8, 23 or 24 wherein the templates are indexed in said library according to template features, and wherein said step of comparing proceeds according to the index, whereby those templates more likely, based on features, to match a symbol are compared to the symbol before templates less likely to match, and those templates whose indexed features indicate that the likelihood of a match falls below a predetermined threshold are not compared.

33. The method of claims 1, 2, 3, 4, 7, 8, 23, 24, or 26 further comprising reducing the resolution of the representation of a plurality of templates.

34. The method of any of claims 1, 2, 3, 4, 7, 8, 23, 24 or 26 wherein said compressed representation of said image includes a plurality of data streams, and wherein at least one of said streams is further compressed.

35. The method of any of claims 1, 2, 3, 4, 7, 8, 23, 24 or 26 wherein said compressed representation of said image includes a template stream, a template reference stream, and row and column position streams, and wherein at least one of said streams is further compressed.

36. The method of any of claims 1, 2, 3, 4, 7, 8, 23, 24 or 26 further comprising splitting templates comprising a region smaller than a predetermined pattern of pixels into more than one template.

37. The method of claim 36 further comprising comparing templates formed by splits to other templates and merging templates formed by splits which match another template with that template.

38. The method of any of claims 1, 2, 3, 4, 7, 8, 25, 24 or 26 further comprising eliminating symbols smaller than predetermined patterns of pixels.

39. The method of any of claims 1, 2, 3, 4, 7, 8, 23, 24 or 26 wherein the indications of locations for symbols in said image are represented by the difference between the actual offset between a given symbol and a preceding symbol and a standard offset for the symbol pair defined by said given symbol and preceding symbol.

40. The method of claim 39 wherein said standard offset is the offset last seen for the symbol pair.

41. The method of claim 39 wherein said standard offset is the most frequently seen offset for the symbol pair.

42. The method of claim 39 wherein the difference between the standard offset and the actual offset is determined at a lower resolution than the resolution of the first representation of said image.

43. The method of any of claims 1, 2, 3, 4, 7, 8, 23, 24 or 26 further comprising determining approximate reading order of said symbols and generating said compressed representation of said image according to said reading order.

44. The method of claim 43 wherein said reading order is determined by locating symbols on a single line and sorting the symbols.

45. The method of claim 44 wherein the symbols on a line are determined by using a beam to search along the line, the size of said beam varying according to the size of one or more adjacent symbols.

46. The method of claim 45 wherein bounds on the size of the beam are imposed.

47. The method of any of claims 1, 2, 3, 4, 7, 8, 23, 24 or 26 applied to an image transmission system.

48. The method of any of claims 1, 2, 3, 4, 7, 8, 23, 24 or 26 applied to a facsimile transmission system.

49. The method of any of claims 1, 2, 3, 4, 7, 8, 23, 24 or 26 applied to an image enhancement system.

50. The method of any of claims 1, 2, 3, 4, 7, 8, 23, 24 or 26 applied to an image storage system.

51. Apparatus for compressing images comprising:

input means for accepting a first representation of an image, and
processing means for
a) precompressing said first representation of said image to generate a precompressed representation of said image,
b) identifying symbols in said precompressed representation of said image,
c) comparing a plurality of identified symbols to each of at least one template from a library of templates to match identified symbols to templates, and
d) generating a compressed representation of said image including a representation of templates, and an indication of a location and a template corresponding to symbols in said image.

52. Apparatus for compressing images comprising:

input means for accepting a, first representation of an image, and
processing means for
a) identifying symbols in said first representation of said image,
b) comparing a plurality of identified symbols to each of at least one template from a library of templates to match identified symbols to templates, wherein said library is augmented during image compression by storing in said library symbols for which no matching template is found as new templates, and wherein each template is defined by representations determined by a plurality of the symbols which match, wherein each template is defined by a unique spatial distribution of pixels, said distribution determined by the distributions of pixels of a plurality of the symbols which match said template, and
c) generating a compressed representation of said image including a representation of templates, and an indication of a location and a template corresponding to symbols in said image.

53. Apparatus for compressing images comprising:

input means for accepting a first representation of an image, and
processing means for
a) identifying symbols in said first presentation of said image,
b) comparing a plurality of identified symbols to each of at least one template from a library of templates to match identified symbols to templates, said comparing step including identifying error locations, performing at least one test on said error locations and on other global features of the symbol and the template, and declaring a match between a symbol and a template only if all of the tests in at least one of a set of predetermined groups of tests are passed, and
c) generating a compressed representation of said image including a representation of templates, and an indication of a location and a template corresponding to symbols in said image.

54. Apparatus for compressing images comprising:

input means for accepting a first representation of an image, and
processing means for
a) identifying symbols in said first representation of said image,
b) comparing a plurality of identified symbols to each of at least one template from a library of templates to match identified symbols to templates, wherein each said template is defined by a representation based on a spatial distribution of pixels of a first type, and
c) generating a compressed representation of said image including a representation of templates, and an indication of a location and a template corresponding to symbols in said image, wherein the representation of a plurality of said templates is a representation of the boundary of the spatial distribution of pixels of the first type for the templates.

55. Apparatus for compressing images comprising:

input means for accepting a first representation of an image, and processing means for
a) identifying symbols in said first representation of said image,
b) comparing a plurality of identified symbols to each of at least one template from a library of templates to match identified symbols to templates, and
c) generating a compressed representation of said image including a representation of templates, and an indication of a location and a template corresponding to symbols in said image, wherein the representations of a plurality of said templates comprise a reference to a frame template for defining an outer boundary of the template and a list of hole templates with associated positions within said frame template for defining any inner boundaries of said template.

56. Apparatus for compressing images comprising:

input means for accepting a first representation of an image, and processing means for
a) identifying symbols in said first representation of said image,
b) comparing a plurality of identified symbols to each of at least one template from a library of templates to match identified symbols to templates, wherein the templates are indexed in said library according to template features, and wherein said step of comparing proceeds according to the index, whereby those templates more likely, based on features, to match a symbol are compared to the symbol before templates less likely to match, and those templates whose indexed features would preclude a match are not compared, and
c) generating a compressed representation of said image including a representation of templates, and an indication of a location and a template corresponding to symbols in said image.

57. The apparatus as in any of claims 51-56 further comprising output means for providing said compressed representation of said image.

58. The apparatus as in any of claims 51-56 wherein said input means is a scanner.

59. The apparatus of claim 55 wherein said output means is a modem.

60. A method for compressing images comprising:

precompressing a first representation of an image, said first representation based on pixels of a first type and a second type, to generate a precompressed representation of said image,
identifying symbols in said precompressed representation of said image,
comparing a plurality of identified symbols to each of at least one template from a library of templates to match identified symbols to templates, and
generating a compressed representation of said image including an indication of a location and a template for symbols in said image.

61. The method of claim 60 wherein said first representation of an image is precompressed by run-length encoding.

62. The method of claim 61 wherein said first representation is based on rows and columns of pixels, and symbols are identified by associating runs of said first type of pixel in adjacent rows of said precompressed representation which have at least one pixel of said first type in the same column or in the same or adjacent columns.

63. A method for compressing images comprising:

identifying symbols in a first representation of an image,
comparing a plurality of identified symbols to each of at least one template in a library of templates to match identified symbols to templates, said comparing step including identifying error locations, performing at least one test on said error locations and on other global features of the symbol and the template, and declaring a match between a symbol and a template only if all of the tests in at least one of a set of predetermined groups of tests are passed, and
generating a compressed representation of said image including an indication of a location and a template for symbols in said image.

64. The method of claim 63 wherein said first representation is based on rows and columns of pixels of a first type and a second type, said comparing step including identifying error pixel locations which have a pixel of said first type in only said symbol or said template, but not both, and performing at least one test on said error pixel locations and other global features of the symbol and the template, a match between a symbol and a template being declared only if all of the tests in at least one of a set of predetermined groups of tests are passed.

65. The method of claim 64 wherein said error locations are run-length encoded.

66. The method of claim 64 wherein one of said at least one test is passed if the distance between each error pixel location and the nearest pixel of the first type in the template or symbol having a pixel of the second type at the error pixel location is less than a predetermined value.

67. The method of claim 64 wherein one of said at least one test is passed if the distance between each error pixel location and the nearest pixel of the second type in the template or symbol having a pixel of the first type at the error pixel location is less than a predetermined value.

68. The method of claim 64 wherein one of said at least one test depends on the sizes, shapes, and orientations of contiguous groups of error pixels in some error map.

69. The method of claim 68 wherein one of said at least one test is passed if all contiguous groups of error pixel locations are smaller than predetermined patterns of pixels.

70. The method of claim 68 wherein one of said at least one test is passed if inferred shifts of the symbol relative to the template are consistent.

71. The method of claim 70 wherein shifts are inferred from the sizes, shapes, and orientations of contiguous groups of error pixel locations and their relation to adjacent pixels.

72. The method of claim 71 wherein shifts are inferred from triangles of pixels in the template and symbol error maps such that the inferred shift is towards or away from the fourth pixel in the square bounding the triangle depending on whether said fourth pixel has the same or different parity, respectively, as the triangle pixels in the template.

73. The method of claim 64 wherein one of said at least one test is passed if the difference in heights between a template and a symbol is less than a predetermined value.

74. The method of claim 64 wherein one of said at least one test is passed if the difference in widths between a template and a symbol is less than a predetermined value.

75. The method of claim 64 wherein one of said at least one test is passed if the ratio of the number of pixels of the first type in the symbol and the number of pixels of the first type in the template is within a predetermined range.

76. The method of claim 64 wherein one of said at least one test is passed if the ratio of the number of error pixel locations to the number of pixels of the first type in said template or said symbol, or the minimum or maximum of the two, is less than a predetermined value.

77. The method of claim 64 wherein one of said at least one test is passed if the ratio of the number of error pixel locations to the number of pixels of the first type adjacent to a pixel of said second type in said template or said symbol, or the minimum or maximum of the two, is less than a predetermined value.

78. The method of claims 63 or 64 wherein at least one of said at least one test depends on symbol size.

79. A method for compressing images comprising:

identifying symbols in a first representation of an image,
comparing a plurality of identified symbols to each of at least one template in a library of templates to match identified symbols to templates, wherein the templates are indexed in said library according to template features, and wherein said step of comparing proceeds according to the index, whereby those templates more likely, based on features, to match a symbol are compared to the symbol before templates less likely to match, and those templates whose indexed features indicate that the likelihood of a match falls below a predetermined threshold are not compared, and
generating a compressed representation of said image including an indication of a location and a template for symbols in said image.

80. A method for compressing images comprising:

identifying symbols in a first representation of an image, said first representation based on rows and columns of pixels of a first type and a second type,
comparing a plurality of identified symbols to each of at least one template in a library of templates to match identified symbols to templates, said comparing step including identifying error pixel locations which have a pixel of said first type in only said symbol or said template, but not both, and performing at least one test on said error pixel locations, wherein one of said at least one test is passed if the distance between each error pixel location and the nearest pixel of the first type in the template or symbol having a pixel of the second type at the error pixel location is less than a predetermined value, and
generating a compressed representation of said image including a representation of templates, and an indication of a location and a template for symbols in said image.

81. A method for compressing images comprising:

identifying symbols in a first representation of an image, said first representation based on rows and columns of pixels of a first type and a second type,
comparing a plurality of identified symbols to each of at least one template in a library of templates to match identified symbols to templates, said comparing step including identifying error pixel locations which have a pixel of said first type in only said symbol or said template, but not both, and performing at least one test on said error pixel locations, wherein one of said at least one test is passed if the distance between each error pixel location and the nearest pixel of the second type in the template or symbol having a pixel of the first type at the error pixel location is less than a predetermined value, and
generating a compressed representation of said image including a representation of templates, and an indication of a location and a template for symbols in said image.

82. A method for compressing images comprising:

identifying symbols in a first representation of an image, said first representation based on rows and columns of pixels of a first type and a second type,
comparing a plurality of identified symbols to each of at least one template in a library of templates to match identified symbols to templates, said comparing step including identifying error pixel locations which have a pixel of said first type in only said symbol or said template, but not both, and performing at least one test on said error pixel locations, wherein one of said at least one test depends on the sizes, shapes and orientations of contiguous groups of error pixel locations in some error map other than an error map consisting of all error pixel locations, and
generating a compressed representation of said image including a representation of templates, and an indication of a location and a template for symbols in said image.

83. The method of claim 82 wherein one of said at least one test is passed if all of said contiguous groups of error pixel locations are smaller than predetermined patterns of pixels.

84. A method for compressing images comprising:

identifying symbols in a first representation of an image, said first representation based on rows and columns of pixels of a first type and a second type,
comparing a plurality of identified symbols to each of at least one template in a library of templates to match identified symbols to templates, said comparing step including identifying error pixel locations which have a pixel of said first type in only said symbol or said template, but not both, and performing at least one test on said error pixel locations, wherein one of said at least one test is passed if inferred shifts of the symbol relative to the template are consistent, and
generating a compressed representation of said image including a representation of templates, and an indication of a location and a template for symbols in said image.

85. The method of claim 84 wherein shifts are inferred from the sizes, shapes, and orientations of contiguous groups of error pixel locations and their relation to adjacent pixels.

86. The method of claim 85 wherein shifts are inferred from triangles of pixels in the template and symbol error maps such that the inferred shift is towards or away from the fourth pixel in the square bounding the triangle depending on whether said fourth pixel has the same or different parity, respectively, as the triangle pixels in the template.

87. The method of claim 85 wherein shifts are inferred from single error pixels such that the inferred shift is towards or away from some pixel adjacent to said single error pixel depending on whether said adjacent pixel has the same or different parity, respectively, as said error pixel in the template.

88. A method for compressing images comprising:

identifying symbols in a first representation of an image, said first representation based on rows and columns of pixels of a first type and a second type,
comparing a plurality of identified symbols to each of at least one template in a library of templates to match identified symbols to templates, said comparing step including identifying error pixel locations which have a pixel of said first type in only said symbol or said template, but not both, and performing at least one test on said error pixel locations, wherein one of said at least one test is passed if the difference in width between the template and the symbol is less than a predetermined value, and
generating a compressed representation of said image including a representation of templates, and an indication of a location and a template for symbols in said image.

89. A method for compressing images comprising:

identifying symbols in a first representation of an image, said first representation based on rows and columns of pixels of a first type and a second type,
comparing a plurality of identified symbols to each of at least one template in a library of templates to match identified symbols to templates, said comparing step including identifying error pixel locations which have a pixel of said first type in only said symbol or said template, but not both, and performing at least one test on said error pixel locations, wherein one of said at least one test is passed if the difference in height between the template and the symbol is less than a predetermined value, and
generating a compressed representation of said image including a representation of templates, and an indication of a location and a template for symbols in said image.

90. A method for compressing images comprising:

identifying symbols in a first representation of an image, said first representation based on rows and columns of pixels of a first type and a second type,
comparing a plurality of identified symbols to each of at least one template in a library of templates to match identified symbols to templates, said comparing step including identifying error pixel locations which have a pixel of said first type in only said symbol or said template but not both, and performing at least one test on said error pixel locations, wherein one of said at least one test is passed if the ratio of the number of pixels of the first type in the symbol and the number of pixels of the first type in the template is within a predetermined range, and
generating a compressed representation of said image including a representation of templates, and an indication of a location and a template for symbols in said image.

91. A method for compressing images comprising:

identifying symbols in a first representation of an image, said first representation based on rows and columns of pixels of a first type and a second type,
comparing a plurality of identified symbols to each of at least one template in a library of templates to match identified symbols to templates, said comparing step including identifying error pixel locations which have a pixel of said first type in only said symbol or said template, but not both, and performing at least one test on said error pixel locations, wherein one of said at least one test is passed if the ratio of the number of error pixel locations to the number of pixels of the first type in said template or said symbol, or the minimum or maximum of the two, is less than a predetermined value, and
generating a compressed representation of said image including a representation of templates, and an indication of a location and a template for symbols in said image.

92. A method for compressing images comprising:

identifying symbols in a first representation of an image, said first representation based on rows and columns of pixels of a first type and a second type,
comparing a plurality of identified symbols to each of at least one template in a library of templates to match identified symbols to templates, said comparing step including identifying error pixel locations which have a pixel of said first type in only said symbol or said template but not both, and performing at least one test on said error pixel locations, wherein one of said at least one test is passed if the ratio of the number of error pixel locations to the number of pixels of the first type adjacent to a pixel of said second type in said template or said symbol, or the minimum or maximum of the two, is less than a predetermined value, and
generating a compressed representation of said image including a representation of templates, and an indication of a location and a template for symbols in said image.

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