Time-efficient method of analyzing imaged input data to locate two-dimensional machine-readable symbols or other linear images therein

• US 6,064,763 A
• Filed: 07/26/1996
• Issued: 05/16/2000
• Est. Priority Date: 07/26/1996
• Status: Expired due to Term

• Current Assignee: Intermec IP Corporation (Honeywell International Inc.)
• Original Assignee: Intermec IP Corporation (Honeywell International Inc.)
• Inventors: Maltsev, Pavel A.
• Primary Examiner(s): Lee, Thomas D.
• Assistant Examiner(s): Chen, Wenpeng
• Application Number:
  US08/687,659
• Time in Patent Office: 1,390 Days
• Field of Search: 382/199, 382/286, 382/287, 382/289, 382/291, 382/175, 382/177-179, 382/184, 382/101-102, 382/141-142, 382/151, 382/153, 382/311, 382/183, 382/132, 235/472, 235/462, 235/470
• US Class Current: 382/183
• CPC Class Codes: G06K 7/14 using light without selection of wavelength, e.g. sensing reflected white light G06K7/10831 - G06K7/1097 take precedence
• CPC Class Codes: G06K 7/1478 adapting the threshold for pixels in a CMOS or CCD pixel sensor for black and white recognition
• CPC Class Codes: G06K 7/1486 Setting the threshold-width for bar codes to be decoded
• CPC Class Codes: G06V 30/10 Character recognition
• CPC Class Codes: G06V 30/146 Aligning or centring of the image pick-up or image-field

Abstract

A method and apparatus locates edges of patterns in a stored image, such as edges of start/stop patterns of machine-readable symbols (e.g., PDF 417 symbols). The present invention first divides the stored image into analysis regions and samples each region using a 16-beam star pattern. The beam patterns are analyzed to detect for edges that may correspond to edges of start/stop patterns of the symbol. Coast lines, or elongated edges, of the detected edges are analyzed for parallelism and minimal length to filter out any spurious detected edges. Thereafter, the coast lines are analyzed to confirm that a start or stop pattern has been located. A second start/stop pattern is thereafter located, boundary points are determined at a periphery of the symbol, and finally the symbol is analyzed for its geometric shape to confirm that the located boundary points conform to an accepted geometry for this symbol.

Claims

1. A method of locating a machine-readable symbol representing encoded information, the symbol including a plurality of selectively spaced two-dimensional geometric shapes, the symbol having a predetermined orientation pattern of at least two elongated shapes or spaces, the method comprising:

storing an image of the symbol;

dividing the stored image into a plurality of analysis regions;

sampling at least two regions along a plurality of sampling paths in each region, wherein the plurality of sampling paths begin from a selected point in each region and end at approximately a boundary of region;

locating an edge point;

analyzing an area adjacent to the edge point to locate a first elongated edge;

locating the first elongated edge based on the sampled linear sampling paths;

determining if the located first elongated edge is an edge of one of the elongated shapes or spaces;

identifying a second elongated edge of another of the elongated shapes or spaces; and

defining a position and orientation of the image of the symbol based on the located first elongated edge and the identified second elongated edge.

2. The method of claim 1 wherein storing an image of the symbol stores an image of a PDF417 symbol and wherein the elongated shapes or spaces are first and second wide bars of start and stop patterns that define opposite ends of the symbol.

3. The method of claim 1 wherein dividing the stored image divides the stored image into at least center, top, bottom, left, and right analysis regions, and wherein the center region has an area larger than areas of each of the top, bottom, left and right regions.

4. The method of claim 1 wherein dividing the stored image divides the stored image into at least center, top, bottom, left, and right analysis regions, and wherein the sampling samples the center region before sampling the top, bottom, left and right regions.

5. The method of claim 1 wherein sampling sequentially samples the region along a plurality of approximately linear sampling paths that radially extend from approximately a center point of the region.

6. The method of claim 1 wherein sampling samples the region along a plurality of approximately linear sampling paths, wherein each of the sampling paths extend from a point in the region to an edge of the region.

7. The method of claim 1 wherein locating includes:

determining a dominant direction of the located first elongated edge based on the analyzed area; and

applying a vertical searching template for locating a position of the first elongated edge if the dominant direction is horizontal, and applying a horizontal searching template for locating a position of the first elongated edge if the dominant direction is vertical.

8. The method of claim 1, further comprising the step of decoding the information encoded in the symbol based on the located predetermined point of the symbol.

9. The method of claim 1 wherein determining if the located first elongated edge is an edge of one of the elongated shapes or spaces includes:

locating an opposite edge of one of the elongated shapes or spaces;

comparing the opposite edge to the first elongated edge; and

ignoring the first elongated edge if the first and opposite elongated edges are not approximately parallel.

10. The method of claim 1 wherein determining includes:

determining an X-dimension of the symbol;

determining a width of the one shape or space having the located first elongated edge;

comparing the determined width to an expected width based on the determined X-dimension; and

ignoring the first elongated edge if the determined width substantially differs from the expected width.

11. The method of claim 1 wherein storing an image of the symbol stores an image of a PDF417 symbol, wherein the elongated shapes or spaces are first and second wide bars of start and stop patterns that define opposite ends of the symbol, and wherein determining includes:

sampling along at least one path perpendicular to the located first elongated edge;

comparing the sampled perpendicular path to an expected path through the start or stop patterns; and

ignoring the first elongated edge if the sampled path substantially differs from the expected path.

12. The method of claim 1 wherein storing an image of the symbol stores an image of a PDF417 symbol, wherein the elongated shapes or spaces are first and second wide bars of start and stop patterns that define opposite ends of the symbol, and wherein defining includes:

identifying pairs of end points at opposite ends of the first and second elongated edges; and

defining a bounding box around the symbol based on the identified pairs of end points.

13. The method of claim 1, further comprising:

determining first and second angles of the first and second elongated edges with respect to a selected line;

comparing the first and second angles;

aborting the method if the first and second angles have a predetermined relationship to a selected value.

14. In a computer system having a processor and a data storage device, a computer implemented method of locating one or more predetermined elongated shapes in an image stored in the data storage device, the stored image possibly including additional elongated shapes, the method comprising:

dividing the stored image into a plurality of analysis regions;

sampling at least two regions along a plurality of sampling paths in each region, wherein the plurality of sampling paths begin from a selected point in each region and end at approximately a boundary of region;

locating a first elongated edge based on the sampled sampling paths;

determining if the located first elongated edge is an edge of the predetermined elongated shape;

determining a dominant direction of the located first elongated edge; and

defining the location of the predetermined elongated shape based on the located first elongated edge.

15. The method of claim 14 wherein the stored image includes an image of a machine-readable symbol, wherein the predetermined elongated shapes are first and second bars of start and stop patterns that define opposite ends of the symbol, wherein locating a first elongated edge locates a first elongated edge of the first bar, and wherein the method further includes:

identifying a second elongated edge of the second bar; and

defining a position and orientation of the image of the symbol based on the located first and second elongated edges.

16. The method of claim 14 wherein dividing the stored image divides the stored image into at least center, top, bottom, left, and right analysis regions, and wherein the center region has an area larger than areas of each of the top, bottom left and right regions.

17. The method of claim 14 wherein dividing the stored image divides the stored image into at least center, top, bottom, left, and right analysis regions, and wherein sampling samples the center region before sampling the top, bottom, left and right regions.

18. The method of claim 14 wherein sampling sequentially samples the region along a plurality of approximately linear sampling paths that radially extend from approximately a center point of the region.

19. The method of claim 14 wherein sampling samples the region along a plurality of approximately linear sampling paths, wherein each of the sampling paths extend from a point in the region to an edge of the region.

20. The method of claim 14 wherein the locating includes:

determining a dominant direction of the located first elongated edge based on the analyzed area; and

applying a vertical searching template for locating a position of the first elongated edge if the dominant direction is horizontal, and applying a horizontal searching template for locating a position of the first elongated edge if the dominant direction is vertical.

21. The method of claim 14 wherein determining includes:

locating an edge opposite to the first elongated edge;

comparing the opposite edge to the first elongated edge; and

ignoring the first elongated edge if the first and opposite elongated edges are not approximately parallel.

22. The method of claim 14 wherein the stored image includes an image of a machine-readable symbol, wherein the predetermined elongated shapes are first and second bars of start and stop patterns that define opposite ends of the symbol, and wherein determining includes:

sampling along at least one path perpendicular to the located first elongated edge;

comparing the sampled perpendicular path to an expected path through the start or stop patterns; and

ignoring the first elongated edge if the sampled path substantially differs from the expected path.

23. The method of claim 14 wherein the stored image includes an image of a machine-readable symbol, wherein the predetermined elongated shapes are first and second bars of start and stop patterns that define opposite ends of the symbol, and wherein the method further comprising:

identifying a second elongated edge of the second bar;

determining first and second angles of the first and second elongated edges with respect to a selected line;

comparing the first and second angles;

aborting the method if the first and second angles have a predetermined relationship to a selected value.

24. An apparatus for decoding a machine-readable symbol representing encoded information, the symbol including a plurality of selectively spaced two-dimensional geometric shapes, the symbol having a predetermined orientation pattern of at least two elongated shapes or spaces, the apparatus comprising:

a sensor that receives light that is reflected from the symbol and produces an output signal therefrom that resents the reflectance of the shapes and spaces comprising the symbol;

a receiver that receives the output signal and produces a digital signal representing an image of the shapes and spaces of the symbol;

a storage device for storing the digital signal;

a processor for processing the digital signal and producing a signal indicative of the information encoded in the symbol, wherein the processor (a) divides the image into a plurality of analysis regions, (b) samples at least one region along a plurality of sampling paths, (c) locates a first elongated edge based on the sampled sampling paths, (d) determines if the located first elongated edge is an edge is an edge of one of the elongated shapes or spaces, (e) identifies a second elongated edge of another of the elongated shapes or spaces, (f) defines a position of the image of the symbol based on the located first elongated edge and the identified second elongated edge, and (g) decodes the symbol and producing a signal indicative of the information encoded in the symbol based on the defined position of the symbol; and

wherein the processor divides the stored image into at least center, top, bottom, left, and right analysis regions, and wherein the center region has an area larger than areas of each of the top, bottom, left and right regions.

25. An apparatus for decoding a machine-readable symbol representing encoded information, the symbol including a pluralitv of selectively spaced two-dimensional geometric shapes, the symbol having a predetermined orientation pattern of at least two elongated shapes or spaces, the apparatus comprising:

a sensor that receives light that is reflected from the symbol and produces an output signal therefrom that represents the reflectance of the shapes and spaces comprising the symbol;

a receiver that receives the output signal and produces a digital signal representing an image of the shapes and spaces of the symbol;

a storage device for storing the digital signal;

a processor for processing the digital signal and producing a signal indicative of the information encoded in the symbol, wherein the processor (a) divides the image into a plurality of analysis regions, (b) samples at least one region along a plurality of sampling paths, (c) locates a first elongated edge based on the sampled sampling paths, (d) determines if the located first elongated edge is an edge is an edge of one of the elongated shapes or spaces, (e) identifies a second elongated edge of another of the elongated shapes or spaces, (f) defines a position of the image of the symbol based on the located first elongated edge and the identified second elongated edge, and (g) decodes the symbol and producing a signal indicative of the infornation encoded in the symbol based on the defined position of the symbol; and

wherein the processor locates the elongated edges by (a) locating an edge point, (b) analyzing an area proximate the located edge point to locate the first elongated edge, (c) determining a dominant direction of the located first elongated edge based on the analyzed area, and (d) applying a vertical searching template for locating a position of the first elongated edge if the dominant direction is horizontal, and applying a horizontal searching template for locating a position of the first elongated edge if the dominant direction is vertical.

26. In a computer system having a processor and a data storage device, a computer implemented method of analyzing an image stored in the data storage device for a predetermined shape, the method comprising the steps of:

defining a point within the stored image, wherein defining defines a point approximately in the center of the stored image; and

sampling the stored image along a plurality of approximately linear sampling paths for the predetermined shape, wherein each sampling path extends from the defined point.

27. In a computer system having a processor and a data storage device, a computer implemented method of analyzing an image stored in the data storage device for one or more predetermined shapes, the method comprising:

dividing the stored image into at least a center analysis region and surrounding analysis regions, and wherein the center region has an area larger than areas of the surrounding regions; and

sequentially sampling always the center region first, and then sampling the surrounding regions second, until the predetermined shape is located in the stored image.

28. The method of claim 27 wherein dividing the stored image includes dividing the surrounding analysis regions into at least top, bottom, left, and right analysis regions, and wherein the center analysis region has an area larger than areas of each of the top, bottom, left and right analysis regions.

29. The method of claim 27 wherein dividing the stored image divides the stored image into at least center, top, bottom, left, right and corner analysis regions, and wherein sequentially sampling samples the center analysis region first, the top, bottom, left and right analysis regions second, and the corner analysis regions third.

30. The method of claim 27 wherein dividing the stored image includes dividing the surrounding analysis regions into at least top, bottom, left, and right analysis regions, and wherein sequentially sampling samples the center analysis region first, the top and bottom regions second and the left and right analysis regions third.

31. The method of claim 27 wherein dividing the stored image divides the stored image into nine regions.

32. The method of claim 27 wherein analyzing includes:

defining a point within at least one of the regions of the stored image; and

sampling the region a plurality of approximately linear sampling paths for the predetermined shape, wherein each sampling path extends from the defined point.

33. In a computer system having a processor and a data storage device, a computer implemented method of analyzing an image stored in the data storage device for one or more predetermined shapes, the method comprising:

dividing the stored image into at least center, top, bottom, left, right, and corner analysis regions; and

analyzing always the center region first, before analyzing the top, bottom, left, and right regions second, and the corner regions third to determine the location of the predetermined shape or shapes in the stored image.

34. The method of claim 33 wherein in dividing the stored image the center region has an area larger than areas of each of the top, bottom, left, right, and corner regions.

35. The method of claim 33 wherein dividing the stored image divides the stored image into at least center, top, bottom, left, and right analysis regions, and wherein the top and bottom regions are analyzed before the left or right regions.

36. The method of claim 33 wherein dividing the stored image divides the stored image into nine regions.

37. The method of claim 33 wherein analyzing includes:

defining a point within at least one of the regions of the stored image; and

sampling the region a plurality of approximately linear sampling paths for the predetermined shape, wherein each sampling path extends from the defined point.