Method and apparatus for reading machine-readable symbols having surface or optical distortions

• US 5,854,478 A
• Filed: 10/11/1996
• Issued: 12/29/1998
• Est. Priority Date: 10/11/1996
• Status: Expired due to Fees

• Current Assignee: Intermec IP Corporation (Honeywell International Inc.)
• Original Assignee: Intermec IP Corporation (Honeywell International Inc.)
• Inventors: Vartanian, Lisa M., Liu, Lingnan, Shimizu, Mark Y.
• Primary Examiner(s): Gross, Anita Pellman
• Assistant Examiner(s): Dunn, Drew A.
• Application Number:
  US08/731,274
• Time in Patent Office: 809 Days
• Field of Search: 235/462, 235/463
• US Class Current: 235/462.27
• 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 7/1452 detecting bar code edges

Abstract

A method and apparatus for reading a distorted image of data collection symbol within a reader image generated and stored by a two-dimensional symbology reader begins by first locating a starting point in the distorted symbol image within the stored reader image. The method identifies edge contours of some or all of the bars and spaces in the symbol. The method then identifies one or more points within each of the identified edges. Thereafter, the method defines one or more sampling paths or lines that extend through the symbol, and through the points such that each line is constructed in a "connect-the-dot" fashion. The bars and spaces can then be sampled based on one or more of the defined lines, and the information in the symbol decoded from the sampled bars and spaces.

Claims

1. A method of reading a distorted image of a data collection symbol stored within an image generated and stored by a symbol reader, the symbol in its undistorted form having an array of substantially parallel rectangular bars and spaces between the bars that encode data, the bars and spaces being arranged along at least one axis, the method comprising the steps of:

locating a bar or space of the distorted image of the data collection symbol;

identifying an edge of the bar or space;

repeating the steps of locating a bar or space and identifying an edge until at least some of the edges of the bars or spaces in the data collection symbol have been identified;

selecting at least one point on each identified edge;

defining at least one path extending between each corresponding point of each edge;

sampling the bars and spaces along the at least one path; and

decoding the data in the data collection symbol based on the sampled bars and spaces along the at least one path.

2. The method of claim 1 wherein the step of selecting at least one point on each identified edge includes identifying at least first, second and third points on each edge,

wherein the step of defining at least one path extending between each corresponding point of each edge includes defining a first path extending through each of the first points on each edge, defining a second path extending through each of the second points on each edge, and defining a third path extending through each of the third points on each edge, and

wherein the step of decoding the data in the data collection symbol based on the sampled bars and spaces along the at least one path includes decoding the data in the data collection symbol based on a portion of the first path and a portion of the third path.

3. The method of claim 1 wherein the data collection symbol includes first and second rows of bars and spaces arranged along two parallel axes, wherein the step of selecting at least one point on each identified edge includes selecting at least one point on each identified edge of each bar in each row, and wherein the step of defining at least one path extending between each corresponding point of each edge defines at least first and second paths through the first and second rows.

4. The method of claim 1 wherein the step of locating a bar or space of the image of the data collection symbol includes identifying a starting point within the stored image.

5. The method of claim 1 wherein the step of selecting at least one point on each identified edge includes identifying at least first, second and third points on each edge, and wherein the step of defining at least one path extending between each corresponding point of each edge includes defining a first path extending through each of the first points on each edge, defining a second path extending through each of the second points on each edge, and defining a third path extending through each of the third points on each edge.

6. The method of claim 1, further comprising the steps of:

attempting to decode the data collection symbol based on the sampled bars and spaces along the at least one path;

selecting a plurality of points on each edge greater than a number of points previously selected under the step of selecting at least one point on each identified edge;

defining a plurality of paths extending between the plurality of points on each edge;

sampling the bars and spaces along the plurality of paths; and

decoding the data in the data collection symbol based on the sampled bars and spaces along the plurality of paths.

7. The method of claim 1 wherein the data collection symbol includes a defined pattern, and wherein the step of locating a bar or space of the distorted image of the data collection symbol includes the step of locating the defined pattern of the data collection symbol.

8. The method of claim 1 wherein the step of repeating the steps of locating a bar or space include identifying an edge until all edges of the bars or spaces in the data collection symbol have been identified.

9. The method of claim 1 wherein the step of repeating the steps of locating a bar or space includes the steps of:

moving a fixed distance in a direction substantially perpendicular to the identified edge to a new point;

locating an edge of a bar or space in a neighborhood proximate to the new point; and

repeating the steps of moving and locating an edge until edges of several bars or spaces in the data collection symbol have been identified.

10. The method of claim 1 wherein the step of identifying an edge of the bar or space includes the steps of:

identifying a starting edge point on each identified edge and sequentially identifying connecting points along the identified edge until opposite endpoints of each identified edge are located; and

determining a distance between the opposite endpoints.

11. The method of claim 1 wherein the step of identifying an edge of the bar or space includes the steps of:

identifying a starting point within each bar or space and sequentially identifying connecting points within the bar or space until opposite endpoints of each bar or space are located; and

determining a length of each bar or space based on a curve connecting the opposite endpoints.

12. The method of claim 1 wherein the step of selecting at least one point on each identified edge includes identifying at least first and second points on each edge,

wherein the step of defining at least one path extending between each corresponding point of each edge includes the steps of:

defining a first path extending through each of the corresponding first points on each identified edge; and

defining a second path extending through each of the corresponding second points on each identified edge, and

wherein the step of decoding the data in the data collection symbol based on the sampled bars and spaces along the at least one path includes the steps of;

decoding the data in the data collection symbol based on a portion of the first path, the portion of the first path extending from a first end of the symbol to a first inner point;

moving along an inner edge of a bar or space in the symbol from the first inner point to a second inner point; and

decoding the data in the data collection symbol based on a portion of the second path, the portion of the second path extending from the second inner point in the symbol to a second end of the symbol.

13. A method of sampling information of a distorted image of machine-readable visual indicia within a reader image generated and stored by an indicia reader, the machine-readable visual indicia in its undistorted form having a plurality of information bearing indicia extending and decodable along at least one axis, and the plurality of information bearing indicia having a plurality of edges between the information bearing indicia and areas formed therebetween, the method comprising the steps of:

identifying a starting point proximate to an information bearing indicia of the distorted image of the machine-readable visual indicia;

identifying at least some edges of the information bearing indicia based on the starting point;

selecting at least one point on each identified edge;

defining at least one path extending between each corresponding point of each edge; and

sampling the information bearing indicia along the at least one path.

14. The method of claim 13 wherein the step of selecting at least one point on each identified edge includes identifying at least first, second and third points on each edge,

wherein the step of defining at least one path extending between each corresponding point of each edge includes defining a first path extending through each of the first points on each edge, defining a second path extending through each of the second points on each edge, and defining a third path extending through each of the third points on each edge, and

wherein the step of reading the machine-readable visual indicia based on the sampled information bearing indicia along the at least one path includes reading the machine-readable visual indicia based on a portion of the first path and a portion of the third path.

15. The method of claim 13 wherein the machine-readable visual indicia includes first and second rows of information bearing indicia arranged along two parallel axes, wherein the step of selecting at least one point on each identified edge includes selecting at least one point on each identified edge of each information bearing indicia in each row, and wherein the step of defining at least one path extending between each corresponding point of each edge defines at least first and second paths through the first and second rows.

16. The method of claim 13 wherein the step of identifying a starting point includes locating an information bearing indicia of the image of the machine-readable visual indicia.

17. The method of claim 13 wherein the step of selecting at least one point on each identified edge includes identifying at least first, second and third points on each edge, and wherein the step of defining at least one path extending between each corresponding point of each edge includes defining a first path extending through each of the first points on each edge, defining a second path extending through each of the second points on each edge, and defining a third path extending through each of the third points on each edge.

18. The method of claim 13, further comprising the steps of:

attempting to read the machine-readable visual indicia based on the sampled information bearing indicia along the at least one path;

selecting a plurality of points on each edge greater than a number of points previously selected under the step of selecting at least one point on each identified edge;

defining a plurality of paths extending between the plurality of points on each edge;

sampling the information bearing indicia along the plurality of paths; and

reading the machine-readable visual indicia based on the sampled information bearing indicia along the plurality of paths.

19. The method of claim 13 wherein the machine-readable visual indicia includes a defined pattern, and wherein the step of identifying a starting point includes the step of locating the defined pattern of the machine-readable visual indicia.

20. The method of claim 13 wherein the machine-readable visual indicia is a bar code symbol, and wherein the step of reading the machine-readable visual indicia includes decoding the bar code symbol.

21. The method of claim 13, further comprising the step of reading the machine-readable visual indicia based on the sampled information bearing indicia along the at least one path.

22. The method of claim 13 wherein the step of identifying at least some edges of the information bearing indicia includes identifying all edges of the information bearing indicia.

23. The method of claim 13 wherein the step of identifying at least some edges of the information bearing indicia includes the steps of:

moving a selected distance in a direction along the at least one axis to a new point;

locating an edge of one of the information bearing indicia in a neighborhood proximate to the new point; and

repeating the steps of moving and locating an edge until edges of several information bearing indicia have been identified.

24. The method of claim 13 wherein the step of selecting at least one point on each identified edge includes the steps of:

identifying endpoints of at least some of the identified edges; and

determining a distance between the endpoints.

25. The method of claim 13 wherein the step of selecting at least one point on each identified edge includes identifying at least first and second points on each edge,

wherein the step of defining at least one path extending between each corresponding point of each edge includes the steps of:

determining a first path extending through each of the corresponding first points on each identified edge; and

defining a second path extending through each of the corresponding second points on each identified edge, and

wherein the step of sampling the information bearing indicia along the at least one path includes the steps of;

sampling the information bearing indicia based on a portion of the first path, the portion of the first path extending from a first end of the machine-readable visual indicia to a first inner point;

moving along an inner edge of one of the visual indicia from the first inner point to a second inner point proximate to the inner edge; and

sampling the information bearing indicia based on a portion of the second path, the portion of the second path extending from the second inner point to another point.

26. The method of claim 14 wherein the step of selecting at least one point on each identified edge includes the steps of:

identifying endpoints of at least some of the identified edges; and

determining a length of the at least some of the identified edges between the endpoints.

28. The method of claim 26 wherein the step of defining a plurality of planar areas includes the step of determining an area of each bar or space in the data collection symbol based on the plurality of defined planar areas.

29. The method of claim 26 wherein the step of defining a plurality of segments includes defining a plurality of sampling paths, each sampling path including a plurality of linked segments extending along the at least one dimension.

30. The method of claim 26 wherein the step of repeating the steps of locating a bar or space includes identifying an edge until all edges of the bars or spaces in the data collection symbol have been identified.

27. A method of analyzing a distorted image of a data collection symbol stored within a two-dimensional image generated and stored by a symbol reader, the symbol in its undistorted form having an array of substantially parallel rectangular bars and spaces between the bars that encode data, the bars and spaces being arranged along at least one dimension, the symbol being distorted in three-dimensions, the method comprising the steps of:

locating a bar or space of the distorted two-dimensional image of the data collection symbol;

identifying an edge of the bar or space;

repeating the steps of locating a bar or space and identifying an edge until at least some of the edges of the bars and spaces in the data collection symbol have been identified;

selecting a plurality of points on each identified edge;

defining a plurality of segments extending between each corresponding point of each edge; and

defining a plurality of planar areas for bar or space, each planar area defined by a pair of the plurality of segments and portions of adjacent identified edges.

31. An apparatus for decoding a machine-readable symbol representing encoded information, the symbol including an array of shapes and spaces between each shape that encode data, the shapes and spaces being arranged along at least one axis, the apparatus comprising:

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

a storage device for storing the output signal of the distorted image of the shapes and spaces; and

a processor for processing a stored signal and producing a signal indicative of the information encoded in the symbol, wherein a processor (a) identifies edges of the shapes in the symbol, (b) selects at least one point on each edge, (c) defines at least one path extending between each corresponding point of each edge, (d) samples the bars and spaces along the at least one path; and

(e) decodes the data in the symbol based on the sampled bars and spaces along the at least one path.

32. A method of sampling information of a distorted image of machine-readable indicia within a reader image generated and stored by an indicia reader, the machine-readable visual indicia in its undistorted form having a plurality of information bearing indicia extending and decodable along at least one axis, the method comprising the steps of:

identifying a starting point proximate to an information bearing indicia of the distorted image of the machine-readable visual indicia;

identifying a curve extending through at least some of the information bearing indicia based on the starting point;

selecting at least one point on each identified curve;

defining at least one path extending between each corresponding point of each identified curve; and

sampling the information bearing indicia along the at least one path.

33. The method of claim 32 wherein the step of selecting at least one point on each identified curve includes the steps of:

identifying a start point within an information bearing indicia and sequentially identifying connecting points along the identified curve until opposite endpoints of the identified curve are located; and

determining a length of the identified curve extending between the opposite endpoints.

34. The method of claim 33 wherein the step of selecting at least one point on each identified curve includes the steps of:

identifying a start point within an information bearing indicia and sequentially identifying connecting points along the curve until opposite endpoints of the identified curve are located; and

determining a distance between the opposite endpoints.