Decoding distorted symbols

• US 7,878,402 B2
• Filed: 12/20/2005
• Issued: 02/01/2011
• Est. Priority Date: 12/20/2005
• Status: Expired due to Fees

• Current Assignee: Cognex Technology & Investment Corporation (Cognex Corporation)
• Original Assignee: Cognex Technology & Investment Corporation (Cognex Corporation)
• Inventors: Ye, Xiangyun, Nadabar, Sateesha
• Primary Examiner(s): Lee; Michael G
• Assistant Examiner(s): Haupt; Kristy A
• Application Number:
  US11/312,703
• Publication Number:
  US 20090090781A1
• Time in Patent Office: 1,869 Days
• Field of Search: 235/462.09, 235/462.1, 382/199, 382/149, 382/218
• US Class Current: 235/462.1
• 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: G06T 3/00 Geometric image transformations in the plane of the image

Abstract

A method is provided for reading distorted optical symbols using known locating and decoding methods, without requiring a separate and elaborate camera calibration procedure, without excessive computational complexity, and without compromised burst noise handling. The invention exploits a distortion-tolerant method for locating and decoding 2D code symbols to provide a correspondence between a set of points in an acquired image and a set of points in the symbol. A coordinate transformation is then constructed using the correspondence, and run-time images are corrected using the coordinate transformation. Each corrected run-time image provides a distortion-free representation of a symbol that can be read by traditional code readers that normally cannot read distorted symbols. The method can handle both optical distortion and printing distortion. The method is applicable to “portable” readers when an incident angle with the surface is maintained, the reader being disposed at any distance from the surface.

Claims

1. A method for decoding distorted symbols, the method comprising:

at train-time;

acquiring a training image of a two-dimensional (2D) code symbol disposed on a train-time surface using a camera with an optical axis having an incident angle with respect to the train-time surface;

running a 2D code symbol reader that can detect and tolerate distortion so as to provide a correspondence between at least two 2D coordinates of points within the training image and at least two 2D coordinates of points within the 2D code symbol;

using the correspondence to construct a coordinate transformation;

at run-time;

disposing a symbol on a run-time surface that is substantially parallel to the train-time surface;

acquiring a run-time image of a symbol disposed on the run-time surface using a camera with an optical axis having substantially the incident angle with respect to the run-time surface;

correcting distortion of the run-time image using the coordinate transformation to provide a corrected image; and

running a run-time symbol reader on the corrected image.

2. The method of claim 1, wherein the run-time symbol reader can read damaged symbols.

3. The method of claim 1, wherein the 2D code symbol is a matrix code symbol.

4. The method of claim 3, wherein the run-time symbol is a matrix code symbol having a different number of modules than included in the matrix code symbol in the training image.

5. The method of claim 3, wherein the run-time symbol is a matrix code symbol having different information content from the information content of the matrix code symbol in the training image.

6. The method of claim 1, wherein the 2D code symbol is one of a Data Matrix symbol, a QR Code symbol, a MaxiCode symbol, a Code One symbol, and an Aztec Code symbol.

7. The method of claim 1, wherein the 2D code symbol can be read by a reader that provides at least two feature points having well-defined correspondence with expected locations in the symbol.

8. The method of claim 1, wherein the coordinate transformation is at least one of a geometric transformation and a non-linear transformation.

9. The method of claim 1, wherein running a run-time symbol reader on the corrected image includes:

providing at least two 2D coordinates of points within the run-time symbol in the corrected image,

and the method further comprises;

applying an inverse of the coordinate transformation to the at least two 2D coordinates of points to provide mapped versions of the at least two 2D coordinates of points.

10. The method of claim 9, wherein the mapped versions of the at least two 2D coordinates of points are displayed within the run-time image so as to define an outline of the run-time symbol.

11. The method of claim 9, wherein the mapped versions of the at least two 2D coordinates of points are analyzed.

12. The method of claim 1, after running a symbol reader on the corrected image, further comprising:

computing quality metrics of the symbol within the corrected image.

13. The method of claim 1, wherein the surface includes a non-planar surface.

14. The method of claim 1, wherein the coordinate transformation includes at least one of an affine transformation portion, a perspective transformation portion, and a high-order non-linear transformation portion.

15. The method of claim 1, wherein the run-time symbol is one of a two-dimensional matrix code symbol, a stacked code, a linear barcode, and a text block.

16. The method of claim 1, wherein the run-time symbol is a matrix code symbol of different scale than the matrix code symbol in the training image.

17. The method of claim 1, wherein the run-time symbol is not a matrix code symbol.

18. The method of claim 1, wherein running the 2D code reader includes:

establishing correspondence based on multiple feature points as supported by the 2D code reader.

19. The method of claim 1, wherein running the 2D code reader includes:

establishing correspondence based on corner points of a polygonal 2D code symbol.

20. The method of claim 1, wherein running the 2D code reader includes:

establishing correspondence based on four corner points of a quadrilateral 2D code symbol.

21. The method of claim 1, where in the coordinate transformation is a perspective coordinate transformation constructed using a correspondence established based on four corner points of a quadrilateral 2D code symbol.

22. The method of claim 1, wherein the camera is a projective camera.

23. The method of claim 1, wherein the surface is not normal with respect to an optical axis of an image sensor of the camera.

24. The method of claim 1, further comprising:

at train-time;

mounting a camera at a three-dimensional position fixed relative to a train time surface upon which run-time symbols will be presented.

25. The method of claim 1, wherein the run-time image is one of the train-time image, a copy of the train-time image, a derivative of the train-time image, a portion of the train-time image, and an equivalent of the train-time image.

26. The method of claim 1, wherein the corrected image corresponds to a portion of the run-time image.

27. The method of claim 1, wherein the corrected image corresponds to a full run-time image.

28. A method for decoding distorted symbols, the method comprising:

acquiring a train-time image of a 2D code symbol, the 2D code symbol showing distortion in the train-time image;

running a 2D code symbol reader on the training image, the 2D code symbol reader being able to detect and tolerate distortion so as to provide a correspondence between at least two 2D coordinates of points within the train-time image and two 2D coordinates of points within the 2D code symbol;

using the correspondence to construct a coordinate transformation;

acquiring a run-time image of a symbol under the same conditions as the acquiring of the train-time image of the 2D code symbol;

correcting distortion of the run-time image using the coordinate transformation to provide a corrected image; and

running a run-time symbol reader on the corrected image.

29. The method of claim 28, wherein the run-time symbol shows the distortion of the train-time symbol;

and

the distortion includes at least one of an optical distortion and a printing distortion.

30. A method for decoding distorted symbols, the method comprising:

acquiring a run-time image of a symbol, the symbol showing distortion in the run-time image;

obtaining a coordinate transformation that describes the distortion shown in the image of the symbol;

correcting distortion shown in the run-time image using the coordinate transformation so as to provide a corrected image;

running a run-time symbol reader on the corrected image; and

wherein the coordinate transformation is constructed using a correspondence between at least two 2D coordinates of points within a train-time image and two 2D coordinates of points within a 2D code symbol, the correspondence being provided by a symbol reader that can detect and tolerate distortion of the 2D code symbol.

31. The method of claim 30, wherein the distortion includes at least one of an optical distortion and a printing distortion.

32. A method for decoding distorted symbols, the method comprising:

at train-time;

acquiring a training image of a two-dimensional (2D) code symbol disposed on a train-time surface using a camera with an optical axis having an incident angle with respect to the train-time surface;

running a 2D code symbol reader that can detect and tolerate distortion so as to provide a correspondence between at least two 2D coordinates of points within the training image and at least two 2D coordinates of points within the 2D code symbol;

using the correspondence to construct a coordinate transformation;

at run-time;

disposing a symbol on a run-time surface that is substantially parallel to the train-time surface;

acquiring a run-time image of a symbol disposed on the run-time surface using a camera with an optical axis having substantially the incident angle with respect to the run-time surface;

correcting distortion of the run-time image using the coordinate transformation to provide a corrected representation of the symbol; and

running a run-time symbol reader on the corrected representation of the symbol.

33. The method of claim 32, wherein the corrected representation of the symbol is a corrected image of the symbol.

34. The method of claim 32, wherein the corrected representation of the symbol is a corrected feature of the symbol.

35. A method for decoding distorted symbols, the method comprising:

acquiring a run-time image of a symbol, the symbol showing distortion in the run-time image;

obtaining a coordinate transformation that describes the distortion shown in the image of the symbol wherein the coordinate transform is determined prior to run-time;

correcting distortion shown in the run-time image using the coordinate transformation so as to provide a corrected image; and

running a run-time symbol reader on the corrected image.

36. A method for decoding distorted symbols, the method comprising:

at train-time;

acquiring a training image of a two-dimensional (2D) code symbol disposed on a train-time surface using a camera with an optical axis having an incident angle with respect to the train-time surface;

running a 2D code symbol reader that can detect and tolerate distortion so as to provide a correspondence between at least two 2D coordinates of points within the training image and at least two 2D coordinates of points within the 2D code symbol;

using the correspondence to construct a coordinate transformation;

at run- time;

disposing a symbol on a run-time surface that is generally parallel to the train-time surface;

acquiring a run-time image of a symbol disposed on the run-time surface using a camera with an optical axis having substantially the incident angle with respect to the run-time surface;

correcting distortion of the run-time image using the coordinate transformation to provide a corrected image; and

running a run-time symbol reader on the corrected image.

37. The method of claim 36, wherein the coordinate transformation is at least one of a geometric transformation and a non-linear transformation.

38. The method of claim 36, wherein running a run-time symbol reader on the corrected image includes:

providing at least two 2D coordinates of points within the run-time symbol in the corrected image,

and the method further comprises;

applying an inverse of the coordinate transformation to the at least two 2D coordinates of points to provide mapped versions of the at least two 2D coordinates of points.