Geometric parameter measurement of an imaging device

US 20090161945A1
Filed: 11/21/2008
Published: 06/25/2009
Est. Priority Date: 12/21/2007
Status: Active Grant

First Claim

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1. A method of determining at least one three-dimensional (3D) geometric parameter of an imaging device, the method comprising the steps of:

(a) providing a two-dimensional (2D) target image comprising a plurality of alignment patterns;

(b) imaging said target image with an imaging device to form a captured image;

(c) comparing at least one said pattern of said captured image with a corresponding pattern of said target image; and

(d) determining from said comparison said geometric parameter of the imaging device,wherein the alignment patterns include at least one of;

(i) one or more patterns comprising a 2D scale and rotation invariant basis function $f_{1} (r, θ) = {\begin{matrix} Re ⌊ w (r, θ) r^{i α + p} e^{ k θ} ⌋, & r > r_{0} \\ q, & r \leq r_{0} \end{matrix}$ where a≠

0, k≠

0, and q≠

0;

(ii) one or more patterns comprising a 1D scale invariant basis function
f(x)=cos(β

log|x|+γ

); and

(iii) one or more patterns having a plurality of grey levels and comprising a plurality of superimposed sinusoidal patterns, said plurality of sinusoidal patterns having a plurality of predetermined discrete orientations.

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Abstract

Disclosed is a method of determining at least one three-dimensional (3D) geometric parameter of an imaging device. A two-dimensional (2D) target image is provided having a plurality of alignment patterns. The target image is imaged with an imaging device to form a captured image. At least one pattern of the captured image is compared with a corresponding pattern of the target image. From the comparison, the geometric parameter of the imaging device is then determined. The alignment patterns include at least one of (i) one or more patterns comprising a 2D scale and rotation invariant basis function, (ii) one or more patterns comprising a 1D scale invariant basis function, and (iii) one or more patterns having a plurality of grey levels and comprising a plurality of superimposed sinusoidal patterns, the plurality of sinusoidal patterns having a plurality of predetermined discrete orientations. Also disclosed is a two-dimensional test chart for use in testing an imaging device, the test chart comprising a plurality of alignment patterns, at least one of said alignment patterns including one of those patterns mentioned above.

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27 Claims

1. A method of determining at least one three-dimensional (3D) geometric parameter of an imaging device, the method comprising the steps of:
- (a) providing a two-dimensional (2D) target image comprising a plurality of alignment patterns;
  
  (b) imaging said target image with an imaging device to form a captured image;
  
  (c) comparing at least one said pattern of said captured image with a corresponding pattern of said target image; and
  
  (d) determining from said comparison said geometric parameter of the imaging device,wherein the alignment patterns include at least one of;
  
  (i) one or more patterns comprising a 2D scale and rotation invariant basis function $f_{1} (r, θ) = {\begin{matrix} Re ⌊ w (r, θ) r^{i α + p} e^{ k θ} ⌋, & r > r_{0} \\ q, & r \leq r_{0} \end{matrix}$ where a≠
  
  0, k≠
  
  0, and q≠
  
  0;
  
  (ii) one or more patterns comprising a 1D scale invariant basis function
  f(x)=cos(β
  
  log|x|+γ
  
  ); and
  
  (iii) one or more patterns having a plurality of grey levels and comprising a plurality of superimposed sinusoidal patterns, said plurality of sinusoidal patterns having a plurality of predetermined discrete orientations.
- View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24)
- - 2. A method according to claim 1, where the said alignment patterns are represented as binary images using a half-toning algorithm.
  - 3. A method according to claim 1, where the said geometric parameter is a parameter describing a perspective transformation from said target image to said captured image.
  - 4. A method according to claim 1, where the said geometric parameter is a parameter describing a rotation of said target image from a reference position.
  - 5. A method according to claim 1, where the said geometric parameter is a parameter describing a translation of said target image from a reference position.
  - 6. A method according to claim 1, where the said geometric parameter is a parameter describing a scaling of said target image from a reference size.
  - 7. A method according to claim 1, where the said geometric parameter is a parameter describing a geometric lens distortion transformation from said target image to said captured image.
  - 8. A method according to claim 1, where the said geometric parameter is the focal length of the lens system of the said image capture device.
  - 9. A method according to claim 1, where the said geometric parameter is the location of a principal point of the lens system of the said image capture device.
  - 10. A method according to claim 1, where the alignment of said target image to said image capture device is such that distortion of the said captured image compared to said target image caused by perspective transformation is small compared to the distortion of the said captured image compared to said target image caused by geometric lens distortion.
  - 11. A method according to claim 1, where a plurality of geometric parameters that describe a transformation from said target image to said captured image are derived by simultaneous fitting to a composite transformation function characterised by the said plurality of geometric parameters.
  - 12. A method according to claim 1, where one or more geometric parameters that describe a perspective transformation from said target image to said captured image, and one or more geometric parameters that describe a geometric lens distortion transformation from said target image to said captured image, are derived by the steps of:
    - (A) deriving said parameters characterising said geometric lens distortion by said comparison of at least one pattern of said captured image with a corresponding pattern of said target image;
      
      (B) transforming said captured image according to an inverse of said geometric lens distortion parameters to produce a modified captured image; and
      
      (C) deriving said parameters characterising the perspective transformation by comparing at least one pattern of said modified captured image with a corresponding pattern of said target image.
  - 13. A method according to claim 12, wherein step (B) comprises modifying coordinates of said captured image according to said derived parameters.
  - 14. A method according to claim 1, where the said target image is an image fabricated on to a substantially planar surface material.
  - 15. A method according to claim 1, where the said target image is an image displayed on a display device.
  - 16. A method according to claim 1, where the said target image is an image displayed on a projection surface by an image projector.
  - 17. A method according to claim 1, where the said image capture device is a document scanner and said geometric parameters relate to the image-forming geometry of said scanner.
  - 18. A method according to claim 1, where the said image capture device is a camera and said geometric parameters relate to the image-forming geometry of said camera.
  - 19. A method according to claim 1, where the said geometric parameter is used to determine the alignment of an imaging plane within said image capture device, relative to a reference plane.
  - 20. A method according to claim 19, where the said imaging plane is coincident with an imaging sensor.
  - 21. A method according to claim 19, where the said imaging plane is coincident with a manual focusing screen.
  - 22. A method according to claim 19, where the said imaging plane is coincident with an autofocussing sensor.
  - 23. A method according to claim 1, wherein step (c) comprises correlating a pattern of said captured image with a pattern of said target image.
  - 24. A method according to claim 1, wherein at least one said alignment pattern of said target image comprises a composite of at least two of the patterns (i), (ii) and (iii).

25. A two-dimensional test chart for use in testing an imaging device, said test chart comprising a plurality of alignment patterns, at least one of said alignment patterns including one of:
- (i) a pattern comprising a 2D scale and rotation invariant basis function $f_{1} (r, θ) = {\begin{matrix} Re ⌊ w (r, θ) r^{i α + p} e^{ k θ} ⌋, & r > r_{0} \\ q, & r \leq r_{0} \end{matrix}$ where a≠
  
  0, k≠
  
  0, and q≠
  
  0;
  
  (ii) a pattern comprising a 1D scale invariant basis function
  f(x)=cos(β
  
  log|x|+γ
  
  ); and
  
  (iii) a pattern having a plurality of grey levels and comprising a plurality of superimposed sinusoidal patterns, said plurality of sinusoidal patterns having a plurality of predetermined discrete orientations.

26. A computer readable medium having a computer program recorded thereon, the program being executable by computer apparatus to cause an imaging device to reproduce a two-dimensional test image for use with in testing an imaging device, said test image comprising a plurality of alignment patterns, at least one of said alignment patterns including at least one of:
- (i) a pattern comprising a 2D scale and rotation invariant basis function $f_{1} (r, θ) = {\begin{matrix} Re ⌊ w (r, θ) r^{i α + p} e^{ k θ} ⌋, & r > r_{0} \\ q, & r \leq r_{0} \end{matrix}$ where a≠
  
  0, k≠
  
  0, and q≠
  
  0;
  
  (ii) a pattern comprising a 1D scale invariant basis function
  f(x)=cos(β
  
  log|x|+γ
  
  ); and
  
  (iii) a pattern having a plurality of grey levels and comprising a plurality of superimposed sinusoidal patterns, said plurality of sinusoidal patterns having a plurality of predetermined discrete orientations.

27. An imaging device testing system, said system comprising:
- apparatus incorporating a two-dimensional test chart, said test chart comprising a plurality of alignment patterns, at least one of said alignment patterns including one of;
  
  (i) a pattern comprising a 2D scale and rotation invariant basis function $f_{1} (r, θ) = {\begin{matrix} Re ⌊ w (r, θ) r^{i α + p} e^{ k θ} ⌋, & r > r_{0} \\ q, & r \leq r_{0} \end{matrix}$ where a≠
  
  0, k≠
  
  0, and q≠
  
  0;
  
  (ii) a pattern comprising a 1D scale invariant basis function
  f(x)=cos(β
  
  log|x|+γ
  
  ); and
  
  (iii) a pattern having a plurality of grey levels and comprising a plurality of superimposed sinusoidal patterns, said plurality of sinusoidal patterns having a plurality of predetermined discrete orientations; and
  
  an imaging device configured for imaging said test chart.

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Current Assignee
Canon Kabushiki Kaisha (Canon Inc.)
Original Assignee
Canon Kabushiki Kaisha (Canon Inc.)
Inventors
Arnison, Matthew R., Morgan-Mar, David, Deller, Christine Anne, Hardy, Stephen James, Larkin, Kieran Gerard

Granted Patent

US 8,818,130 B2
Time in Patent Office

Days
Field of Search
US Class Current

382/154
CPC Class Codes

G06T 5/006   Geometric correction correc...

G06T 5/80   Geometric correction

G06V 10/245   by locating a pattern; Spec...

H04N 1/00827   Arrangements for reading an...

H04N 17/002   for television cameras

Geometric parameter measurement of an imaging device

First Claim

1 Assignment

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Abstract

51 Citations

27 Claims

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Geometric parameter measurement of an imaging device

First Claim

1 Assignment

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0 Petitions

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Accused Products

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Abstract

51 Citations

27 Claims

Specification

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Solutions

Use Cases

Quick Links