Abstract

In photogrammetric applications, camera calibration and orientation procedures are a prerequisite for the extraction of precise and reliable 3D metric information from images. This study presents a method for full automatic calibration of color digital cameras using color targets. Software developed using Borland C + + Builder programming language is used to apply the method. With this software, the calibration process is carried out in 3 stages: firstly, at least four of six color targets (whose 3D object coordinates are known) on each image of the overall test field are detected and the approximate exterior orientation parameters are computed. Then, the remaining target points are measured using the approximate image locations, determined using these parameters and the 3D object point coordinates parameters. Finally, calibration parameters are determined using a self-calibration bundle adjustment technique. The colored targets within the test field are assigned labels corresponding to their color. For the detection of color targets and computation of approximate exterior orientation elements, HSV color space was used together with space resection computation method for all the possible color labels of targets. To test the proposed method, full automatic calibration was carried out using six different digital cameras. The calibration accuracies achieved in object space were within the range 0.006 to 0.030 mm; the accuracies achieved in image space were within the range 0.14 to 0.51 µm.

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References

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  1. F. Remondino and C. Fraser, “Digital camera calibration methods: considerations and comparisons,” Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 36(5), 266–272 (2006).
  2. C. Fraser, M. R. Shortis, and G. Ganci, “Multi-sensor system self-calibration,” in Video-metrics IV (SPIE, 1995), pp. 2–18.
  3. C. Fraser, “Digital camera self-calibration,” ISPRS J. Photogramm. Remote Sens. 52(4), 149–159 (1997).
    [CrossRef]
  4. S. Cronk, C. Fraser, and H. Hanley, “Automatic metric calibration of colour digital cameras,” Photogramm. Rec. 21(116), 355–372 (2006).
    [CrossRef]
  5. M. R. Shortis, T. A. Clarke, and T. Short, “Comparison of some techniques for the subpixel location of discrete target images,” Proc. SPIE  2350, 25 (1994).
  6. A. Koschan and M. Abidi, Digital Color Image Processing, 1st ed. (John Wiley & Sons, Inc., 2008).
  7. K. Kraus, “Photogrammetry,” vols 1, Bonn, Dümmler, ISBN 3–427–78686–6, 78653–6. (1997).
  8. J. O. Otepka, H. B. Hanley, and C. Fraser, “Algorithm developments for automated offline vision metrology,” Proceedings of the ISPRS Commission V Symposium, ISPRS 2002, Corfu, Greece, September, 1–2, pp. 60–67.
  9. M. R. Shortis, T. A. Clarke, and S. Robson, ““Practical testing of the precision and accuracy of target image centering algorithms,” Videometrics IV,” Proc. SPIE 2598, 65–76 (1995).
    [CrossRef]
  10. R. A. H. Munjy, and M. Hussain, “Closed-form space resection using photo scale variation,” Proceedings of the XVIII ISPRS Congress, Vienna, Austria, 9–19 June 1996.

2006

F. Remondino and C. Fraser, “Digital camera calibration methods: considerations and comparisons,” Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 36(5), 266–272 (2006).

S. Cronk, C. Fraser, and H. Hanley, “Automatic metric calibration of colour digital cameras,” Photogramm. Rec. 21(116), 355–372 (2006).
[CrossRef]

1997

C. Fraser, “Digital camera self-calibration,” ISPRS J. Photogramm. Remote Sens. 52(4), 149–159 (1997).
[CrossRef]

1995

M. R. Shortis, T. A. Clarke, and S. Robson, ““Practical testing of the precision and accuracy of target image centering algorithms,” Videometrics IV,” Proc. SPIE 2598, 65–76 (1995).
[CrossRef]

1994

M. R. Shortis, T. A. Clarke, and T. Short, “Comparison of some techniques for the subpixel location of discrete target images,” Proc. SPIE  2350, 25 (1994).

Clarke, T. A.

M. R. Shortis, T. A. Clarke, and S. Robson, ““Practical testing of the precision and accuracy of target image centering algorithms,” Videometrics IV,” Proc. SPIE 2598, 65–76 (1995).
[CrossRef]

M. R. Shortis, T. A. Clarke, and T. Short, “Comparison of some techniques for the subpixel location of discrete target images,” Proc. SPIE  2350, 25 (1994).

Cronk, S.

S. Cronk, C. Fraser, and H. Hanley, “Automatic metric calibration of colour digital cameras,” Photogramm. Rec. 21(116), 355–372 (2006).
[CrossRef]

Fraser, C.

S. Cronk, C. Fraser, and H. Hanley, “Automatic metric calibration of colour digital cameras,” Photogramm. Rec. 21(116), 355–372 (2006).
[CrossRef]

F. Remondino and C. Fraser, “Digital camera calibration methods: considerations and comparisons,” Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 36(5), 266–272 (2006).

C. Fraser, “Digital camera self-calibration,” ISPRS J. Photogramm. Remote Sens. 52(4), 149–159 (1997).
[CrossRef]

Hanley, H.

S. Cronk, C. Fraser, and H. Hanley, “Automatic metric calibration of colour digital cameras,” Photogramm. Rec. 21(116), 355–372 (2006).
[CrossRef]

Remondino, F.

F. Remondino and C. Fraser, “Digital camera calibration methods: considerations and comparisons,” Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 36(5), 266–272 (2006).

Robson, S.

M. R. Shortis, T. A. Clarke, and S. Robson, ““Practical testing of the precision and accuracy of target image centering algorithms,” Videometrics IV,” Proc. SPIE 2598, 65–76 (1995).
[CrossRef]

Short, T.

M. R. Shortis, T. A. Clarke, and T. Short, “Comparison of some techniques for the subpixel location of discrete target images,” Proc. SPIE  2350, 25 (1994).

Shortis, M. R.

M. R. Shortis, T. A. Clarke, and S. Robson, ““Practical testing of the precision and accuracy of target image centering algorithms,” Videometrics IV,” Proc. SPIE 2598, 65–76 (1995).
[CrossRef]

M. R. Shortis, T. A. Clarke, and T. Short, “Comparison of some techniques for the subpixel location of discrete target images,” Proc. SPIE  2350, 25 (1994).

Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci.

F. Remondino and C. Fraser, “Digital camera calibration methods: considerations and comparisons,” Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 36(5), 266–272 (2006).

ISPRS J. Photogramm. Remote Sens.

C. Fraser, “Digital camera self-calibration,” ISPRS J. Photogramm. Remote Sens. 52(4), 149–159 (1997).
[CrossRef]

Photogramm. Rec.

S. Cronk, C. Fraser, and H. Hanley, “Automatic metric calibration of colour digital cameras,” Photogramm. Rec. 21(116), 355–372 (2006).
[CrossRef]

Proc. SPIE

M. R. Shortis, T. A. Clarke, and T. Short, “Comparison of some techniques for the subpixel location of discrete target images,” Proc. SPIE  2350, 25 (1994).

Proc. SPIE

M. R. Shortis, T. A. Clarke, and S. Robson, ““Practical testing of the precision and accuracy of target image centering algorithms,” Videometrics IV,” Proc. SPIE 2598, 65–76 (1995).
[CrossRef]

Other

R. A. H. Munjy, and M. Hussain, “Closed-form space resection using photo scale variation,” Proceedings of the XVIII ISPRS Congress, Vienna, Austria, 9–19 June 1996.

C. Fraser, M. R. Shortis, and G. Ganci, “Multi-sensor system self-calibration,” in Video-metrics IV (SPIE, 1995), pp. 2–18.

A. Koschan and M. Abidi, Digital Color Image Processing, 1st ed. (John Wiley & Sons, Inc., 2008).

K. Kraus, “Photogrammetry,” vols 1, Bonn, Dümmler, ISBN 3–427–78686–6, 78653–6. (1997).

J. O. Otepka, H. B. Hanley, and C. Fraser, “Algorithm developments for automated offline vision metrology,” Proceedings of the ISPRS Commission V Symposium, ISPRS 2002, Corfu, Greece, September, 1–2, pp. 60–67.

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Figures (6)

Fig. 1
Fig. 1

Hexacone representation of HSV color space.

Fig. 2
Fig. 2

Image of target parameters created by the software.

Fig. 3
Fig. 3

Software image obtained after resection driveback process.

Fig. 4
Fig. 4

Result dialog box obtained after self-calibration process.

Fig. 5
Fig. 5

Test field.

Fig. 6
Fig. 6

Image acquisition geometry.

Tables (3)

Tables Icon

Table 1 Technical Specifications of Cameras

Tables Icon

Table 2 Automatically Calculated Calibration Parameters for Six Camera Types

Tables Icon

Table 3 Self-calibration Bundle Adjustment Results of Six Cameras

Equations (6)

Equations on this page are rendered with MathJax. Learn more.

r = σ 12 σ 1 . σ 2 = ( g 1 g ¯ 1 ) ( g 2 g ¯ 2 ) ( g 1 g ¯ 1 ) 2 ( g 2 g ¯ 2 ) 2 ,
[ x 0 y 0 ] = i = 1 n j = 1 m g i j [ x i j y i j ] i = 1 n j = 1 m g i j       .
x x 0 + Δ x = c R 1 R 3 , y y 0 + Δ y = c R 2 R 3 ,
[ R 1 R 2 R 3 ] = R [ X X 0 Y Y 0 Z Z 0 ] ,
Δ x = x 0 x c Δ c + x ¯ r 2 k 1 + x ¯ r 4 k 2 + x ¯ r 6 k 3 + ( r 2 + 2 x ¯ 2 ) p 1 + 2 p 2 x ¯ y ¯ + b 1 x ¯ + b 2 y ¯ , Δ y = y 0 y c Δ c + y ¯ r 2 k 1 + y ¯ r 4 k 2 + y ¯ r 6 k 3 + 2 p 1 x ¯ y ¯ + ( r 2 + 2 y ¯ 2 ) p 2 ,
r = x ¯ 2 + y ¯ 2 ,             x ¯ = x x 0 ,             y ¯ = y y 0 ,

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