Abstract

A fully automated system that utilizes two CCD cameras and a polarizing beam splitter to create a polarization camera capable of sensing the polarization of reflected light from objects at pixel resolution is presented. The physical dimensions of the polarization of light beyond that of intensity carry extra information from a scene that can provide a richer set of descriptive physical constraints for the understanding of images. It has been shown that polarization cues can be used to perform dielectric and metal material identification and specular-and diffuse-reflection component analysis, as well as complex image segmentations that would be immensely more complicated or even infeasible with the use of intensity and color alone. A polarizing-plate beam splitter is placed in front of two CCD cameras so that light beams reflected from and transmitted through the beam splitter are each incident upon a separate camera. The polarization state of the reflected and the transmitted beams are linearly independent in terms of two orthogonal-polarization components, and these components are resolved in real time from the simple solution of two simultaneous linear equations. The polarizing-plate beam splitter allows for the simultaneous measurement of two orthogonal-polarization components over fairly wide field views suitable for vision and robotics. A polarization contrast image can be produced at 15 Hz. Two sets of orthogonal-polarization component pairs can be resolved by electronically switching a twisted nematic liquid crystal placed in front of the beam splitter, permitting the real-time measurement of partial-linear-polarization images at 7.5 Hz. A scheme for mapping states of partial linear polarization into hue, saturation, and intensity, which is a very suitable representation for a polarization image, is illustrated. The unique vision-understanding capabilities of this polarization camera system are demonstrated with experimental results showing polarization-based dielectric and metal material classification, shape constraints from reflected polarization, and specular-reflection and occluding-contour segmentations in a fairly complex scene.

© 1994 Optical Society of America

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References

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  1. L. B. Wolff, “Surface orientation from polarization images,” in Optics, Illumination, and Image Sensing for Machine Vision II, D. J. Svetkoff, ed., Proc. Soc. Photo-Opt. Instrum. Eng.850, 110–121 (1987).
    [CrossRef]
  2. L. B. Wolff, “Polarization-based material classification from specular reflection,”IEEE Trans. Pattern Anal. Mach. Intell. 12, 1059–1071 (1990).
    [CrossRef]
  3. L. B. Wolff, T. E. Boult, “Constraining object features using a polarization reflectance model,”IEEE Trans. Pattern Anal. Mach. Intell. 13, 635–657 (1991).
    [CrossRef]
  4. L. B. Wolff, “Polarization methods in computer vision,” Ph.D. dissertation (Columbia University, New York, 1991).
  5. T. E. Boult, L. B. Wolff, “Physically-based edge labeling,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (Institute of Electrical and Electronics Engineers, New York, 1991), pp. 656–662.
  6. L. B. Wolff, T. A. Mancini, “Liquid crystal polarization camera,” in Proceedings of the IEEE Workshop on Applications of Computer Vision (Institute of Electrical and Electronics Engineers, New York, 1992), pp. 120–127.
    [CrossRef]
  7. D. F. Elmore, “The advanced Stokes polarimeter: a new instrument for solar magnetic field research,” Tech. Rep. (High Altitude Observatory of the National Center for Atmospheric Research, Boulder, Colo., 1992).
  8. G. D. Bernard, R. Wehner, “Functional similarities between polarization vision and color vision,” Vision Res. 17, 1019–1028 (1977).
    [CrossRef] [PubMed]
  9. G. A. Mazokhin-Porshnyakov, Insect Vision (Plenum, New York, 1969).
  10. S. Rossel, R. Wehner, “Polarization vision in bees,” Nature 323, 128–131 (1969).
    [CrossRef]
  11. D. A. Cameron, E. N. Pugh, “Double cones as a basis for a new type of polarization vision in vertebrates,” Nature 353, 161–164 (1991).
    [CrossRef] [PubMed]
  12. C. W. Hawryshyn, “Polarization vision in fish,” Am. Sci. 80, 164–175 (1992).
  13. M. Born, E. Wolf, Principles of Optics (Pergamon, New York, 1959).
  14. D. Clarke, J. F. Grainger, Polarized Light and Optical Measurement (Pergamon, New York, 1971).
  15. R. Siegal, J. R. Howell, Thermal Radiation Heat Transfer (McGraw-Hill, New York, 1981).
  16. G. Healey, T. O. Binford, “Predicting material classes,” in Proceedings of the DARPA Image Understanding Workshop (Defense Advanced Research Projects Agency, Arlington, Va., 1988), pp. 1140–1146.
  17. G. Healey, “Using color for geometry-insensitive segmentation,” J. Opt. Soc. Am. A 6, 920–937 (1989).
    [CrossRef]
  18. E. B. Priestly, P. J. Wojtowicz, P. Sheng, Introduction to Liquid Crystals (Plenum, New York, 1975).
  19. T. H. Waterman, “Polarization sensitivity,” in Handbook of Sensory Physiology, H. J. Altrum, ed. (Springer-Verlag, New York, 1981), Vol. 7, Pt. 6(b), pp. 283–463.

1992 (1)

C. W. Hawryshyn, “Polarization vision in fish,” Am. Sci. 80, 164–175 (1992).

1991 (2)

L. B. Wolff, T. E. Boult, “Constraining object features using a polarization reflectance model,”IEEE Trans. Pattern Anal. Mach. Intell. 13, 635–657 (1991).
[CrossRef]

D. A. Cameron, E. N. Pugh, “Double cones as a basis for a new type of polarization vision in vertebrates,” Nature 353, 161–164 (1991).
[CrossRef] [PubMed]

1990 (1)

L. B. Wolff, “Polarization-based material classification from specular reflection,”IEEE Trans. Pattern Anal. Mach. Intell. 12, 1059–1071 (1990).
[CrossRef]

1989 (1)

1977 (1)

G. D. Bernard, R. Wehner, “Functional similarities between polarization vision and color vision,” Vision Res. 17, 1019–1028 (1977).
[CrossRef] [PubMed]

1969 (1)

S. Rossel, R. Wehner, “Polarization vision in bees,” Nature 323, 128–131 (1969).
[CrossRef]

Bernard, G. D.

G. D. Bernard, R. Wehner, “Functional similarities between polarization vision and color vision,” Vision Res. 17, 1019–1028 (1977).
[CrossRef] [PubMed]

Binford, T. O.

G. Healey, T. O. Binford, “Predicting material classes,” in Proceedings of the DARPA Image Understanding Workshop (Defense Advanced Research Projects Agency, Arlington, Va., 1988), pp. 1140–1146.

Born, M.

M. Born, E. Wolf, Principles of Optics (Pergamon, New York, 1959).

Boult, T. E.

L. B. Wolff, T. E. Boult, “Constraining object features using a polarization reflectance model,”IEEE Trans. Pattern Anal. Mach. Intell. 13, 635–657 (1991).
[CrossRef]

T. E. Boult, L. B. Wolff, “Physically-based edge labeling,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (Institute of Electrical and Electronics Engineers, New York, 1991), pp. 656–662.

Cameron, D. A.

D. A. Cameron, E. N. Pugh, “Double cones as a basis for a new type of polarization vision in vertebrates,” Nature 353, 161–164 (1991).
[CrossRef] [PubMed]

Clarke, D.

D. Clarke, J. F. Grainger, Polarized Light and Optical Measurement (Pergamon, New York, 1971).

Elmore, D. F.

D. F. Elmore, “The advanced Stokes polarimeter: a new instrument for solar magnetic field research,” Tech. Rep. (High Altitude Observatory of the National Center for Atmospheric Research, Boulder, Colo., 1992).

Grainger, J. F.

D. Clarke, J. F. Grainger, Polarized Light and Optical Measurement (Pergamon, New York, 1971).

Hawryshyn, C. W.

C. W. Hawryshyn, “Polarization vision in fish,” Am. Sci. 80, 164–175 (1992).

Healey, G.

G. Healey, “Using color for geometry-insensitive segmentation,” J. Opt. Soc. Am. A 6, 920–937 (1989).
[CrossRef]

G. Healey, T. O. Binford, “Predicting material classes,” in Proceedings of the DARPA Image Understanding Workshop (Defense Advanced Research Projects Agency, Arlington, Va., 1988), pp. 1140–1146.

Howell, J. R.

R. Siegal, J. R. Howell, Thermal Radiation Heat Transfer (McGraw-Hill, New York, 1981).

Mancini, T. A.

L. B. Wolff, T. A. Mancini, “Liquid crystal polarization camera,” in Proceedings of the IEEE Workshop on Applications of Computer Vision (Institute of Electrical and Electronics Engineers, New York, 1992), pp. 120–127.
[CrossRef]

Mazokhin-Porshnyakov, G. A.

G. A. Mazokhin-Porshnyakov, Insect Vision (Plenum, New York, 1969).

Priestly, E. B.

E. B. Priestly, P. J. Wojtowicz, P. Sheng, Introduction to Liquid Crystals (Plenum, New York, 1975).

Pugh, E. N.

D. A. Cameron, E. N. Pugh, “Double cones as a basis for a new type of polarization vision in vertebrates,” Nature 353, 161–164 (1991).
[CrossRef] [PubMed]

Rossel, S.

S. Rossel, R. Wehner, “Polarization vision in bees,” Nature 323, 128–131 (1969).
[CrossRef]

Sheng, P.

E. B. Priestly, P. J. Wojtowicz, P. Sheng, Introduction to Liquid Crystals (Plenum, New York, 1975).

Siegal, R.

R. Siegal, J. R. Howell, Thermal Radiation Heat Transfer (McGraw-Hill, New York, 1981).

Waterman, T. H.

T. H. Waterman, “Polarization sensitivity,” in Handbook of Sensory Physiology, H. J. Altrum, ed. (Springer-Verlag, New York, 1981), Vol. 7, Pt. 6(b), pp. 283–463.

Wehner, R.

G. D. Bernard, R. Wehner, “Functional similarities between polarization vision and color vision,” Vision Res. 17, 1019–1028 (1977).
[CrossRef] [PubMed]

S. Rossel, R. Wehner, “Polarization vision in bees,” Nature 323, 128–131 (1969).
[CrossRef]

Wojtowicz, P. J.

E. B. Priestly, P. J. Wojtowicz, P. Sheng, Introduction to Liquid Crystals (Plenum, New York, 1975).

Wolf, E.

M. Born, E. Wolf, Principles of Optics (Pergamon, New York, 1959).

Wolff, L. B.

L. B. Wolff, T. E. Boult, “Constraining object features using a polarization reflectance model,”IEEE Trans. Pattern Anal. Mach. Intell. 13, 635–657 (1991).
[CrossRef]

L. B. Wolff, “Polarization-based material classification from specular reflection,”IEEE Trans. Pattern Anal. Mach. Intell. 12, 1059–1071 (1990).
[CrossRef]

L. B. Wolff, “Surface orientation from polarization images,” in Optics, Illumination, and Image Sensing for Machine Vision II, D. J. Svetkoff, ed., Proc. Soc. Photo-Opt. Instrum. Eng.850, 110–121 (1987).
[CrossRef]

L. B. Wolff, “Polarization methods in computer vision,” Ph.D. dissertation (Columbia University, New York, 1991).

T. E. Boult, L. B. Wolff, “Physically-based edge labeling,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (Institute of Electrical and Electronics Engineers, New York, 1991), pp. 656–662.

L. B. Wolff, T. A. Mancini, “Liquid crystal polarization camera,” in Proceedings of the IEEE Workshop on Applications of Computer Vision (Institute of Electrical and Electronics Engineers, New York, 1992), pp. 120–127.
[CrossRef]

Am. Sci. (1)

C. W. Hawryshyn, “Polarization vision in fish,” Am. Sci. 80, 164–175 (1992).

IEEE Trans. Pattern Anal. Mach. Intell. (2)

L. B. Wolff, “Polarization-based material classification from specular reflection,”IEEE Trans. Pattern Anal. Mach. Intell. 12, 1059–1071 (1990).
[CrossRef]

L. B. Wolff, T. E. Boult, “Constraining object features using a polarization reflectance model,”IEEE Trans. Pattern Anal. Mach. Intell. 13, 635–657 (1991).
[CrossRef]

J. Opt. Soc. Am. A (1)

Nature (2)

S. Rossel, R. Wehner, “Polarization vision in bees,” Nature 323, 128–131 (1969).
[CrossRef]

D. A. Cameron, E. N. Pugh, “Double cones as a basis for a new type of polarization vision in vertebrates,” Nature 353, 161–164 (1991).
[CrossRef] [PubMed]

Vision Res. (1)

G. D. Bernard, R. Wehner, “Functional similarities between polarization vision and color vision,” Vision Res. 17, 1019–1028 (1977).
[CrossRef] [PubMed]

Other (12)

G. A. Mazokhin-Porshnyakov, Insect Vision (Plenum, New York, 1969).

L. B. Wolff, “Polarization methods in computer vision,” Ph.D. dissertation (Columbia University, New York, 1991).

T. E. Boult, L. B. Wolff, “Physically-based edge labeling,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (Institute of Electrical and Electronics Engineers, New York, 1991), pp. 656–662.

L. B. Wolff, T. A. Mancini, “Liquid crystal polarization camera,” in Proceedings of the IEEE Workshop on Applications of Computer Vision (Institute of Electrical and Electronics Engineers, New York, 1992), pp. 120–127.
[CrossRef]

D. F. Elmore, “The advanced Stokes polarimeter: a new instrument for solar magnetic field research,” Tech. Rep. (High Altitude Observatory of the National Center for Atmospheric Research, Boulder, Colo., 1992).

E. B. Priestly, P. J. Wojtowicz, P. Sheng, Introduction to Liquid Crystals (Plenum, New York, 1975).

T. H. Waterman, “Polarization sensitivity,” in Handbook of Sensory Physiology, H. J. Altrum, ed. (Springer-Verlag, New York, 1981), Vol. 7, Pt. 6(b), pp. 283–463.

L. B. Wolff, “Surface orientation from polarization images,” in Optics, Illumination, and Image Sensing for Machine Vision II, D. J. Svetkoff, ed., Proc. Soc. Photo-Opt. Instrum. Eng.850, 110–121 (1987).
[CrossRef]

M. Born, E. Wolf, Principles of Optics (Pergamon, New York, 1959).

D. Clarke, J. F. Grainger, Polarized Light and Optical Measurement (Pergamon, New York, 1971).

R. Siegal, J. R. Howell, Thermal Radiation Heat Transfer (McGraw-Hill, New York, 1981).

G. Healey, T. O. Binford, “Predicting material classes,” in Proceedings of the DARPA Image Understanding Workshop (Defense Advanced Research Projects Agency, Arlington, Va., 1988), pp. 1140–1146.

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Figures (22)

Fig. 1
Fig. 1

Previously developed liquid-crystal polarization camera.

Fig. 2
Fig. 2

Recently developed polarization camera utilizing two CCD cameras and a polarizing beam splitter.

Fig. 3
Fig. 3

Recently developed polarization camera utilizing two CCD cameras, a polarizing beam splitter, and a TN liquid crystal.

Fig. 4
Fig. 4

Linearly polarized electromagnetic light wave. E, H, two mutually orthogonal waveforms representing, respectively, electric and magnetic fields.

Fig. 5
Fig. 5

Unpolarized light incident upon a linear-polarizing filter transmitted as linear-polarized light orientated parallel to the transmission axis.

Fig. 6
Fig. 6

Transmitted radiance sinusoid defined as pixel intensity versus linear-polarizer angle.

Fig. 7
Fig. 7

Definition of the plane of incidence at a point on a smooth object surface.

Fig. 8
Fig. 8

Polarization of specular (interface) reflection resulting from unpolarized light incident upon an object surface.

Fig. 9
Fig. 9

Polarization of diffuse reflection resulting from unpolarized light incident upon a dielectric object surface.

Fig. 10
Fig. 10

Top-view diagram of a two-CCD polarization camera with a polarizing beam splitter and, in its full configuration, with a TN liquid crystal. The P and the S directions are defined.

Fig. 11
Fig. 11

Rotation of the linear-polarized component of partially linear-polarized light by a TN liquid crystal.

Fig. 12
Fig. 12

P and S directions with a TN liquid crystal in a 0° twist state (solid arrowheads) and in a 45° twist state (dashed arrowheads).

Fig. 13
Fig. 13

Representation scheme for partial linear polarization at a pixel in a polarization image in terms of color hue, color saturation, and intensity.

Fig. 14
Fig. 14

Diagram depicting concentric circles of linear-polarizing transmission orientations in a radial-polarization filter. At a point on a radial-polarizing filter light becomes linearly polarized at an orientation that is tangent to the circle going through that point.

Plate 1
Plate 1

Polarization image of a radial-polarization filter taken by a two-CCD polarization camera with a polarizing beam splitter and a TN liquid crystal.

Plate 2
Plate 2

Intensity image of a ceramic cup and its reflection in a glass mirror.

Plate 3
Plate 3

Partial-polarization-intensity image produced by a two-CCD polarization camera with a polarizing beam splitter. Partial polarization is represented as the saturation of the color hue blue.

Plate 4
Plate 4

Polarization image produced by a two-CCD polarization camera with a polarizing beam splitter and a TN liquid crystal.

Plate 5
Plate 5

Intensity image of a ceramic cup under extended illumination.

Plate 6
Plate 6

Polarization image produced by a two-CCD polarization camera with a polarizing beam splitter and a TN liquid crystal.

Plate 7
Plate 7

Intensity image of a circuit board with metal solder, plastic dielectric substrate, and translucent dielectric coating on solder metal.

Plate 8
Plate 8

Material segmentation produced by a two-CCD polarization camera with a polarizing beam splitter. Blue corresponds to dielectric, red corresponds to metal, and yellow corresponds to translucent dielectric coating on solder metal. Some red shows where translucent dielectric coating on solder is crinkled.

Equations (16)

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

partial polarization = I max - I min I max + I min ,
I max - I min I max + I min ( partial polariaztion ) , I max + I min ( total intensity ) , θ ( phase ) .
θ = ( 1 / 2 ) tan - 1 ( I 0 + I 90 - 2 I 45 I 90 - I 0 ) ,
I max + I min = I 0 + I 90 ,
I max - I min I max + I min = I 90 - I 0 ( I 90 + I 0 ) cos ( 2 θ ) .
I max I min ,
a P + b S = I transmitted , ( 1 - a ) P + ( 1 - b ) S = I reflected ,
S = I tramsmitted ( 1 - a ) - a I reflected b - a ,
P = I transmitted ( 1 - b ) - b I reflected a - b .
P - S P + S .
P - S cos 2 θ ( P + S )
I max + I min 2 - I max - I min 2 cos 2 ( ϕ - θ ) .
I 0 = I max + I min 2 - I max - I min 2 cos 2 θ , I 45 = I max + I min 2 - I max - I min 2 sin 2 θ , I 90 = I max + I min 2 + I max - I min 2 cos 2 θ ,
I 0 + I 90 = I max + I min             [ Eq . ( 3 ) ] , I 90 - I 0 = ( I max - I min ) cos 2 θ , I 0 + I 90 - 2 I 45 = ( I max - I min ) sin 2 θ .
I 0 + I 90 - 2 I 45 I 90 - I 0 = tan 2 θ θ = ( 1 / 2 ) tan - 1 ( I 0 + I 90 - 2 I 45 I 90 - I 0 ) ,
I 90 - I 0 I 90 + I 0 = I max - I min I max + I min cos 2 θ I max - I min I max + I min = I 90 - I 0 ( I 90 - I 0 ) cos 2 θ ,

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