Abstract

A method for orientation-selective enhancement of edges in color images is proposed. The method utilizes the capacity of digital micromirror devices to generate a positive and a negative color replica of the image used as input. When both images are slightly displaced and imagined together, one obtains an image with enhanced edges. The proposed technique does not require a coherent light source or precise alignment. The proposed method could be potentially useful for processing large image sequences in real time. Validation experiments are presented.

© 2012 Optical Society of America

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References

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  1. A. Koschan and M. A. Abidi, Color Image Processing (Wiley, 2008).
  2. C. L. Novak and S. A. Shafer, “Color edge detection,” in Proceedings of DARPA Image Understanding Workshop 1987 (Morgan Kaufmann, 1998), Vol. 1, pp. 35–37.
  3. M. Hedley and H. Yan, “Segmentation of color images using spatial and color space information,” J. Electron. Imaging 1, 374–380 (1992).
    [CrossRef]
  4. T. Carron and P. Lambert, “Color edge detector using jointly hue, saturation and intensity,” in Proceedings of ICIP-94 (IEEE, 1994), pp. 977–981.
  5. P. Trahanias and A. N. Venetsanopoulos, “Color edge detection using vector statistics,” IEEE Trans. Image Process. 2, 259–264 (1993).
    [CrossRef]
  6. P. E. Trahanias and A. N. Venetsanopoulos, “Vector order statistics operators as color edge detectors,” IEEE Trans. Syst. Man Cybern. B 26, 135–143 (1996).
    [CrossRef]
  7. S.-Y. Zhu, K. N. Plataniotis, and A. N. Venetsanopoulos, “Comprehensive analysis of edge detection in color image processing,” Opt. Eng. 38, 612–625 (1999).
    [CrossRef]
  8. A. R. Weeks, C. E. Felix, and H. R. Myler, “Edge detection of color images using the HSL color space,” Proc. SPIE 2424, 291–301 (1995).
    [CrossRef]
  9. J. Fan, D.. K. Y. Yau, A. K. Elmagarmid, and W. G. Aref, “Automatic image segmentation by integrating color-edge extraction and seeded region growing,” IEEE Trans. Image Process. 10, 1454–1466 (2001).
    [CrossRef]
  10. R. D. Dony and S. Wesolkowski, “Edge detection on color images using RGB vector angle,” in Proceeding of IEEE Canadian Conference on Electrical and Computer Engineering (IEEE, 1999), pp. 687–692.
  11. S. Wesolkowski and E. Jernigan, “Color edge detection in RGB using jointly Euclidean distance and vector angle,” in Proceedings of Vision Interface ’99 (Canadian Image Processing and Pattern Recognition Society, 1999), pp. 9–16.
  12. J. A. Ferrari and J. L. Flores, “Nondirectional edge enhancement by contrast reverted low-pass Fourier filtering,” Appl. Opt. 49, 3291–3296 (2010).
    [CrossRef]
  13. J. A. Ferrari, J. L. Flores, and G. Garcia-Torales, “Directional edge enhancement using a liquid-crystal display,” Opt. Commun. 283, 2803–2806 (2010).
    [CrossRef]
  14. J. L. Flores and J. A. Ferrari, “Orientation-selective edge detection/enhancement using the irradiance transport equation,” Appl. Opt. 49, 619–624 (2010).
    [CrossRef]
  15. D. Dudley, W. M. Duncan, and J. Slaughter, “Emerging digital micromirror device (DMD) applications,” Proc. SPIE 4985, 14–25 (2003).
    [CrossRef]
  16. D. Malacara, Color Vision and Colorimetry: Theory and Applications (SPIE, 2001).
  17. http://arttattler.com/designcoldwarmodern.html (accessed 6 October 2011).
  18. http://lujosabarcelona.blogs.elle.es/files/2011/02/color-block.jpg (accessed 6 October 2011).
  19. http://www.youtube.com/watch?v=Q8vfl1rR40M (accessed 6 October 2011).
  20. N. Zhang, J. Wang, and Y. Chen, “Image parallel processing based on GPU,” in Proceedings of the 2nd International Conference on Advanced Computer Control (ICACC) (IEEE, 2010), pp. 367–370.
  21. C. Gentsos, C. L. Sotiropoulou, S. Nikolaidis, and N. Vassiliadis, “Real-time canny edge detection parallel implementation for FPGAs,” Proceedings of 2010 17th IEEE International Conference on Electronics, Circuits, and Systems (IEEE, 2010), pp. 499–502.
  22. C. Claus, R. Huitl, J. Rausch, and W. Stechele, “Optimizing the SUSAN corner detection algorithm for a high speed FPGA implementation,” in Proceedings of International Conference on Field Programmable Logic and Applications, 2009 (IEEE, 2009), pp. 138–145.
  23. Texas Instruments, “Using the DLP Pico 2.0 kit for structured light applications,” Application Report DLPA021 (1–18 January 2010).

2010

2003

D. Dudley, W. M. Duncan, and J. Slaughter, “Emerging digital micromirror device (DMD) applications,” Proc. SPIE 4985, 14–25 (2003).
[CrossRef]

2001

J. Fan, D.. K. Y. Yau, A. K. Elmagarmid, and W. G. Aref, “Automatic image segmentation by integrating color-edge extraction and seeded region growing,” IEEE Trans. Image Process. 10, 1454–1466 (2001).
[CrossRef]

1999

S.-Y. Zhu, K. N. Plataniotis, and A. N. Venetsanopoulos, “Comprehensive analysis of edge detection in color image processing,” Opt. Eng. 38, 612–625 (1999).
[CrossRef]

1996

P. E. Trahanias and A. N. Venetsanopoulos, “Vector order statistics operators as color edge detectors,” IEEE Trans. Syst. Man Cybern. B 26, 135–143 (1996).
[CrossRef]

1995

A. R. Weeks, C. E. Felix, and H. R. Myler, “Edge detection of color images using the HSL color space,” Proc. SPIE 2424, 291–301 (1995).
[CrossRef]

1993

P. Trahanias and A. N. Venetsanopoulos, “Color edge detection using vector statistics,” IEEE Trans. Image Process. 2, 259–264 (1993).
[CrossRef]

1992

M. Hedley and H. Yan, “Segmentation of color images using spatial and color space information,” J. Electron. Imaging 1, 374–380 (1992).
[CrossRef]

Abidi, M. A.

A. Koschan and M. A. Abidi, Color Image Processing (Wiley, 2008).

Aref, W. G.

J. Fan, D.. K. Y. Yau, A. K. Elmagarmid, and W. G. Aref, “Automatic image segmentation by integrating color-edge extraction and seeded region growing,” IEEE Trans. Image Process. 10, 1454–1466 (2001).
[CrossRef]

Carron, T.

T. Carron and P. Lambert, “Color edge detector using jointly hue, saturation and intensity,” in Proceedings of ICIP-94 (IEEE, 1994), pp. 977–981.

Chen, Y.

N. Zhang, J. Wang, and Y. Chen, “Image parallel processing based on GPU,” in Proceedings of the 2nd International Conference on Advanced Computer Control (ICACC) (IEEE, 2010), pp. 367–370.

Claus, C.

C. Claus, R. Huitl, J. Rausch, and W. Stechele, “Optimizing the SUSAN corner detection algorithm for a high speed FPGA implementation,” in Proceedings of International Conference on Field Programmable Logic and Applications, 2009 (IEEE, 2009), pp. 138–145.

Dony, R. D.

R. D. Dony and S. Wesolkowski, “Edge detection on color images using RGB vector angle,” in Proceeding of IEEE Canadian Conference on Electrical and Computer Engineering (IEEE, 1999), pp. 687–692.

Dudley, D.

D. Dudley, W. M. Duncan, and J. Slaughter, “Emerging digital micromirror device (DMD) applications,” Proc. SPIE 4985, 14–25 (2003).
[CrossRef]

Duncan, W. M.

D. Dudley, W. M. Duncan, and J. Slaughter, “Emerging digital micromirror device (DMD) applications,” Proc. SPIE 4985, 14–25 (2003).
[CrossRef]

Elmagarmid, A. K.

J. Fan, D.. K. Y. Yau, A. K. Elmagarmid, and W. G. Aref, “Automatic image segmentation by integrating color-edge extraction and seeded region growing,” IEEE Trans. Image Process. 10, 1454–1466 (2001).
[CrossRef]

Fan, J.

J. Fan, D.. K. Y. Yau, A. K. Elmagarmid, and W. G. Aref, “Automatic image segmentation by integrating color-edge extraction and seeded region growing,” IEEE Trans. Image Process. 10, 1454–1466 (2001).
[CrossRef]

Felix, C. E.

A. R. Weeks, C. E. Felix, and H. R. Myler, “Edge detection of color images using the HSL color space,” Proc. SPIE 2424, 291–301 (1995).
[CrossRef]

Ferrari, J. A.

Flores, J. L.

Garcia-Torales, G.

J. A. Ferrari, J. L. Flores, and G. Garcia-Torales, “Directional edge enhancement using a liquid-crystal display,” Opt. Commun. 283, 2803–2806 (2010).
[CrossRef]

Gentsos, C.

C. Gentsos, C. L. Sotiropoulou, S. Nikolaidis, and N. Vassiliadis, “Real-time canny edge detection parallel implementation for FPGAs,” Proceedings of 2010 17th IEEE International Conference on Electronics, Circuits, and Systems (IEEE, 2010), pp. 499–502.

Hedley, M.

M. Hedley and H. Yan, “Segmentation of color images using spatial and color space information,” J. Electron. Imaging 1, 374–380 (1992).
[CrossRef]

Huitl, R.

C. Claus, R. Huitl, J. Rausch, and W. Stechele, “Optimizing the SUSAN corner detection algorithm for a high speed FPGA implementation,” in Proceedings of International Conference on Field Programmable Logic and Applications, 2009 (IEEE, 2009), pp. 138–145.

Jernigan, E.

S. Wesolkowski and E. Jernigan, “Color edge detection in RGB using jointly Euclidean distance and vector angle,” in Proceedings of Vision Interface ’99 (Canadian Image Processing and Pattern Recognition Society, 1999), pp. 9–16.

Koschan, A.

A. Koschan and M. A. Abidi, Color Image Processing (Wiley, 2008).

Lambert, P.

T. Carron and P. Lambert, “Color edge detector using jointly hue, saturation and intensity,” in Proceedings of ICIP-94 (IEEE, 1994), pp. 977–981.

Malacara, D.

D. Malacara, Color Vision and Colorimetry: Theory and Applications (SPIE, 2001).

Myler, H. R.

A. R. Weeks, C. E. Felix, and H. R. Myler, “Edge detection of color images using the HSL color space,” Proc. SPIE 2424, 291–301 (1995).
[CrossRef]

Nikolaidis, S.

C. Gentsos, C. L. Sotiropoulou, S. Nikolaidis, and N. Vassiliadis, “Real-time canny edge detection parallel implementation for FPGAs,” Proceedings of 2010 17th IEEE International Conference on Electronics, Circuits, and Systems (IEEE, 2010), pp. 499–502.

Novak, C. L.

C. L. Novak and S. A. Shafer, “Color edge detection,” in Proceedings of DARPA Image Understanding Workshop 1987 (Morgan Kaufmann, 1998), Vol. 1, pp. 35–37.

Plataniotis, K. N.

S.-Y. Zhu, K. N. Plataniotis, and A. N. Venetsanopoulos, “Comprehensive analysis of edge detection in color image processing,” Opt. Eng. 38, 612–625 (1999).
[CrossRef]

Rausch, J.

C. Claus, R. Huitl, J. Rausch, and W. Stechele, “Optimizing the SUSAN corner detection algorithm for a high speed FPGA implementation,” in Proceedings of International Conference on Field Programmable Logic and Applications, 2009 (IEEE, 2009), pp. 138–145.

Shafer, S. A.

C. L. Novak and S. A. Shafer, “Color edge detection,” in Proceedings of DARPA Image Understanding Workshop 1987 (Morgan Kaufmann, 1998), Vol. 1, pp. 35–37.

Slaughter, J.

D. Dudley, W. M. Duncan, and J. Slaughter, “Emerging digital micromirror device (DMD) applications,” Proc. SPIE 4985, 14–25 (2003).
[CrossRef]

Sotiropoulou, C. L.

C. Gentsos, C. L. Sotiropoulou, S. Nikolaidis, and N. Vassiliadis, “Real-time canny edge detection parallel implementation for FPGAs,” Proceedings of 2010 17th IEEE International Conference on Electronics, Circuits, and Systems (IEEE, 2010), pp. 499–502.

Stechele, W.

C. Claus, R. Huitl, J. Rausch, and W. Stechele, “Optimizing the SUSAN corner detection algorithm for a high speed FPGA implementation,” in Proceedings of International Conference on Field Programmable Logic and Applications, 2009 (IEEE, 2009), pp. 138–145.

Trahanias, P.

P. Trahanias and A. N. Venetsanopoulos, “Color edge detection using vector statistics,” IEEE Trans. Image Process. 2, 259–264 (1993).
[CrossRef]

Trahanias, P. E.

P. E. Trahanias and A. N. Venetsanopoulos, “Vector order statistics operators as color edge detectors,” IEEE Trans. Syst. Man Cybern. B 26, 135–143 (1996).
[CrossRef]

Vassiliadis, N.

C. Gentsos, C. L. Sotiropoulou, S. Nikolaidis, and N. Vassiliadis, “Real-time canny edge detection parallel implementation for FPGAs,” Proceedings of 2010 17th IEEE International Conference on Electronics, Circuits, and Systems (IEEE, 2010), pp. 499–502.

Venetsanopoulos, A. N.

S.-Y. Zhu, K. N. Plataniotis, and A. N. Venetsanopoulos, “Comprehensive analysis of edge detection in color image processing,” Opt. Eng. 38, 612–625 (1999).
[CrossRef]

P. E. Trahanias and A. N. Venetsanopoulos, “Vector order statistics operators as color edge detectors,” IEEE Trans. Syst. Man Cybern. B 26, 135–143 (1996).
[CrossRef]

P. Trahanias and A. N. Venetsanopoulos, “Color edge detection using vector statistics,” IEEE Trans. Image Process. 2, 259–264 (1993).
[CrossRef]

Wang, J.

N. Zhang, J. Wang, and Y. Chen, “Image parallel processing based on GPU,” in Proceedings of the 2nd International Conference on Advanced Computer Control (ICACC) (IEEE, 2010), pp. 367–370.

Weeks, A. R.

A. R. Weeks, C. E. Felix, and H. R. Myler, “Edge detection of color images using the HSL color space,” Proc. SPIE 2424, 291–301 (1995).
[CrossRef]

Wesolkowski, S.

R. D. Dony and S. Wesolkowski, “Edge detection on color images using RGB vector angle,” in Proceeding of IEEE Canadian Conference on Electrical and Computer Engineering (IEEE, 1999), pp. 687–692.

S. Wesolkowski and E. Jernigan, “Color edge detection in RGB using jointly Euclidean distance and vector angle,” in Proceedings of Vision Interface ’99 (Canadian Image Processing and Pattern Recognition Society, 1999), pp. 9–16.

Yan, H.

M. Hedley and H. Yan, “Segmentation of color images using spatial and color space information,” J. Electron. Imaging 1, 374–380 (1992).
[CrossRef]

Yau, D.. K. Y.

J. Fan, D.. K. Y. Yau, A. K. Elmagarmid, and W. G. Aref, “Automatic image segmentation by integrating color-edge extraction and seeded region growing,” IEEE Trans. Image Process. 10, 1454–1466 (2001).
[CrossRef]

Zhang, N.

N. Zhang, J. Wang, and Y. Chen, “Image parallel processing based on GPU,” in Proceedings of the 2nd International Conference on Advanced Computer Control (ICACC) (IEEE, 2010), pp. 367–370.

Zhu, S.-Y.

S.-Y. Zhu, K. N. Plataniotis, and A. N. Venetsanopoulos, “Comprehensive analysis of edge detection in color image processing,” Opt. Eng. 38, 612–625 (1999).
[CrossRef]

Appl. Opt.

IEEE Trans. Image Process.

J. Fan, D.. K. Y. Yau, A. K. Elmagarmid, and W. G. Aref, “Automatic image segmentation by integrating color-edge extraction and seeded region growing,” IEEE Trans. Image Process. 10, 1454–1466 (2001).
[CrossRef]

P. Trahanias and A. N. Venetsanopoulos, “Color edge detection using vector statistics,” IEEE Trans. Image Process. 2, 259–264 (1993).
[CrossRef]

IEEE Trans. Syst. Man Cybern. B

P. E. Trahanias and A. N. Venetsanopoulos, “Vector order statistics operators as color edge detectors,” IEEE Trans. Syst. Man Cybern. B 26, 135–143 (1996).
[CrossRef]

J. Electron. Imaging

M. Hedley and H. Yan, “Segmentation of color images using spatial and color space information,” J. Electron. Imaging 1, 374–380 (1992).
[CrossRef]

Opt. Commun.

J. A. Ferrari, J. L. Flores, and G. Garcia-Torales, “Directional edge enhancement using a liquid-crystal display,” Opt. Commun. 283, 2803–2806 (2010).
[CrossRef]

Opt. Eng.

S.-Y. Zhu, K. N. Plataniotis, and A. N. Venetsanopoulos, “Comprehensive analysis of edge detection in color image processing,” Opt. Eng. 38, 612–625 (1999).
[CrossRef]

Proc. SPIE

A. R. Weeks, C. E. Felix, and H. R. Myler, “Edge detection of color images using the HSL color space,” Proc. SPIE 2424, 291–301 (1995).
[CrossRef]

D. Dudley, W. M. Duncan, and J. Slaughter, “Emerging digital micromirror device (DMD) applications,” Proc. SPIE 4985, 14–25 (2003).
[CrossRef]

Other

D. Malacara, Color Vision and Colorimetry: Theory and Applications (SPIE, 2001).

http://arttattler.com/designcoldwarmodern.html (accessed 6 October 2011).

http://lujosabarcelona.blogs.elle.es/files/2011/02/color-block.jpg (accessed 6 October 2011).

http://www.youtube.com/watch?v=Q8vfl1rR40M (accessed 6 October 2011).

N. Zhang, J. Wang, and Y. Chen, “Image parallel processing based on GPU,” in Proceedings of the 2nd International Conference on Advanced Computer Control (ICACC) (IEEE, 2010), pp. 367–370.

C. Gentsos, C. L. Sotiropoulou, S. Nikolaidis, and N. Vassiliadis, “Real-time canny edge detection parallel implementation for FPGAs,” Proceedings of 2010 17th IEEE International Conference on Electronics, Circuits, and Systems (IEEE, 2010), pp. 499–502.

C. Claus, R. Huitl, J. Rausch, and W. Stechele, “Optimizing the SUSAN corner detection algorithm for a high speed FPGA implementation,” in Proceedings of International Conference on Field Programmable Logic and Applications, 2009 (IEEE, 2009), pp. 138–145.

Texas Instruments, “Using the DLP Pico 2.0 kit for structured light applications,” Application Report DLPA021 (1–18 January 2010).

T. Carron and P. Lambert, “Color edge detector using jointly hue, saturation and intensity,” in Proceedings of ICIP-94 (IEEE, 1994), pp. 977–981.

A. Koschan and M. A. Abidi, Color Image Processing (Wiley, 2008).

C. L. Novak and S. A. Shafer, “Color edge detection,” in Proceedings of DARPA Image Understanding Workshop 1987 (Morgan Kaufmann, 1998), Vol. 1, pp. 35–37.

R. D. Dony and S. Wesolkowski, “Edge detection on color images using RGB vector angle,” in Proceeding of IEEE Canadian Conference on Electrical and Computer Engineering (IEEE, 1999), pp. 687–692.

S. Wesolkowski and E. Jernigan, “Color edge detection in RGB using jointly Euclidean distance and vector angle,” in Proceedings of Vision Interface ’99 (Canadian Image Processing and Pattern Recognition Society, 1999), pp. 9–16.

Supplementary Material (1)

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Figures (6)

Fig. 1.
Fig. 1.

Scheme of the system for edge enhancement in a color image. D and E denote the DMD and its own control electronic interface, respectively. L, LS, M14, G, and C denote an imaging lens, a light source constituted by three RGB LEDs, four mirrors, a thin glass plate and a digital color camera, respectively. A personal computer is used to drive the DLP and the CCD camera.

Fig. 2.
Fig. 2.

Two representative micromirrors, mm1 tilted to the left and mm2 tilted to the right with respect to the direction orthogonal to the DMD surface (dotted line). Both micromirrors are illuminated from two different directions with the help of the mirrors M3 and M4. The light rays reflected (quasi-) orthogonal to the DMD surface will pass through the imaging lens (L).

Fig. 3.
Fig. 3.

Experimental results using computer generated test images. (a), (e) “Positive” images obtained when the light reflected by M4 is blocked; (b), (f) complementary (“negative”) images obtained when the light reflected by M3 is blocked; (c), (g) images obtained by superposition, with the “negative” image slightly displaced with respect to the “positive” one along the horizontal direction; (d), (h) images obtained by superposition, with the “negative” image slightly displaced along the vertical direction.

Fig. 4.
Fig. 4.

Experimental results using Picasso’s painting Dove of Peace as test image. (a), (b) “Positive” and “negative” image obtained experimentally, respectively; (c), (d) superposition of both images, with the “negative” image slightly displaced with respect to the “positive” one along the horizontal and vertical directions, respectively.

Fig. 5.
Fig. 5.

Experimental results using a set of colored cubes with pastel shades as test image. (a), (b) “Positive” and “negative” images, respectively; (c), (d) superposition of both images, with the negative replica slightly displaced in the horizontal and vertical directions, respectively.

Fig. 6.
Fig. 6.

Single-frame excerpt from a video recording (Media 1) showing the cell division of fruit fly embryo observed using two-photon fluorescence microscopy. (a) Original image, (b) complementary color image, (c) superposition of both images with the negative replica slightly displaced.

Tables (1)

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Table 1. Processing Time for Different Image Sizesa

Equations (2)

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Iout(x,y)=a·I(x,y)+b·{I0I(x+Δx,y)},
Iout(x,y)=(ab)·I(x,y)b·{I(x+Δx,y)I(x,y)}+b·I0.

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