Color Image Edge Detection using Pseudo-Complement and Matrix Operations
A color image edge detection algorithm is proposed in
this paper using Pseudo-complement and matrix rotation operations.
First, pseudo-complement method is applied on the image for each
channel. Then, matrix operations are applied on the output image of
the first stage. Dominant pixels are obtained by image differencing
between the pseudo-complement image and the matrix operated
image. Median filtering is carried out to smoothen the image thereby
removing the isolated pixels. Finally, the dominant or core pixels
occurring in at least two channels are selected. On plotting the
selected edge pixels, the final edge map of the given color image is
obtained. The algorithm is also tested in HSV and YCbCr color
spaces. Experimental results on both synthetic and real world images
show that the accuracy of the proposed method is comparable to
other color edge detectors. All the proposed procedures can be
applied to any image domain and runs in polynomial time.
[1] J.T.Allen and T. Huntsberger, "Comparing color edge detection and
segmentation methods", IEEE SouthEastCon-89, pp.722-728, 1989.
[2] Anil K. Jain, "Fundamentals of digital image processing", Prentice-Hall,
Englewood Cliffs, 1989.
[3] T. Carron and P. Lambert, "Color edge detector using jointly hue,
saturation and intensity", proceedings of IEEE International Conference
on Image Processing, pp.977-981, 1994.
[4] T. Carron and P. Lambert, "Fuzzy color extraction by inference rules -
quantitative study and evaluation performances", proceedings of IEEE
International Conference on Image Processing, pp.181-184, 1995.
[5] R. Nevatia, "A color edge detector and its use in scene segmentation",
IEEE Transactions on Systems, Man Cybernetics, Vol. 7, pp.820-826,
1977.
[6] M.A. Abidi, R.A. Salinas, C. Richardson and R.C. Gonzalez, "Data
fusion: color edge detection and surface reconstruction through
regularization", IEEE Transactions on Ind. Electron.,43(3), pp.355-363,
1996.
[7] P.E. Trahanias and A. N. Venetsanopoulos, "Vector order statistics
operators as color edge detectors", IEEE Transactions on Systems, Man,
Cybernetics, 26(1), pp.135-143, 1996.
[8] J. Canny, "A computational approach to edge detection", IEEE
Transactions on Pattern Analysis and Machine Intelligence, 8(6),
pp.679-698, 1986.
[9] C.L. Novak and S.A. Shafer, Color edge detection", Proceedings of
DARPA Image Understanding workshop, Los Angeles, CA, USA, vol.1,
pp.35-37, 1987.
[10] A. Koschan, "A comparative study on color edge detection",
Proceedings of 2nd Asian Conference on Computer Vision, ACCV 95,
vol.3, pp. 574-578, 1995.
[11] R. Machuca and K. Philips, "Applications of vector fields to image
processing", IEEE Transactions on Pattern Analysis and Machine
Intelligence, 5(3), pp316-329, 1983.
[12] T.N. Janakiraman and P.V.S.S.R. Chandra Mouli, "A Robust Preprocessing
step for efficient edge detection", Proceedings of IEEE
sponsored Intl. Conference ACVIT-07,Aurangabad, pp.810-815, 2007.
[13] T.N. Janakiraman and P.V.S.S.R. Chandra Mouli, "Dominant Pixel
Identification from Gray-level Image using various matrix rotation
operations - An application to Edge Detection", Proceedings of IEEE
sponsored Int. Conference ICSCN-08, Chennai, pp.510-513, 2008.
[1] J.T.Allen and T. Huntsberger, "Comparing color edge detection and
segmentation methods", IEEE SouthEastCon-89, pp.722-728, 1989.
[2] Anil K. Jain, "Fundamentals of digital image processing", Prentice-Hall,
Englewood Cliffs, 1989.
[3] T. Carron and P. Lambert, "Color edge detector using jointly hue,
saturation and intensity", proceedings of IEEE International Conference
on Image Processing, pp.977-981, 1994.
[4] T. Carron and P. Lambert, "Fuzzy color extraction by inference rules -
quantitative study and evaluation performances", proceedings of IEEE
International Conference on Image Processing, pp.181-184, 1995.
[5] R. Nevatia, "A color edge detector and its use in scene segmentation",
IEEE Transactions on Systems, Man Cybernetics, Vol. 7, pp.820-826,
1977.
[6] M.A. Abidi, R.A. Salinas, C. Richardson and R.C. Gonzalez, "Data
fusion: color edge detection and surface reconstruction through
regularization", IEEE Transactions on Ind. Electron.,43(3), pp.355-363,
1996.
[7] P.E. Trahanias and A. N. Venetsanopoulos, "Vector order statistics
operators as color edge detectors", IEEE Transactions on Systems, Man,
Cybernetics, 26(1), pp.135-143, 1996.
[8] J. Canny, "A computational approach to edge detection", IEEE
Transactions on Pattern Analysis and Machine Intelligence, 8(6),
pp.679-698, 1986.
[9] C.L. Novak and S.A. Shafer, Color edge detection", Proceedings of
DARPA Image Understanding workshop, Los Angeles, CA, USA, vol.1,
pp.35-37, 1987.
[10] A. Koschan, "A comparative study on color edge detection",
Proceedings of 2nd Asian Conference on Computer Vision, ACCV 95,
vol.3, pp. 574-578, 1995.
[11] R. Machuca and K. Philips, "Applications of vector fields to image
processing", IEEE Transactions on Pattern Analysis and Machine
Intelligence, 5(3), pp316-329, 1983.
[12] T.N. Janakiraman and P.V.S.S.R. Chandra Mouli, "A Robust Preprocessing
step for efficient edge detection", Proceedings of IEEE
sponsored Intl. Conference ACVIT-07,Aurangabad, pp.810-815, 2007.
[13] T.N. Janakiraman and P.V.S.S.R. Chandra Mouli, "Dominant Pixel
Identification from Gray-level Image using various matrix rotation
operations - An application to Edge Detection", Proceedings of IEEE
sponsored Int. Conference ICSCN-08, Chennai, pp.510-513, 2008.
@article{"International Journal of Engineering, Mathematical and Physical Sciences:51199", author = "T. N. Janakiraman and P. V. S. S. R. Chandra Mouli", title = "Color Image Edge Detection using Pseudo-Complement and Matrix Operations", abstract = "A color image edge detection algorithm is proposed in
this paper using Pseudo-complement and matrix rotation operations.
First, pseudo-complement method is applied on the image for each
channel. Then, matrix operations are applied on the output image of
the first stage. Dominant pixels are obtained by image differencing
between the pseudo-complement image and the matrix operated
image. Median filtering is carried out to smoothen the image thereby
removing the isolated pixels. Finally, the dominant or core pixels
occurring in at least two channels are selected. On plotting the
selected edge pixels, the final edge map of the given color image is
obtained. The algorithm is also tested in HSV and YCbCr color
spaces. Experimental results on both synthetic and real world images
show that the accuracy of the proposed method is comparable to
other color edge detectors. All the proposed procedures can be
applied to any image domain and runs in polynomial time.", keywords = "Color edge detection, dominant pixels, matrixrotation/shift operations, pseudo-complement.", volume = "2", number = "6", pages = "328-5", }