Edge Detection in Low Contrast Images
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32922
Edge Detection in Low Contrast Images

Authors: Koushlendra Kumar Singh, Manish Kumar Bajpai, Rajesh K. Pandey


The edges of low contrast images are not clearly distinguishable to human eye. It is difficult to find the edges and boundaries in it. The present work encompasses a new approach for low contrast images. The Chebyshev polynomial based fractional order filter has been used for filtering operation on an image. The preprocessing has been performed by this filter on the input image. Laplacian of Gaussian method has been applied on preprocessed image for edge detection. The algorithm has been tested on two test images.

Keywords: Chebyshev polynomials, Fractional order differentiator, Laplacian of Gaussian (LoG) method, Low contrast image.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1099850

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3246


[1] R. C. Gonzalez, Richard E. Woods, Digital Image Processing, Third Edition, Pearson Education, New Delhi, 2009.
[2] A. Rosenfeld and M. Thurston, “Edge and curve detection for visual scene analysis” IEEE Trans. Cornput., vol. C-20, pp. 562-569, 1971.
[3] D. Man, Vision. San Francisco, CA: Freeman, 1982.
[4] D. Marrand E. Hildreth, “Theory of edge detection,” Proc. Roy. Soc. London, vol. B207, pp. 187-217, 1980.
[5] A. P. Witkin, “Scale-space filtering” in Proc. IJCAI-8, 1983.
[6] A. L. Yuille and T. Poggio, “Scaling theorems for zero-crossings” IEEE Trans. Patfern Anal. Machine Intell., vol. PAMI-8, pp. 15-25, 1986.
[7] J.M.S. Prewitt, “Object Enhancement and Extraction” Picture Processing and Psychopictorics, B. Lipkin and A. Rosenfeld, eds., pp. 75-149. New York: Academic, 1970.
[8] J. Canny, “A Computational Approach to Edge Detection” IEEE Trans. Pattern Analysis and Machine Intelligence, Vol.8 (6), pp. 679- 698, Nov. 1986.
[9] R. Deriche. “Fast algorithms for low-level vision”, IEEE Trans, PAMI, Vol.12 no A pp. 78-87, 1990.
[10] J. Shen and S. Castan, “An Optimal Linear Operator for Step Edge Detection” Computer Vision Graphics Image Processing, vol. 54 no. 2, pp. 112-13, Mar. 1992.
[11] S. Lanser and W. Eckstein, “Eine Modification des Deriche-VerfahrenszurKantendetektion”, In B. Radig, ed., Mustererkennung 1991, vol. 290 of InformatikFachberichte, DAGMSymposium, Munchen, Springer, Berlin, 1991,pp. 151-158.
[12] B. Jahne, H. Scharr, and S. Korgel, “Principles of filter design”, In B. Jahne, H. HauEecker, and P. GeiEJer, eds., Computer Vision and Applications, vol 2, Signal Processing and Pattern Recognition, chapter 6, Academic Press, San Diego. pp 125-151, 1999.
[13] R.P. Johnson, Contrast based edge detection, Pattern Recognition Vol. 23, pp. 311–318,1990.
[14] Koushlendra K.Singh, Manish K. Bajpai, Rajesh K. Pandey “A Novel Approach for Enhancement of Geometric and Contrast ResolutionProperties of Low Contrast Images”IIITDMJ/CSE/2014/PGR0108, 2014.
[15] D.Chen, Y.Q.Chen, “Digital Fractional Order Savitzky-GolayDifferentiator” IEEE trans. on Circuit and System-II: Express Briefs Vol. 58 pp.758-762, Nov. 2011.
[16] S.Guillon, P.Baylon, M.Najim, N.Keskes, Adaptive nonlinear filters for 2-D and 3-D image enhancement, Signal Processing,Vol. 67,pp.237-254, 1998.
[17] S.K.Mitra, Digital Signal Processing: A computer based approach, McGraw-Hill India edition, 2004.
[18] T.J.Rivlin, The chebyshev polynomials, John Wiley & Sons press, 1974.
[19] I.Podulubny, Fractional Differential Equation, Mathematics in Science & Engineering, 198, Academic Press: California, USA.
[20] http://photojournal.jpl.nasa.gov/catalog/PIA10300.