Abstract
This paper proposes a new approach for structure based separation of image objects using fuzzy morphology. With set operators in fuzzy context, we apply an adaptive alpha-cut morphological processing for edge detection, image enhancement and segmentation. A Top-hat transform is first applied to the input image and the resulting image is thresholded to a binary form. The image is then thinned using hit-or-miss transform. Finally, m-connectivity is used to keep the desired number of connected pixels. The output image is overlayed on the original for enhanced boundaries. Experiments were performed using real images of aerial views, sign boards and biological objects. A comparison to other edge enhancement techniques like unsharp masking, sobel and laplacian filtering shows improved performance by the proposed technique.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Gonzalez, W.: Digital Image Processing, 2nd edn. Prentice Hall, Englewood Cliffs (2002)
Liu, H.C., Srinath, M.D.: Partial shape classification using contour matching in distance transformation. IEEE Transactions on Pattern Analysis and Machine Intelligence 12, 1072–10791 (1990)
Marr, D., Hildreth, E.: Theory of edge detection. Proc. R. Soc. Lond. 207, 187–217 (1980)
Brown, L.G.: A survey of image registeration techniques. ACM Computing Surveys 24, 352–376 (1992)
Hoff, W., Ahuja, N.: Surface from stereo: Integrating feature matching, disparity estimation, and contoure detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 11, 121–136 (1989)
Lengagne, R.P.F., Monga, O.: Using crest lines to guide sufrace reconstructin from stereo. In: IEEE International Conference on Pattern Recognition (1996)
Matheron, G.: Random Sets and Integral Geometry. Wiley, New York (1975)
Serra, J.: Image Analysis and Mathematical Morphology. Academic Press, London (1982)
Rosenfeld, A., Kak, A.C.: Digital Picture Processing. Academic Press, Boston (1982)
Preston, D.: Modern Cellular Automata. Plenum Press, New York (1984)
Maragos, P., Schafer, R.W.: Morphological filters. par i: Their set-theoretic analysis and relations to linear shift-invariant filters. part ii their relations to median, order-statistic, and stack filters. IEEE Transactions on Pattern Analysis and Machine Intelligence (1987)
Maragos, P., Schafer, R.W.: Morphological systems for mulitdimensional signal processing. In: Trew, R.J. (ed.) Proc. of IEEE, pp. 690–710 (1990)
Heijmans, H.: Morphological Image Operators. Academic Press, Boston (1994)
Serra: Image Analysis and Mathematical Morphology. Academic Press, Boston (1988)
Bovik, A.: Morphological filtering for image enhancement and feature detection. In: Bovik, A. (ed.) Handbook of image and video processing, pp. 135–156 (2005)
Bloch, I., Maitre, H.: Fuzzy mathematical morphologies: A comparative study. Pattern Recognition (1995)
Soille: Morphological Image Analysis: Principles and Applications. Springer, Berlin (1999)
Tizhoosh: Fuzzy Image Processing. Springer, Berlin (1997)
Rosenfeld: The fuzzy geometry of image subsets. Pattern Recognition Letters (1984)
Kaufmann, G.: Fuzzy Mathematical Models in Engineering and Mangement Science. Elsevier Science Inc. New York (1988)
Nachtegael, Van der Weken, Van De Ville, Kerre (eds.): Fuzzy Filters for Image Processing. Studies in Fuzziness and Soft Computing, vol. 1. Springer, Heidelberg (2004)
Popov: Fuzzy mathematical morphology and its applications to colour image processing. W S C G (2007)
Ito, A.: Tissue boundary extraction from ultrasonogram by fuzzy morphology processing. In: 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, vol. 20, IEEE, Los Alamitos (1998)
Maccarone, T., Gesu: Fuzzy mathematical morphology to analyse astronomical images. In: International Conference on Pattern Recognition. (1992)
Wirth, N.: Applications of fuzzy morphology to contrast enhancement. In: Annual Meeting of the N. American Fuzzy Information Processing Society (2005)
Großert, Köppen, N.: A new approach to fuzzy morphology based on fuzzy integral and its application in image processing. In: ICPR 1996, vol. 2, pp. 625–630 (2005)
Strauss, C.: Fuzzy morphology for omnidirectional images. In: IEEE International Conference on Image Processing, vol. 2, pp. 141–144. IEEE, Los Alamitos (2005)
Bloch, S.: Why robots should use fuzzy mathematical morphology. In: 1st Int. ICSC-NAISO Congress on Neuro-Fuzzy Technologies (2002)
Otsu, N.: A threshold selection method from gray-level histogram. IEEE Transactin on Systems, Man and Cybernetics (1979)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mansoor, A.B., Mian, A.S., Khan, A., Khan, S.A. (2007). Fuzzy Morphology for Edge Detection and Segmentation. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2007. Lecture Notes in Computer Science, vol 4842. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76856-2_80
Download citation
DOI: https://doi.org/10.1007/978-3-540-76856-2_80
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-76855-5
Online ISBN: 978-3-540-76856-2
eBook Packages: Computer ScienceComputer Science (R0)