Abstract
Component-trees can be used for the design of image processing methods, and in particular segmentation ones. However, despite their ability to consider various kinds of knowledge and their tractable computation, methodological deadlocks often forbid to efficiently involve them in real applications. In this article, we explore new solutions to some of these deadlocks, and more especially those related to (i) complexity of the structures of interest and (ii) multiple knowledge handling. The usefulness of the proposed strategies is illustrated by preliminary results related to vessel segmentation from 3-D angiographic data.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
References
Hanusse, P., Guillataud, P.: Sémantique des images par analyse dendronique. In: RFIA 1991, vol. 2, pp. 577–588 (1991)
Chen, L., Berry, M., Hargrove, W.: Using dendronal signatures for feature extraction and retrieval. International Journal of Imaging Systems and Technology 11(4), 243–253 (2000)
Mattes, J., Demongeot, J.: Efficient algorithms to implement the confinement tree. In: Nyström, I., Sanniti di Baja, G., Borgefors, G. (eds.) DGCI 2000. LNCS, vol. 1953, pp. 392–405. Springer, Heidelberg (2000)
Salembier, P., Oliveras, A., Garrido, L.: Anti-extensive connected operators for image and sequence processing. IEEE Transactions on Image Processing 7(4), 555–570 (1998)
Breen, E.J., Jones, R.: Attribute openings, thinnings, and granulometries. Computer Vision and Image Understanding 64(3), 377–389 (1996)
Najman, L., Couprie, M.: Building the component tree in quasi-linear time. IEEE Transactions on Image Processing 15(11), 3531–3539 (2006)
Menotti, D., Najman, L., de Albuquerque Araújo, A.: 1D component tree in linear time and space and its application to gray-level image multithresholding. In: ISMM 2007, vol. 1, pp. 437–448. INPE (2007)
Urbach, E.R., Boersma, N.J., Wilkinson, M.H.F.: Vector attribute filters. In: ISMM 2005. Computational Imaging and Vision, vol. 30, pp. 95–104. Springer, Heidelberg (2005)
Jones, R.: Connected filtering and segmentation using component trees. Computer Vision and Image Understanding 75(3), 215–228 (1999)
Urbach, E.R., Wilkinson, M.H.F.: Shape-only granulometries and gray-scale shape filters. In: ISMM 2002, pp. 305–314. CSIRO Publishing (2002)
Ouzounis, G.K., Wilkinson, M.H.F.: Mask-based second-generation connectivity and attribute filters. IEEE Transactions on Pattern Analysis and Machine Intelligence 29(6), 990–1004 (2007)
Urbach, E.R., Roerdink, J.B.T.M., Wilkinson, M.H.F.: Connected shape-size pattern spectra for rotation and scale-invariant classification of gray-scale images. IEEE Transactions on Pattern Analysis and Machine Intelligence 29(2), 272–285 (2007)
Naegel, B., Passat, N., Boch, N., Kocher, M.: Segmentation using vector-attribute filters: methodology and application to dermatological imaging. In: ISMM 2007. INPE, vol. 1, pp. 239–250 (2007)
Mosorov, V.: A main stem concept for image matching. Pattern Recognition Letters 26(8), 1105–1117 (2005)
Alajlan, N., Kamel, M.S., Freeman, G.H.: Geometry-based image retrieval in binary image databases. IEEE Transactions on Pattern Analysis and Machine Intelligence 30(6), 1003–1013 (2008)
Dokládal, P., Bloch, I., Couprie, M., Ruijters, D., Urtasun, R., Garnero, L.: Topologically controlled segmentation of 3D magnetic resonance images of the head by using morphological operators. Pattern Recognition 36(10), 2463–2478 (2003)
Wilkinson, M.H.F., Westenberg, M.A.: Shape preserving filament enhancement filtering. In: Niessen, W.J., Viergever, M.A. (eds.) MICCAI 2001. LNCS, vol. 2208, pp. 770–777. Springer, Heidelberg (2001)
Vapnik, V.: Statistical Learning Theory. Wiley-Interscience, New York (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Caldairou, B., Naegel, B., Passat, N. (2009). Segmentation of Complex Images Based on Component-Trees: Methodological Tools. In: Wilkinson, M.H.F., Roerdink, J.B.T.M. (eds) Mathematical Morphology and Its Application to Signal and Image Processing. ISMM 2009. Lecture Notes in Computer Science, vol 5720. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03613-2_16
Download citation
DOI: https://doi.org/10.1007/978-3-642-03613-2_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03612-5
Online ISBN: 978-3-642-03613-2
eBook Packages: Computer ScienceComputer Science (R0)