This Article 
 Bibliographic References 
 Add to: 
A Multiresolution Hierarchical Approach to Image Segmentation Based on Intensity Extrema
June 1990 (vol. 12 no. 6)
pp. 529-540

A computer algorithm which segments gray-scale images into regions of interest (objects) has been developed. These regions can provide the basis for scene analysis (including shape-parameter calculation) or surface-based, shaded-graphics display. The algorithm creates a tree structure for image description by defining a linking relationship between pixels in successively blurred versions of the initial image. The image is described in terms of nested light and dark regions. This algorithm, successfully implemented in one, two, and three dimensions, can theoretically work with any number of dimensions. The interactive postprocessing developed technique selects regions from the descriptive tree for display in several ways: pointing to a branch of the image description tree, specifying by sliders the range of scale and/or intensity of all regions which should be displayed, and pointing (on the original image) to any pixel in the desired region. The algorithm has been applied to approximately 15 computer tomography (CT) images of the abdomen.

[1] P. J. Burt, T. Hong, and A. Rosenfeld, "Segmentation and estimation of image region properties through cooperative hierarchical computation,"IEEE Trans. Syst., Man, Cybern., vol. SMC-11, no. 12, pp. 802-809, 1981.
[2] J. L. Crowley and A. C. Parker, "A representation for shape based on peaks and ridges in the difference of low-pass transform,"IEEE Trans. Pattern Anal. Machine Intell., vol. PAMI-6, no. 2, pp. 156- 169, 1984.
[3] Y. Cheng and S. Lu, "Waveform correlation by tree matching,"IEEE Trans. Pattern Anal. Machine Intell., vol. PAMI-7, no. 3, pp. 299- 305, 1985.
[4] F. Bergholm, "Edge focusing,"IEEE Trans. Pattern Anal. Machine Intell., vol. PAMI-9, pp. 726-741, 1987.
[5] J. M. Beaulieu and M. Goldberg, "Hierarchy in picture segmentation: A stepwise optimization approach,"IEEE Trans. Pattern Anal. Machine Intell., vol. 11, no. 2, pp. 150-163, 1989.
[6] Y. Lu and R. C. Jain, "Behavior of edges in scale space,"IEEE Trans. Pattern Anal. Machine Intell., vol. 11, no. 4, pp. 337-356, 1989.
[7] S. L. Tanimoto, Ed.,IEEE Trans. Pattern Anal. Machine Intell., Special Section on Multiresolution Representation, vol. 11, no. 7, pp. 673-748, 1989.
[8] J. J. Koenderink, "The structure of images,"Biol. Cybern., vol. 50, pp. 363-370, 1984.
[9] S. M. Pizer, J. J. Koenderink, L. M. Lifshitz, L. Helmink, and A. D. J. Kaasjager, "An image description for object definition, based on extremal regions in the stack," inProc. 9th Conf. Information Processing in Medical Imaging. Boston, MA: Martinus Nijhoff, 1986.
[10] E. C. Zachmanoglou and D. W. Thoe,Introduction of Partial Differential Equations with Applications. Baltimore, MD: Williams and Wilkins, 1976.
[11] L. M. Lifshitz, "Image segmentation via multiresolution extrema following," dissertation, Univ. North Carolina, Chapel Hill, 1987.
[12] F. John,Partial Differential Equations. New York: Springer-Verlag, 1982.
[13] L. Toet, J. J. Koenderink, C. N. deGraaf, and P. Zuidema, "The treatment of image boundaries in the case of progressive defocussing," Dep. Medical and Physiological Physics, State Univ. Utrecht, The Netherlands, Internal Rep., 1986.
[14] M. A. Cohen and S. Grossberg, "Neural dynamics of brightness perception: Features, boundaries, diffusion, and resonance,"Perception and Psychophys., vol. 36, no. 5, pp. 428-456, 1984.
[15] J. K. T. Lee, S. S. Sagel, and R. Stanley,Computed Body Tomography. New York: Raven, 1983.
[16] T. H. Hong, K. A. Narayanan, S. Peleg, A. Rosenfeld, and T. Silberberg, "Image smoothing and segmentation by multiresolution pixel linking: Further experiments and extensions,"IEEE Trans. Syst., Man, Cybern., vol. SMC-12, no. 5, pp. 611-622, 1982.

Index Terms:
multiresolution hierarchical approach; image segmentation; intensity extrema; gray-scale images; scene analysis; tree structure; image description; computer tomography; computerised picture processing; computerised tomography; trees (mathematics)
L.M. Lifshitz, S.M. Pizer, "A Multiresolution Hierarchical Approach to Image Segmentation Based on Intensity Extrema," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 12, no. 6, pp. 529-540, June 1990, doi:10.1109/34.56189
Usage of this product signifies your acceptance of the Terms of Use.