Indentation and Protrusion Detection and Its Applications

  • Tim K. Lee
  • M. Stella Atkins
  • Ze-Nian Li
Conference paper
Part of the Lecture Notes in Computer Science 2106 book series (LNCS, volume 2106)


In this paper, we investigated the mechanism of dividing a 2Dobject border into a set of local and global indentation and protrusion segments by extending the classic curvature scale-space filtering method. The resultant segments, arranged in hierarchical structures, can represent the object shape. Applying this technique, we derived a border irregularity measure for pigmented skin lesions. The measure correlated well with experienced dermatologists’ evaluations and may be useful for measuring the malignancy of the lesion. Furthermore, we can use the method to discover all the bays in an aerial map.


Smoothing Process Melanocytic Lesion Apex Point Curvature Extremum Structure Irregularity 
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  1. 1.
    Nevaita, R., Binford, T.O.: Description and recognition of curved objects. Artificial Intelligence 8 (1977) 77–98.CrossRefGoogle Scholar
  2. 2.
    Pentland, A.P.: Recognition by parts. In:IEEE International Conference on Computer Vision (1987) 612–620.Google Scholar
  3. 3.
    Lou, S.L., Chang, C.L., Lin, K.P., Chen, T.S.: Object-based deformation technique for 3D CT lung nodule detection. In: SPIE Medical Imaging, San Diego (1999) 1544–1552.Google Scholar
  4. 4.
    Blum, H., Nagel, R.N.: Shape description using weighted symmetric axis features. Pattern Recognition 10 (1978) 167–180.zbMATHCrossRefGoogle Scholar
  5. 5.
    Attneave, F.: Some informational aspects of visual perception. Psychol. Rev. 61 (1954) 183–193.CrossRefGoogle Scholar
  6. 6.
    Hoffman, D.D., Richards, W.A.: Parts of recognition. Cognition 18 (1985) 65–96.CrossRefGoogle Scholar
  7. 7.
    Richards, W., Hoffman, D.D.: Condon Constraints on Closed 2D Shapes. Computer Vision, Graphics, and Image Processing 31 (1985) 265–281.CrossRefGoogle Scholar
  8. 8.
    Siddiqi, K., Kimia, B.B.: Parts of visual form: computational aspects. IEEE Transactions on Pattern Analysis and Machine Intelligence 17 (1995) 239–251.CrossRefGoogle Scholar
  9. 9.
    Mokhtarian, F., Mackworth, A.: Scale-based description and recognition of planar curves and two-dimensional shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence 8 (1986) 34–43.CrossRefGoogle Scholar
  10. 10.
    Mokhtarian, F.: Silhouette-based object recognition through curvature scale space. IEEE Transactions on Pattern Analysis and Machine Intelligence 17 (1995) 539–544.CrossRefGoogle Scholar
  11. 11.
    Mokhtarian, F., Suomela, R.: Robust image corner detection through curvature scale space. IEEE Transactions Pattern Analysis and Machine Intelligence 20 (1998) 1376–1381.CrossRefGoogle Scholar
  12. 12.
    Lee, T.K., Atkins, M.S.: A new approach to measure border irregularity for melanocytic lesions. In: SPIE Medical Imaging 2000, San Diego (2000) 668–675.Google Scholar
  13. 13.
    Mokhtarian, F., Mackworth, A.K.: A theory of multiscale, curvature-based shape representation for planar curves. IEEE Transactions on Pattern Analysis and Machine Intelligence 14 (1992) 789–805.CrossRefGoogle Scholar
  14. 14.
    Lindeberg, T.: Scale-space Theory in Computer Vision Kluwer Academic Publishers, Boston (1994).CrossRefGoogle Scholar
  15. 15.
    Lee, T., Atkins, S., Gallagher, R., MacAulay, C., Coldman, A., McLean, D.: Describing the structural shape of melanocytic lesions. In: SPIE Medical Imaging 1999, San Diego (1999) 1170–1179.Google Scholar
  16. 16.
    Lee, T.K., Atkins, M.S.: A new shape measure for melanocytic lesions. In: Medical Image Understanding and Analysis 2000, London, England (2000) 25–28.Google Scholar
  17. 17.
    Maize, J.C., Ackerman, A.B.: Pigmented Lesions of the Skin Lea & Febiger, Philadelphia (1987).Google Scholar
  18. 18.
    Rivers, J.K.: Melanoma. Lancet 347 (1996) 803–807.CrossRefGoogle Scholar
  19. 19.
    Claridge, E., Hall, P.N., Keefe, M., Allen, J.P.: Shape analysis for classification of malignant melanoma. Journal Biomed. Eng. 14 (1992) 229–234.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Tim K. Lee
    • 1
    • 2
  • M. Stella Atkins
    • 2
  • Ze-Nian Li
    • 2
  1. 1.Cancer Control Research ProgramBC Cancer AgencyVancouverCanada
  2. 2.Simon Fraser University, School of Computing ScienceBurnabyCanadaV5A 1S6

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