ALOE: Augmented Local Operator for Edge Detection

  • Maria De Marsico
  • Michele Nappi
  • Daniel RiccioEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8814)


We present here a novel approach to edge detection exploiting a local operator. One of the advantages of such operator is that its results are augmented with the edge direction without any further processing.


Edge detection Local operator Divided difference method 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Bergholm, F.: Edge focusing. IEEE Transactions on Pattern Analysis and Machine Intelligence 9, 726–741 (1987)CrossRefGoogle Scholar
  2. 2.
    Canny, J.: A Computational Approach to Edge Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 8(6), 679–698 (1986)CrossRefGoogle Scholar
  3. 3.
    Gao, W., Zhan, X., Yang, L., Liu, H.: An improved Sobel edge detection. In: 3rd IEEE International Conference on Computer Science and Information Technology (ICCSIT), vol. 5, pp. 67–71 (2010)Google Scholar
  4. 4.
    Gonzalez, R.C., Woods, R.E.: Digital image processing. Prentice Hall, Upper Saddle River (2008)Google Scholar
  5. 5.
    Jabid, T., Kabir, M.H., Chae, O.: Local directional pattern (LDP)–A robust image descriptor for object recognition. In: Seventh IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), pp. 482–487 (2010)Google Scholar
  6. 6.
    Kirsch, R.: Computer determination of the constituent structure of biological images. Computers and Biomedical Research 4, 315–328 (1971)CrossRefGoogle Scholar
  7. 7.
    Konishi, S., Yuille, A.L., Coughlan, J.M., Zhu, S.C.: Statistical Edge Detection: Learning and Evaluating Edge Cues. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(1), 57–74 (2003)CrossRefGoogle Scholar
  8. 8.
    Lee, J., Haralick, R.M., Shapiro, L.G.: Morphologic edge detection. IEEE Journal of Robotics and Automation 3(2), 142–156 (1987)CrossRefGoogle Scholar
  9. 9.
    Mainberger, M., Weickert, J.: Edge-based image compression with homogeneous diffusion. In: Jiang, X., Petkov, N. (eds.) CAIP 2009. LNCS, vol. 5702, pp. 476–483. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  10. 10.
    Marr, D., Hildreth, E.: Theory of edge detection. Proc. Royal Society of London, B 207, 187–217 (1980)CrossRefGoogle Scholar
  11. 11.
    Ojala, T., Pietikainen, M., Maenpaa, T.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(7), 971–987 (2002)CrossRefGoogle Scholar
  12. 12.
    Pinho, A.J., Almeida, L.B.: A review on edge detection based on filtering and differentiation. Revista DO DETUA 2(1), 113–126 (1997)Google Scholar
  13. 13.
    Schindler, K., Suter, D.: Object Detection by Global Contour Shape. Pattern Recognition 41(12), 3736–3748 (2008)CrossRefzbMATHGoogle Scholar
  14. 14.
    Shih, M.Y., Tseng, D.C.: A wavelet-based multiresolution edge detection. Image and Vision Computing 23, 441–451 (2005)CrossRefGoogle Scholar
  15. 15.
    Yongsheng, G., Leung, M.K.H.: Face recognition using line edge map. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(6), 764–779 (2002)CrossRefGoogle Scholar
  16. 16.
    Yu, Y., Chang, C.: A new edge detection approach based on image context analysis. Image and Vision Computing 24, 1090–1102 (2006)CrossRefGoogle Scholar
  17. 17.

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Maria De Marsico
    • 1
  • Michele Nappi
    • 2
  • Daniel Riccio
    • 3
    Email author
  1. 1.Sapienza Università di RomaRomaItalia
  2. 2.Università di SalernoSalernoItaly
  3. 3.Università di Napoli, Federico IINapoliItaly

Personalised recommendations