DOI QR코드

DOI QR Code

Edge Detection using Morphological Amoebas Noisy Images

잡음영상에서 아메바를 이용한 형태학적 에지검출

  • Published : 2009.06.30

Abstract

Edge detection in images has been widely used in image processing system and computer vision. Morphological edge detection has used structuring elements with fixed shapes. This paper presents morphological operators with non-fixed shape kernels, or amoebas, which take into account the image contour variations to adapt their shape. Experimental results are analyzed in both qualitative analysis through visual inspection and quantitative analysis with PFOM and ROC curves. The Experiments demonstrate that these novel operators outperform classical morphological operations with a fixed, space-invariant structuring elements for edge detection applications.

Keywords

Noisy images;mathematical morphology;amoeba;edge detection;structuring element

References

  1. Canny, J. (1986). A computational approach to edge detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, 8, 679-698 https://doi.org/10.1109/TPAMI.1986.4767851
  2. Chanda, B., Kundu, M. K. and Padmaja, Y. V. (1998). A multi-scale morphologic edge detector, Pattern Recognition, 31, 1469-1478 https://doi.org/10.1016/S0031-3203(98)00014-4
  3. Fan, L., Wen, Y. and Xu, X. (2003). Research on edge detection of gray-scale image corrupted by noise based on multi-structuring elements, Parallel and Distributed Computing, Applications and Technologies, 27, 840-843
  4. Gonzalez, R. C. and Woods, R. E. (1993). Digital Image Processing, Addison-Wesley Publishing Company
  5. Lee, J. S. J., Haralick, R. M. and Sapiro, L. G. (1987). Morphologic edge detection, IEEE Journal of Robotics and Automation, RA-3, 142-156
  6. Lerallut, R., Boehm, M., Decenciere, E. and Meyer, F. (2005). Noise reduction in 3D images using morphological amoebas, Image Processing, 1, 109-112
  7. Lerallut, R., Decenciere, E. and Meyer, F. (2007). Image filtering using morphological amoebas, Image and Vision Computing, 25, 395-404 https://doi.org/10.1016/j.imavis.2006.04.018
  8. Pratt, W. (1978). Digital Image Processing, John Wiley & Sons
  9. Roushdy, M. (2006). Comparative study of edge detection algorithms applying on the grayscale noisy image using morphological filter, GVIP Journal, 6, 17-23
  10. Song, X. and Neuvo, Y. (1991). Robust edge detector based on morphological filters, Circuits and Systems, 1, 332-335
  11. Song, X. and Neuvo, Y. (1993). Robust edge detector based on morphological filters, Pattern Recognition Letters, 14, 889-894 https://doi.org/10.1016/0167-8655(93)90153-5
  12. Zhao, Y., Gui, W., Chen, Z., Tang, J. and Li, L. (2005). Medical images edge detection based on mathematical morphology, Engineering in Medicine and Biology Society, 6492-6495
  13. Zhao, Y., Gui, W. and Chen, Z. (2006). Edge detection based on multi-structure elements morphology, Intelligent Control and Automation, 2, 9795-9798
  14. Zhuang, H. and Hamano, F. (1988). A new type of effective morphologic edge detectors, In Proceedings of the Twentieth Southeastern Symposium, System Theory System Theory, 304-311