Statistical estimation of the dynamics of watershed dams

• Autorzy: Tabor Z.
• Języki publikacji: EN

Abstrakty

EN

In the present study the notion of watershed contour dynamics, defined within the framework of mathematical morphology, is examined. It is shown that the dynamics are a direct measure of the 'sharpness' of transition between neighboring watershed basins. The expressions for the expected value and the statistical error of the estimation of contour dynamics are derived in the presence of noise, based on extreme value theory. The sensitivity of contour dynamics to noise is studied. A statistical approach to the notion of contour dynamics is developed and a definition of statistical dynamics is proposed.

Słowa kluczowe

EN

hierarchical segmentation; contour dynamics; mathematical morphology; statistical analysis

PL

segmentacja hierarchiczna; dynamika konturowa; morfologia matematyczna; analiza statystyczna

• Wydawca: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2009
• Tom: Vol. 19, no 2
• Strony: 349--360
• Opis fizyczny: Bibliogr. 9 poz., rys., wykr.

Twórcy

autor

Tabor Z.

• Institute of Applied Computer Science, Cracow University of Technology, al. Jana Pawła II 37, 31-864 Cracow, Poland

Bibliografia

• [1] Beucher, S. and Lantuéjoul, C. (1979). Use of watersheds in contour detection, Proceedings of the International Workshop on Image Processing, Real-Time Motion Detection/Estimation, Rennes, France, pp.17-21.
• [2] Beucher, S. and Meyer, F. (1993). The morphological approach to segmentation: The watershed transformation, in E. Dougherthy (Ed.), Mathematical Morphology in Image Processing, Marcel Dekker, New York, NY, pp.433-481.
• [3] Beucher, S. (1994). Watershed, hierarchical segmentation and waterfall algorithm, in J. Serra and P. Soille (Eds.), Mathematical Morphology and Its Application to Image Processing, Kluwer Academic Publishers, Dordrecht, pp.69-76.
• [4] Burry, K. V. (1975). Statistical Methods in Applied Science, John Wiley&Sons, New York, NY.
• [5] Haris, K., Efstratiadis, S. N., Maglaveras, N. and Katsaggelos, A.K. (1998). Hybrid image segmentation using watersheds and fast region merging, IEEE Transactions on Image Processing 7(12): 1684-1699.
• [6] Haris, K., Efstratiadis, S. N. and Maglaveras, N. (2001). Hierarchical image segmentation based on contour dynamics, Proceedings of the International Conference on Image Processing, Thessaloniki, Greece, Vol. 1, pp. 54-57.
• [7] Grimaud, M. (1992). A new measure of contrast: Dynamics, Proceedings of the SPIE Conference on Image Algebra and Morphological Processing III, San Diego, CA, USA, Vol. 1769, pp.292-305.
• [8] Najman, L. and Schmitt, M. (1996). Geodesic saliency of watershed contours and hierarchical segmentation, IEEE Transactions on Pattern Analysis and Machine Intelligence 18(12): 1163-1173.
• [9] Vincent, L. and Soille, P. (1991). Watersheds in digital spaces: An efficient algorithm based on immersion simulations, IEEE Transactions on Pattern Analysis and Machine Intelligence 13(6): 583-598.