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Reseach Article
Suitability of Digital Elevation Models for Watershed Segmenting Images with Directional Illumination
by
Tahir Q. Syed,
V. Vigneron,
C. Montagne,
S. Lelandais-bonad
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 78 - Number 12 |
| Year of Publication: 2013 |
| Authors: Tahir Q. Syed, V. Vigneron, C. Montagne, S. Lelandais-bonad |
10.5120/13572-0946
|
Tahir Q. Syed, V. Vigneron, C. Montagne, S. Lelandais-bonad . Suitability of Digital Elevation Models for Watershed Segmenting Images with Directional Illumination. International Journal of Computer Applications. 78, 12 ( September 2013), 1-7. DOI=10.5120/13572-0946
@article{
10.5120/13572-0946,
author = {
Tahir Q. Syed,
V. Vigneron,
C. Montagne,
S. Lelandais-bonad
},
title = { Suitability of Digital Elevation Models for Watershed Segmenting Images with Directional Illumination },
journal = {
International Journal of Computer Applications
},
issue_date = { September 2013 },
volume = { 78 },
number = { 12 },
month = { September },
year = { 2013 },
issn = { 0975-8887 },
pages = {
1-7
},
numpages = {9},
url = {
https://ijcaonline.org/archives/volume78/number12/13572-0946/
},
doi = { 10.5120/13572-0946 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:51:21.330546+05:30
%A Tahir Q. Syed
%A V. Vigneron
%A C. Montagne
%A S. Lelandais-bonad
%T Suitability of Digital Elevation Models for Watershed Segmenting Images with Directional Illumination
%J International Journal of Computer Applications
%@ 0975-8887
%V 78
%N 12
%P 1-7
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract
This paper investigates the use of different functions for the digital elevation model input to the watershed transform. The use of gradient information is the most frequent one, but its strength varies due to illumination variations. We investigate the two major classes of input functions, distance maps and the gradient, their combinations, and propose an different function using soft clustering memberships that is not covariant with illumination.
References
- P. S. U. Adiga and B. B. Chaudhuri. An efficient method based on watershed and rule-based merging for segmentation of 3 . . D histo-pathological images. Pattern Recognition, 34(7):1449–1458, 2001.
- S. Beucher and C. Lantu´ejoul. Use of watersheds in contour detection. In International Workshop on Image Processing, pages 2. 1–2. 12, Rennes, September 1979. CCETT/IRISA.
- S. Beucher and Centre De Morphologie Mathmatique. The watershed transformation applied to image segmentation, June 28 1991.
- J. C. Bezdek. Pattern Recognition with Fuzzy Objective Function Algorithms. Plenum Press, New York, 1981.
- C. Ortiz de Solorzano, E. Garcia Rodriguez, and et al A. Jones. Segmentation of confocal microscope images of cell nuclei in thick tissue sections. Journal of Microscopy, 193(3):212–226, 1999.
- R. Deriche. Using canny's criteria to derive a recursively implemented optimal edge detector. International Journal of Computer Vision, 1(2):167–187, 1987.
- S´ebastien Derivaux, S´ebastien Lef`evre, C´edricWemmert, and Jerzy Korczak. Watershed segmentation of remotely sensed images based on a supervised fuzzy pixel classification. 2006.
- M. Frucci. A novel merging method in watershed segmentation. In ICVGIP, 2004.
- C. Lantu´ejoul. La squelettisation et son application aux mesures topologiques des mosa¨iques polycristallines. PhD thesis, Ecole des Mines de Paris, 1978.
- O. Lezoray. Segmentation d'images par morphologie math´ematique et classification de donn´ees par r´eseaux de neurones : Application `a la classification de cellules en cytologie des s´ereuses. Ph. d thesis, University of Caen, 2000.
- G. Lin, U. Adiga, K. Olson, J. F. Guzowski, C. A. Barnes, and B. Roysam. A hybrid 3D watershed algorithm incorporating gradient cues and object models for automatic segmentation of nuclei in confocal image stacks. Cytometry Part A, 56A(1):23–36, 2003.
- N. Malpica, C. Ortiz, J. J. Vaquero, A. Santos, I. Vallcorba, J. M. Garc´ia-Sagredo, and F. del Pozo. Applying watershed algorithms to the segmentation of clustered nuclei. Cytometry, 28(4):289–297, 1997.
- D. R. Martin. An empirical approach to grouping and segmentation. In Ph. D. , 2002.
- F. Meyer. Topographic distance and watershed lines. Signal Processing, 38(1):113–125, July 1994.
- F. G. Meyer and S. Beucher. Morphological segmentation. Journal of Visual Communication and Image Representation, 1(1):21–46, 1990.
- L. Najman and M. Schmitt. Watershed of a continuous function. Signal Processing, 38:99–112, 1994.
- N. Otsu. A threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man, and Cybernetics, 9(1):62–66, 1979.
- S. Philipp-Foliguet and L. Guigues. Multi-scale criteria for the evaluation of image segmentation algorithms. Journal of Multimedia, 3(5), 2008.
- A. Rosenfeld and J. Pfaltz. Distance functions on digital pictures. Pattern Recognition, 1:33–61, 1968.
- V. Vigneron, T. Q. Syed, G. Barlovatz-Meimon, M. Malo, C. Montagne, and S. Lelandais. Adaptive filtering and hypothesis testing: Application to cancerous cells detection. Pattern Recognition Letters, 31(14):2214–2224, 2010.
- L. Vincet. Segmentation et Mise en Correspondance de R'egions de Paires d'Images St´er´eoscopiques. PhD thesis, Universit´e Paris IX - Dauphine, July 1991.
- C. W¨ahlby, I. -M. Sintorn, F. Erlandsson, G. Borgefors, , and E. Bengtsson. Combining intensity, edge, and shape information for 2d and 3d segmentation of cell nuclei in tissue sections. Journal of Microscopy, 215(1):67–76, 2004.
- C. W¨ahlby, I. -M. Sintorn, and et al F. Erlandsson. Combining intensity, edge, and shape information for 2d and 3d segmentation of cell nuclei on tissue sections. Journal of Microscopy, 215(1):67–76, July 2004.
- D. L. Wilson, A. J. Baddeley, and R. A. Owens. A new metric for grey-scale image comparison. International Journal of Computer Vision, 24(1), 1997.
- W. A. Yasnoff,W. Galbraith, and J. W. Bacus. Error measures for objective assessment of scene segmentation algorithms. AQC, 1:107–121, 1979.
- Y. J. Zhang. Evaluation and comparison of different segmentation algorithms. Pattern Recognition Letters, 18:963–974, 1997.
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