| id |
sigradi2010_324 |
| authors |
Toranzo, Lorca Gustavo; Pereira Barzaga Osvaldo; Arzola Ruiz José |
| year |
2010 |
| title |
Segmentación de imágenes digitales mediante técnicas de clustering complementadas con técnicas de crecimiento de regiones [Digital image segmentation through clustering techniques, enhanced by region growing techniques] |
| source |
SIGraDi 2010_Proceedings of the 14th Congress of the Iberoamerican Society of Digital Graphics, pp. Bogotá, Colombia, November 17-19, 2010, pp. 324-327 |
| summary |
This paper proposes a solution to the problem of digital image segmentation based on clustering techniques. K - means and fuzzy k - means are clustering algorithms detailed within this study. We propose novel modifications to k - means and fuzzy k - means algorithms to vary objective functions and to use color difference as a distance measure. These new algorithms are guaranteed to obtain the same results as the originals while considerably reducing the execution time. Pixel growing is used to obtain connected structures in the results of clustering algorithms. |
| keywords |
clustering; fuzzy k - means; image segmentation; k - means |
| series |
SIGRADI |
| email |
|
| full text |
 file.pdf (159,130 bytes) |
| references |
Content-type: text/plain
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González, R. C. y Wood, R. E. (2001)
 Digital image processing
, New Jersey: Prentice Hall
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Jain, A. K., Murty, M. N. y Flynn, P. J. (1999)
Data clustering: a Review
, ACM Computing Surveys, 265-317
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Sonka, M., Hlavac, V. y Boyle, R. (1993)
Image processing: analysis and machine vision
, Capmam and Hall Computing
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| last changed |
2016/03/10 10:01 |
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