Scale space segmentation of color images using watersheds and fuzzy region merging

A multi-resolution segmentation approach for color images is proposed. The scale space is generated using the Perona-Malik diffusion approach and the watershed algorithm is employed to produce the regions in each scale. The dynamics of contours and the relative entropy of color region distribution a...

Full description

Saved in:
Bibliographic Details
Published inProceedings 2001 International Conference on Image Processing (Cat. No.01CH37205) Vol. 1; pp. 734 - 737 vol.1
Main Authors Makrogiannis, S., Vanhamel, I., Sahli, H., Fotopoulos, S.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2001
Subjects
Anisotropic magnetoresistance
Color
Colored noise
Cost function
Entropy
Image segmentation
Joining processes
Knowledge based systems
Merging
Noise generators
Online AccessGet full text

Cover

More Information
Summary:A multi-resolution segmentation approach for color images is proposed. The scale space is generated using the Perona-Malik diffusion approach and the watershed algorithm is employed to produce the regions in each scale. The dynamics of contours and the relative entropy of color region distribution are estimated as region dissimilarity features across the scale-space stack, and combined using a fuzzy rule based system. A minima-linking process by downward projection is carried out and subsequently the region dissimilarity, combining color, scale and homogeneity is estimated for the finer scale (localization scale). The final segmentation is derived using a previously presented merging process. To validate its performance qualitative and quantitative results are provided.
ISBN:0780367251
9780780367258
DOI:10.1109/ICIP.2001.959150